IDEAS home Printed from https://ideas.repec.org/e/c/phr5.html
   My authors  Follow this author

Wolfgang Karl Härdle
(Wolfgang Karl Haerdle)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Author Profile
    1. Peers at Work as of August 2016
      by Matthew Kahn in Environmental and Urban Economics on 2016-09-04 19:36:00

Working papers

  1. Härdle, Wolfgang & Klochkov, Yegor & Petukhina, Alla & Zhivotovskiy, Nikita, 2021. "Robustifying Markowitz," IRTG 1792 Discussion Papers 2021-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Bruno Spilak & Wolfgang Karl Hardle, 2022. "Risk budget portfolios with convex Non-negative Matrix Factorization," Papers 2204.02757, arXiv.org, revised Jun 2023.

  2. Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2021. "FRM Financial Risk Meter for Emerging Markets," IRTG 1792 Discussion Papers 2021-002, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Wang, Ruting & Althof, Michael & Härdle, Wolfgang, 2021. "A financial risk meter for China," IRTG 1792 Discussion Papers 2021-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

  3. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang, 2021. "K-expectiles clustering," IRTG 1792 Discussion Papers 2021-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    2. Aneiros, Germán & Horová, Ivana & Hušková, Marie & Vieu, Philippe, 2022. "On functional data analysis and related topics," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    3. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    4. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  4. Saef, Danial & Nagy, Odett & Sizov, Sergej & Härdle, Wolfgang, 2021. "Understanding jumps in high frequency digital asset markets," IRTG 1792 Discussion Papers 2021-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Danial Saef & Yuanrong Wang & Tomaso Aste, 2022. "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing," Papers 2208.12614, arXiv.org, revised Sep 2022.

  5. Zinovyev, Elizaveta & Reule, Raphael C. G. & Härdle, Wolfgang, 2021. "Understanding Smart Contracts: Hype or hope?," IRTG 1792 Discussion Papers 2021-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.

  6. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Aneiros, Germán & Horová, Ivana & Hušková, Marie & Vieu, Philippe, 2022. "On functional data analysis and related topics," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

  7. Li, Erqian & Härdle, Wolfgang & Dai, Xiaowen & Tian, Maozai, 2021. "Penalized weigted competing risks models based on quantile regression," IRTG 1792 Discussion Papers 2021-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.

  8. Khowaja, Kainat & Shcherbatyy, Mykhaylo & Härdle, Wolfgang Karl, 2021. "Surrogate Models for Optimization of Dynamical Systems," IRTG 1792 Discussion Papers 2021-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.

  9. Guo, Li & Härdle, Wolfgang & Tao, Yubo, 2021. "A time-varying network for cryptocurrencies," IRTG 1792 Discussion Papers 2021-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Paola Stolfi & Mauro Bernardi & Davide Vergni, 2022. "Robust estimation of time-dependent precision matrix with application to the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.

  10. Ren, Rui & Althof, Michael & Härdle, Wolfgang Karl, 2020. "Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis," IRTG 1792 Discussion Papers 2020-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    2. Theodore Pelagidis & Eleftheria Kostika, 2022. "Investigating the role of central banks in the interconnection between financial markets and cryptoassets," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 481-507, September.
    3. Wang, Ruting & Althof, Michael & Härdle, Wolfgang Karl, 2023. "A financial risk meter for China," Emerging Markets Review, Elsevier, vol. 56(C).
    4. Wang, Ruting & Althof, Michael & Härdle, Wolfgang, 2021. "A financial risk meter for China," IRTG 1792 Discussion Papers 2021-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

  11. Spilak, Bruno & Härdle, Wolfgang Karl, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," IRTG 1792 Discussion Papers 2020-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Bruno Spilak & Wolfgang Karl Hardle, 2022. "Risk budget portfolios with convex Non-negative Matrix Factorization," Papers 2204.02757, arXiv.org, revised Jun 2023.

  12. Trimborn, Simon & Härdle, Wolfgang Karl, 2020. "CRIX an Index for cryptocurrencies," IRTG 1792 Discussion Papers 2020-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Yan, Lei & Mirza, Nawazish & Umar, Muhammad, 2022. "The cryptocurrency uncertainties and investment transitions: Evidence from high and low carbon energy funds in China," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    3. Sergey Nasekin & Cathy Yi-Hsuan Chen, 2020. "Deep learning-based cryptocurrency sentiment construction," Digital Finance, Springer, vol. 2(1), pages 39-67, September.
    4. Georg Keilbar & Yanfen Zhang, 2021. "On cointegration and cryptocurrency dynamics," Digital Finance, Springer, vol. 3(1), pages 1-23, March.
    5. Xinwen Ni & Wolfgang Karl Hardle & Taojun Xie, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," Papers 2009.12121, arXiv.org, revised Aug 2021.
    6. Pennoni, Fulvia & Bartolucci, Francesco & Forte, Gianfranco & Ametrano, Ferdinando, 2020. "Exploring the dependencies among main cryptocurrency log-returns: A hidden Markov model," MPRA Paper 106150, University Library of Munich, Germany.
    7. Moser, Stefanie & Brauneis, Alexander, 2023. "Should you listen to crypto YouTubers?," Finance Research Letters, Elsevier, vol. 54(C).
    8. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    9. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023. "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
    10. Matic, Jovanka Lili & Packham, Natalie & Härdle, Wolfgang Karl, 2021. "Hedging Cryptocurrency Options," MPRA Paper 110774, University Library of Munich, Germany.
    11. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
    12. ALIU Florin & NUHIU Artor & KNAPKOVA Adriana & LUBISHTANI Ermal & TRAN Khang, 2021. "Do Cryptocurrencies Offer Diversification Benefits For Equity Portfolios?," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 16(2), pages 5-18, August.
    13. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2020. "Tail Risk Measurement In Crypto-Asset Markets," DEM Working Papers Series 186, University of Pavia, Department of Economics and Management.
    14. Brauneis, Alexander & Mestel, Roland & Theissen, Erik, 2021. "What drives the liquidity of cryptocurrencies? A long-term analysis," Finance Research Letters, Elsevier, vol. 39(C).
    15. Béatrice Boulu-Reshef & Catherine Bruneau & Maxime Nicolas & Thomas Renault, 2023. "An Experimental Analysis of Investor Sentiment," Post-Print hal-04222561, HAL.
    16. Aikaterini Koutsouri & Francesco Poli & Elise Alfieri & Michael Petch & Walter Distaso & William J Knottenbelt, 2019. "Balancing Cryptoassets and Gold: A Weighted-Risk-Contribution Index for the Alternative Asset Space," Post-Print hal-02952145, HAL.
    17. Umar, Zaghum & Usman, Muhammad & Choi, Sun-Yong & Rice, John, 2023. "Diversification benefits of NFTs for conventional asset investors: Evidence from CoVaR with higher moments and optimal hedge ratios," Research in International Business and Finance, Elsevier, vol. 65(C).
    18. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    19. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Härdle, 2023. "Hedging cryptocurrency options," Review of Derivatives Research, Springer, vol. 26(1), pages 91-133, April.
    20. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Post-Print hal-04218488, HAL.
    21. Christoph J. Borner & Ingo Hoffmann & Jonas Krettek & Lars M. Kurzinger & Tim Schmitz, 2021. "Bitcoin: Like a Satellite or Always Hardcore? A Core-Satellite Identification in the Cryptocurrency Market," Papers 2105.12336, arXiv.org.
    22. Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
    23. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    24. Feng, Wenjun & Zhang, Zhengjun, 2023. "Risk-weighted cryptocurrency indices," Finance Research Letters, Elsevier, vol. 51(C).
    25. Ren, Rui & Althof, Michael & Härdle, Wolfgang Karl, 2020. "Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis," IRTG 1792 Discussion Papers 2020-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Saman Adhami & Dominique Guegan, 2019. "Crypto assets: the role of ICO tokens within a well-diversified portfolio," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02353656, HAL.
    27. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    28. Wang, Qiyu & Chong, Terence Tai-Leung, 2021. "Factor pricing of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    29. Luo, Di & Mishra, Tapas & Yarovaya, Larisa & Zhang, Zhuang, 2021. "Investing during a Fintech Revolution: Ambiguity and return risk in cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    30. Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa & Wang, Yizhi, 2022. "The cryptocurrency uncertainty index," Finance Research Letters, Elsevier, vol. 45(C).
    31. Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    32. Borgards, Oliver & Czudaj, Robert L., 2020. "The prevalence of price overreactions in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    33. Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
    34. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    35. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    36. Ahmad Chokor & Élise Alfieri, 2021. "Long and short-term impacts of regulation in the cryptocurrency market," Post-Print hal-03275473, HAL.
    37. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
    38. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    39. Zhang, Wei & Li, Yi & Xiong, Xiong & Wang, Pengfei, 2021. "Downside risk and the cross-section of cryptocurrency returns," Journal of Banking & Finance, Elsevier, vol. 133(C).
    40. Pho, Kim Hung & Ly, Sel & Lu, Richard & Hoang, Thi Hong Van & Wong, Wing-Keung, 2021. "Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    41. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    42. Konstantin Gorgen & Jonas Meirer & Melanie Schienle, 2022. "Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests," Papers 2203.08224, arXiv.org, revised Jun 2022.
    43. Konstantin Hausler, 2022. "ETF construction on CRIX," Papers 2211.15260, arXiv.org, revised Mar 2023.
    44. Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
    45. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    46. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    47. Christoph J. Börner & Ingo Hoffmann & Jonas Krettek & Tim Schmitz, 2022. "Bitcoin: like a satellite or always hardcore? A core–satellite identification in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 310-321, July.
    48. De Pace, Pierangelo & Rao, Jayant, 2023. "Comovement and instability in cryptocurrency markets," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 173-200.
    49. Adela Socol, 2020. "Cryptocurrencies Between Utopia And Reality," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 5, pages 200-207, October.
    50. Chen, Cathy Yi-Hsuan & Després, Roméo & Guo, Li & Renault, Thomas, 2019. "What makes cryptocurrencies special? Investor sentiment and return predictability during the bubble," IRTG 1792 Discussion Papers 2019-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    51. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang, 2021. "K-expectiles clustering," IRTG 1792 Discussion Papers 2021-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    52. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2022. "Bitcoin unchained: Determinants of cryptocurrency exchange liquidity," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 106-122.
    53. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    54. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    55. Platanakis, Emmanouil & Urquhart, Andrew, 2020. "Should investors include Bitcoin in their portfolios? A portfolio theory approach," The British Accounting Review, Elsevier, vol. 52(4).
    56. Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    57. Umar, Zaghum & Trabelsi, Nader & Alqahtani, Faisal, 2021. "Connectedness between cryptocurrency and technology sectors: International evidence," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 910-922.
    58. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018. "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers 2018-056, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    59. Chokor, Ahmad & Alfieri, Elise, 2021. "Long and short-term impacts of regulation in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 157-173.
    60. Saman Adhami & Dominique Guégan, 2019. "Crypto assets: the role of ICO tokens within a well-diversified portfolio," Documents de travail du Centre d'Economie de la Sorbonne 19020, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    61. Ni, Xinwen & Härdle, Wolfgang Karl & Xie, Taojun, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," IRTG 1792 Discussion Papers 2020-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    62. Saman Adhami & Dominique Guegan, 2020. "Crypto assets: the role of ICO tokens within a well-diversified portfolio," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(2), pages 219-241, June.
    63. Fabian Woebbeking, 2021. "Cryptocurrency volatility markets," Digital Finance, Springer, vol. 3(3), pages 273-298, December.
    64. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2022. "Crypto Asset Portfolio Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    65. Saman Adhami & Dominique Guegan, 2019. "Crypto assets: the role of ICO tokens within a well-diversified portfolio," Post-Print halshs-02353656, HAL.
    66. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    67. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    68. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    69. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Hou, Ai Jun & Wang, Weining, 2018. "Pricing Cryptocurrency options: the case of CRIX and Bitcoin," IRTG 1792 Discussion Papers 2018-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    70. Aslanidis, Nektarios & Fernández Bariviera, Aurelio & Savva, Christos S., 2020. "Weekly dynamic conditional correlations among cryptocurrencies and traditional assets," Working Papers 2072/417680, Universitat Rovira i Virgili, Department of Economics.
    71. Rehman, Mobeen Ur & Katsiampa, Paraskevi & Zeitun, Rami & Vo, Xuan Vinh, 2023. "Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies," Emerging Markets Review, Elsevier, vol. 55(C).
    72. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    73. Élise Alfieri & Yann Ferrat, 2022. "The larger compensation for miners, the higher positive effect on the financial performance of cryptocurrencies [Une meilleure rémunération des mineurs : un effet positif sur la performance financi," Post-Print hal-03670074, HAL.
    74. Elsayed, Ahmed H. & Gozgor, Giray & Yarovaya, Larisa, 2022. "Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices," Finance Research Letters, Elsevier, vol. 47(PB).
    75. Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.
    76. Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa, 2022. "The Effects of Central Bank Digital Currencies News on Financial Markets," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    77. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    78. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.

  13. Lin, Min-Bin & Khowaja, Kainat & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2020. "Blockchain mechanism and distributional characteristics of cryptos," IRTG 1792 Discussion Papers 2020-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Elizaveta Zinovyeva & Raphael C. G. Reule & Wolfgang Karl Hardle, 2021. "Understanding Smart Contracts: Hype or Hope?," Papers 2103.08447, arXiv.org.
    2. Ingo Weber & Mark Staples, 2022. "Programmable money: next-generation blockchain-based conditional payments," Digital Finance, Springer, vol. 4(2), pages 109-125, September.
    3. Stefan Craß & Alexander Eisl & Nedim Begic & Romana Polt, 2022. "Die Rolle moderner Technologien, insbesondere Blockchain, in der Lieferkettenverantwortung," FIW Research Reports series VIII-006, FIW.

  14. Chen, Shiyi & Härdle, Wolfgang Karl & Wang, Li, 2020. "Estimation and Determinants of Chinese Banks’ Total Factor Efficiency: A New Vision Based on Unbalanced Development of Chinese Banks and Their Overall Risk," IRTG 1792 Discussion Papers 2020-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Wang, Weining & Wooldridge, Jeffrey M. & Xu, Mengshan, 2020. "Improved Estimation of Dynamic Models of Conditional Means and Variances," IRTG 1792 Discussion Papers 2020-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Zhen Shi & Shijiong Qin & Yung-ho Chiu & Xiaoying Tan & Xiaoli Miao, 2021. "The impact of gross domestic product on the financing and investment efficiency of China’s commercial banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.

  15. Meng, Lina & Zhou, Yinggang & Zhang, Ruige & Ye, Zhen & Xia, Senmao & Cerulli, Giovanni & Casady, Carter & Härdle, Wolfgang Karl, 2020. "The Effect of Control Measures on COVID-19 Transmission and Work Resumption: International Evidence," IRTG 1792 Discussion Papers 2020-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Wang, Weining & Wooldridge, Jeffrey M. & Xu, Mengshan, 2020. "Improved Estimation of Dynamic Models of Conditional Means and Variances," IRTG 1792 Discussion Papers 2020-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Cuicui Lu & Weining Wang & Jeffrey M. Wooldridge, 2018. "Using generalized estimating equations to estimate nonlinear models with spatial data," Papers 1810.05855, arXiv.org.

  16. Ni, Xinwen & Härdle, Wolfgang Karl & Xie, Taojun, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," IRTG 1792 Discussion Papers 2020-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Elizaveta Zinovyeva & Raphael C. G. Reule & Wolfgang Karl Hardle, 2021. "Understanding Smart Contracts: Hype or Hope?," Papers 2103.08447, arXiv.org.
    2. Cristina Sbirneciu & Nicoleta Valentina Florea, 2023. "Evaluating the Impact of Emerging Technologies on the ECB's Mandate: Can the European Central Bank Use Distributed Ledger Technology and Digital Euro to Advance Financial Inclusion in Europe?," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 1059-1070, August.

  17. Härdle, Wolfgang Karl & Schulz, Rainer & Xie, Taojun, 2019. "Cooling Measures and Housing Wealth: Evidence from Singapore," IRTG 1792 Discussion Papers 2019-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  18. Pele, Daniel Traian & Wesselhöfft, Niels & Härdle, Wolfgang Karl & Kolossiatis, Michalis & Yatracos, Yannis, 2019. "Phenotypic convergence of cryptocurrencies," IRTG 1792 Discussion Papers 2019-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  19. Victor Chernozhukov & Wolfgang Härdle & Chen Huang & Weining Wang, 2019. "LASSO-Driven Inference in Time and Space," CeMMAP working papers CWP20/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
    2. Michael Kostmann & Wolfgang K. Härdle, 2019. "Forecasting in Blockchain-Based Local Energy Markets," Energies, MDPI, vol. 12(14), pages 1-27, July.
    3. Zbonakova, Lenka & Pio Monti, Ricardo & Härdle, Wolfgang Karl, 2018. "Towards the interpretation of time-varying regularization parameters in streaming penalized regression models," IRTG 1792 Discussion Papers 2018-059, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Munday, Tim & Brookes, James, 2021. "Mark my words: the transmission of central bank communication to the general public via the print media," Bank of England working papers 944, Bank of England.
    6. Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Reprints LFIN 2021010, Université catholique de Louvain, Louvain Finance (LFIN).
    7. Smeekes, Stephan & Wijler, Etienne, 2021. "An automated approach towards sparse single-equation cointegration modelling," Journal of Econometrics, Elsevier, vol. 221(1), pages 247-276.
    8. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Dovì, Max-Sebastian & Koester, Gerrit & Nickel, Christiane, 2021. "Addressing the endogeneity of slack in Phillips Curves," Working Paper Series 2619, European Central Bank.
    17. Panxu Yuan & Xiao Guo, 2022. "High-dimensional inference for linear model with correlated errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(1), pages 21-52, January.
    18. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Alain Hecq & Luca Margaritella & Stephan Smeekes, 2023. "Granger Causality Testing in High-Dimensional VARs: A Post-Double-Selection Procedure," Journal of Financial Econometrics, Oxford University Press, vol. 21(3), pages 915-958.
    21. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    22. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    23. Chen, C. Y-H. & Härdle, W. K. & Klochkov, Y., 2019. "Influencers and Communities in Social Networks," Cambridge Working Papers in Economics 1998, Faculty of Economics, University of Cambridge.
    24. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    25. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    27. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    28. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    29. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2019. "SONIC: SOcial Network with Influencers and Communities," IRTG 1792 Discussion Papers 2019-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    30. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    31. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    32. Mihoci, Andrija & Althof, Michael & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2019. "FRM Financial Risk Meter," IRTG 1792 Discussion Papers 2019-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  20. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Brauneis, Alexander & Mestel, Roland & Theissen, Erik, 2021. "What drives the liquidity of cryptocurrencies? A long-term analysis," Finance Research Letters, Elsevier, vol. 39(C).
    2. Ugolini, Andrea & Reboredo, Juan C. & Mensi, Walid, 2023. "Connectedness between DeFi, cryptocurrency, stock, and safe-haven assets," Finance Research Letters, Elsevier, vol. 53(C).
    3. Victoria Dobrynskaya & Mikhail Dubrovskiy, 2022. "Cryptocurrencies Meet Equities: Risk Factors And Asset Pricing Relationships," HSE Working papers WP BRP 86/FE/2022, National Research University Higher School of Economics.
    4. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang, 2021. "K-expectiles clustering," IRTG 1792 Discussion Papers 2021-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  21. Chen, C. Y-H. & Härdle, W. K. & Klochkov, Y., 2019. "Influencers and Communities in Social Networks," Cambridge Working Papers in Economics 1998, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.

  22. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2019. "SONIC: SOcial Network with Influencers and Communities," IRTG 1792 Discussion Papers 2019-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    2. Guðmundsson, Guðmundur Stefán & Brownlees, Christian, 2021. "Detecting groups in large vector autoregressions," Journal of Econometrics, Elsevier, vol. 225(1), pages 2-26.

  23. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  24. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    2. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.

  25. Mihoci, Andrija & Althof, Michael & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2019. "FRM Financial Risk Meter," IRTG 1792 Discussion Papers 2019-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    3. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  26. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
    2. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    3. Paul B. Ellickson & Wreetabrata Kar & James C. Reeder, 2023. "Estimating Marketing Component Effects: Double Machine Learning from Targeted Digital Promotions," Marketing Science, INFORMS, vol. 42(4), pages 704-728, July.

  27. Zinovyeva, Elizaveta & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Antisocial Online Behavior Detection Using Deep Learning," IRTG 1792 Discussion Papers 2019-029, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.

  28. Dautel, Alexander J. & Härdle, Wolfgang Karl & Lessmann, Stefan & Seow, Hsin-Vonn, 2019. "Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks," IRTG 1792 Discussion Papers 2019-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Krystian Jaworski, 2021. "Forecasting exchange rates for Central and Eastern European currencies using country‐specific factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 977-999, September.
    2. Davood Pirayesh Neghab & Mucahit Cevik & M. I. M. Wahab, 2023. "Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning," Papers 2303.16149, arXiv.org.
    3. Fengmin Xu & Jieao Ma, 2023. "Intelligent option portfolio model with perspective of shadow price and risk-free profit," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    4. J. C. Garza Sepúlveda & F. Lopez-Irarragorri & S. E. Schaeffer, 2023. "Forecasting Forex Trend Indicators with Fuzzy Rough Sets," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 229-287, June.
    5. Daniel Poh & Bryan Lim & Stefan Zohren & Stephen Roberts, 2021. "Enhancing Cross-Sectional Currency Strategies by Context-Aware Learning to Rank with Self-Attention," Papers 2105.10019, arXiv.org, revised Jan 2022.

  29. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Sebastian A. Gehricke & Jin E. Zhang, 2020. "Modeling VXX under jump diffusion with stochastic long‐term mean," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1508-1534, October.
    2. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    4. Jui‐Cheng Hung & Hung‐Chun Liu & J. Jimmy Yang, 2023. "Does the tail risk index matter in forecasting downside risk?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3451-3466, July.
    5. Yeguang Chi & Wenyan Hao, 2020. "A Horserace of Volatility Models for Cryptocurrency: Evidence from Bitcoin Spot and Option Markets," Papers 2010.07402, arXiv.org.
    6. Albers, Stefan, 2023. "The fear of fear in the US stock market: Changing characteristics of the VVIX," Finance Research Letters, Elsevier, vol. 55(PA).
    7. Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
    8. Li, Leon, 2022. "The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk," Energy Economics, Elsevier, vol. 105(C).
    9. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    10. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Tai‐Yong Roh & Alireza Tourani‐Rad & Yahua Xu & Yang Zhao, 2021. "Volatility‐of‐volatility risk in the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 245-265, February.
    12. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    13. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Bjørn Eraker & Aoxiang Yang, 2022. "The Price of Higher Order Catastrophe Insurance: The Case of VIX Options," Journal of Finance, American Finance Association, vol. 77(6), pages 3289-3337, December.
    15. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian & Yoon, Seong-Min, 2021. "OPEC news and jumps in the oil market," Energy Economics, Elsevier, vol. 96(C).
    16. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org.
    17. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    18. Carsten H. Chong & Viktor Todorov, 2023. "Volatility of Volatility and Leverage Effect from Options," Papers 2305.04137, arXiv.org, revised Jan 2024.
    19. Qiu, Yue, 2021. "Complete subset least squares support vector regression," Economics Letters, Elsevier, vol. 200(C).
    20. Pérez, Rafaela & Ruiz, Jesús & Guinea, Laurentiu, 2023. "Asymmetric effects of financial volatility and volatility-of-volatility shocks on the energy mix," UC3M Working papers. Economics 36916, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Betton, Sandra & El Meslmani, Nabil & Switzer, Lorne N., 2022. "Volatility of implied volatility and mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 75(C).
    22. Jungah Yoon & Xinfeng Ruan & Jin E. Zhang, 2022. "VIX option‐implied volatility slope and VIX futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1002-1038, June.
    23. Kostopoulos, Dimitrios & Meyer, Steffen & Uhr, Charline, 2022. "Ambiguity about volatility and investor behavior," Journal of Financial Economics, Elsevier, vol. 145(1), pages 277-296.
    24. Chi, Yeguang & Hao, Wenyan, 2021. "Volatility models for cryptocurrencies and applications in the options market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    25. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
    26. Qiu, Yue & Wang, Yifan & Xie, Tian, 2021. "Forecasting Bitcoin realized volatility by measuring the spillover effect among cryptocurrencies," Economics Letters, Elsevier, vol. 208(C).

  30. Petukhina, Alla A. & Reule, Raphael C. G. & Härdle, Wolfgang Karl, 2019. "Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. M. Eren Akbiyik & Mert Erkul & Killian Kaempf & Vaiva Vasiliauskaite & Nino Antulov-Fantulin, 2021. "Ask "Who", Not "What": Bitcoin Volatility Forecasting with Twitter Data," Papers 2110.14317, arXiv.org, revised Dec 2022.
    2. Wen, Zhuzhu & Bouri, Elie & Xu, Yahua & Zhao, Yang, 2022. "Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    3. Donglian Ma & Hisashi Tanizaki, 2022. "Intraday patterns of price clustering in Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    4. Jahanshahloo, Hossein & Corbet, Shaen & Oxley, Les, 2022. "Seeking sigma: Time-of-the-day effects on the Bitcoin network," Finance Research Letters, Elsevier, vol. 49(C).
    5. Elizaveta Zinovyeva & Raphael C. G. Reule & Wolfgang Karl Hardle, 2021. "Understanding Smart Contracts: Hype or Hope?," Papers 2103.08447, arXiv.org.
    6. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    7. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    8. Bouri, Elie & Lau, Chi Keung Marco & Saeed, Tareq & Wang, Shixuan & Zhao, Yuqian, 2021. "On the intraday return curves of Bitcoin: Predictability and trading opportunities," International Review of Financial Analysis, Elsevier, vol. 76(C).
    9. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Ali Mehrban & Pegah Ahadian, 2024. "An adaptive network-based approach for advanced forecasting of cryptocurrency values," Papers 2401.05441, arXiv.org, revised Feb 2024.
    11. Colombo, Jefferson A. & Cruz, Fernando I. L. & Paese, Luis H. Z. & Cortes, Renan X., 2021. "The diversification benefits of cryptocurrencies in multi-asset portfolios: cross-country evidence," Textos para discussão 542, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    12. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    13. Danial Saef & Yuanrong Wang & Tomaso Aste, 2022. "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing," Papers 2208.12614, arXiv.org, revised Sep 2022.

  31. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2019. "Media-expressed tone, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2019-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.

  32. Kostmann, Michael & Härdle, Wolfgang Karl, 2019. "Forecasting in Blockchain-based Local Energy Markets," IRTG 1792 Discussion Papers 2019-014, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Kirli, Desen & Couraud, Benoit & Robu, Valentin & Salgado-Bravo, Marcelo & Norbu, Sonam & Andoni, Merlinda & Antonopoulos, Ioannis & Negrete-Pincetic, Matias & Flynn, David & Kiprakis, Aristides, 2022. "Smart contracts in energy systems: A systematic review of fundamental approaches and implementations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    2. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Haben, Stephen & Arora, Siddharth & Giasemidis, Georgios & Voss, Marcus & Vukadinović Greetham, Danica, 2021. "Review of low voltage load forecasting: Methods, applications, and recommendations," Applied Energy, Elsevier, vol. 304(C).
    4. Ioanna Andreoulaki & Aikaterini Papapostolou & Vangelis Marinakis, 2024. "Evaluating the Barriers to Blockchain Adoption in the Energy Sector: A Multicriteria Approach Using the Analytical Hierarchy Process for Group Decision Making," Energies, MDPI, vol. 17(6), pages 1-27, March.
    5. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    6. Manuel Casquiço & Bruno Mataloto & Joao C. Ferreira & Vitor Monteiro & Joao L. Afonso & Jose A. Afonso, 2021. "Blockchain and Internet of Things for Electrical Energy Decentralization: A Review and System Architecture," Energies, MDPI, vol. 14(23), pages 1-26, December.

  33. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2019. "Dynamic Network Perspective of Cryptocurrencies," IRTG 1792 Discussion Papers 2019-009, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Jacob, Daniel & Härdle, Wolfgang Karl & Lessmann, Stefan, 2019. "Group Average Treatment Effects for Observational Studies," IRTG 1792 Discussion Papers 2019-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  34. Lux, Marius & Härdle, Wolfgang Karl & Lessmann, Stefan, 2018. "Data Driven Value-at-Risk Forecasting using a SVR-GARCH-KDE Hybrid," IRTG 1792 Discussion Papers 2018-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Farid Bagheri & Diego Reforgiato Recupero & Espen Sirnes, 2023. "Leveraging Return Prediction Approaches for Improved Value-at-Risk Estimation," Data, MDPI, vol. 8(8), pages 1-22, August.
    2. Marcin Fałdziński & Piotr Fiszeder & Witold Orzeszko, 2020. "Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression," Energies, MDPI, vol. 14(1), pages 1-18, December.
    3. Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
    4. Almosova, Anna, 2018. "A Monetary Model of Blockchain," IRTG 1792 Discussion Papers 2018-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  35. Vomfell, Lara & Härdle, Wolfgang Karl & Lessmann, Stefan, 2018. "Improving Crime Count Forecasts Using Twitter and Taxi Data," IRTG 1792 Discussion Papers 2018-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Shalak Mendon & Pankaj Dutta & Abhishek Behl & Stefan Lessmann, 2021. "A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters," Information Systems Frontiers, Springer, vol. 23(5), pages 1145-1168, September.
    3. Minxuan Lan & Lin Liu & Andres Hernandez & Weiyi Liu & Hanlin Zhou & Zengli Wang, 2019. "The Spillover Effect of Geotagged Tweets as a Measure of Ambient Population for Theft Crime," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    4. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Bram Janssens & Matthias Bogaert & Mathijs Maton, 2023. "Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents," Annals of Operations Research, Springer, vol. 325(1), pages 557-588, June.
    9. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    19. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    21. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    22. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  36. Härdle, Wolfgang Karl & Harvey, Campbell R. & Reule, Raphael C. G., 2018. "Understanding Cryptocurrencies," IRTG 1792 Discussion Papers 2018-044, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Brodeur, Abel & Gray, David & Islam, Anik & Bhuiyan, Suraiya Jabeen, 2020. "A Literature Review of the Economics of COVID-19," GLO Discussion Paper Series 601, Global Labor Organization (GLO).
    2. Georg Keilbar & Yanfen Zhang, 2021. "On cointegration and cryptocurrency dynamics," Digital Finance, Springer, vol. 3(1), pages 1-23, March.
    3. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    4. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    5. Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis, 2023. "Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 852-871, July.
    6. Emilio Barucci & Giancarlo Giuffra Moncayo & Daniele Marazzina, 2022. "Cryptocurrencies and stablecoins: a high-frequency analysis," Digital Finance, Springer, vol. 4(2), pages 217-239, September.
    7. Wei Zhang & Yi Li, 2023. "Liquidity risk and expected cryptocurrency returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 472-492, January.
    8. Klein, Tony & Hien, Pham Thu & Walther, Thomas, 2018. "Bitcoin Is Not the New Gold: A Comparison of Volatility, Correlation, and Portfolio Performance," QBS Working Paper Series 2018/01, Queen's University Belfast, Queen's Business School.
    9. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Elizaveta Zinovyeva & Raphael C. G. Reule & Wolfgang Karl Hardle, 2021. "Understanding Smart Contracts: Hype or Hope?," Papers 2103.08447, arXiv.org.
    11. Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    12. Yaya, OlaOluwa S. & Lukman, Adewale F. & Vo, Xuan Vinh, 2022. "Persistence and volatility spillovers of bitcoin price to gold and silver prices," Resources Policy, Elsevier, vol. 79(C).
    13. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
    14. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    15. Allen, Franklin & Gu, Xian & Jagtiani, Julapa, 2022. "Fintech, Cryptocurrencies, and CBDC: Financial Structural Transformation in China," Journal of International Money and Finance, Elsevier, vol. 124(C).
    16. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    17. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    18. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    19. Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
    20. Lee A. Smales, 2021. "Volatility Spillovers among Cryptocurrencies," JRFM, MDPI, vol. 14(10), pages 1-12, October.
    21. Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
    22. Hafner, Christian M. & Majeri , Sabrine, 2022. "Analysis of cryptocurrency connectedness based on network to transaction volume ratios," LIDAM Reprints ISBA 2022033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Igor Makarov & Antoinette Schoar, 2021. "Blockchain Analysis of the Bitcoin Market," NBER Working Papers 29396, National Bureau of Economic Research, Inc.
    24. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    25. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    26. Prakash, Navendu & Srivastava, Bhavya & Singh, Shveta & Sharma, Seema & Jain, Sonali, 2022. "Effectiveness of social distancing interventions in containing COVID-19 incidence: International evidence using Kalman filter," Economics & Human Biology, Elsevier, vol. 44(C).
    27. Pattnaik, Debidutta & Hassan, M. Kabir & Dsouza, Arun & Tiwari, Aviral & Devji, Shridev, 2023. "Ex-post facto analysis of cryptocurrency literature over a decade using bibliometric technique," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    28. Liebi, Luca J., 2022. "Is there a value premium in cryptoasset markets?," Economic Modelling, Elsevier, vol. 109(C).
    29. Hoang, Lai T. & Baur, Dirk G., 2022. "Loaded for bear: Bitcoin private wallets, exchange reserves and prices," Journal of Banking & Finance, Elsevier, vol. 144(C).
    30. Dirk G. Baur & Lee A. Smales, 2022. "Trading behavior in bitcoin futures: Following the “smart money”," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1304-1323, July.
    31. Zdravka Aljinoviæ & Tea Šestanoviæ & Blanka Škrabiæ Periæ, 2022. "A New Evidence of the Relationship between Cryptocurrencies and other Assets from the COVID-19 Crisis," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(7-8), pages 603-621, July.
    32. Chang, Shuhua & Li, Anqi & Wang, Xin & Wang, Xinyu, 2022. "Joint optimization of e-commerce supply chain financing strategy and channel contract," European Journal of Operational Research, Elsevier, vol. 303(2), pages 908-927.
    33. Hashem A. AlNemer & Besma Hkiri & Muhammed Asif Khan, 2021. "Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    34. Tripoli, Mischa & Schmidhuber, Josef, 2018. "Emerging Opportunities for the Application of Blockchain in the Agri-Food Industry," Post-Nairobi WTO Agenda 320187, International Centre for Trade and Sustainable Development (ICTSD).
    35. Yousaf, Imran & Yarovaya, Larisa, 2022. "Herding behavior in conventional cryptocurrency market, non-fungible tokens, and DeFi assets," Finance Research Letters, Elsevier, vol. 50(C).
    36. Charfeddine, Lanouar & Benlagha, Noureddine & Khediri, Karim Ben, 2022. "An intra-cryptocurrency analysis of volatility connectedness and its determinants: Evidence from mining coins, non-mining coins and tokens," Research in International Business and Finance, Elsevier, vol. 62(C).
    37. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
    38. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    39. Dai, Lei & Jing, Danyue & Hu, Hao & Wang, Zhaojing, 2021. "An environmental and techno-economic analysis of transporting LNG via Arctic route," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 56-71.
    40. Luciano Somoza & Antoine Didisheim, 2022. "The End of the Crypto-Diversification Myth," Swiss Finance Institute Research Paper Series 22-53, Swiss Finance Institute.
    41. Saifur Rahman Chowdhury & Tachlima Chowdhury Sunna & Shakil Ahmed, 2021. "Telemedicine is an important aspect of healthcare services amid COVID‐19 outbreak: Its barriers in Bangladesh and strategies to overcome," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(1), pages 4-12, January.
    42. Danial Saef & Yuanrong Wang & Tomaso Aste, 2022. "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing," Papers 2208.12614, arXiv.org, revised Sep 2022.
    43. Gerritsen, Dirk F. & Lugtigheid, Rick A.C. & Walther, Thomas, 2022. "Can Bitcoin Investors Profit from Predictions by Crypto Experts?," Finance Research Letters, Elsevier, vol. 46(PA).
    44. Ciner, Cetin & Lucey, Brian & Yarovaya, Larisa, 2022. "Determinants of cryptocurrency returns: A LASSO quantile regression approach," Finance Research Letters, Elsevier, vol. 49(C).
    45. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    46. Simon Mackenzie, 2022. "Criminology Towards the Metaverse: Cryptocurrency Scams, Grey Economy and the Technosocial," The British Journal of Criminology, Centre for Crime and Justice Studies, vol. 62(6), pages 1537-1552.

  37. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    9. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Nasekin, Sergey & Chen, Cathy Yi-Hsuan, 2018. "Deep learning-based cryptocurrency sentiment construction," IRTG 1792 Discussion Papers 2018-066, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    15. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    17. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  38. Petukhina, Alla & Trimborn, Simon & Härdle, Wolfgang Karl & Elendner, Hermann, 2018. "Investing with cryptocurrencies - evaluating the potential of portfolio allocation strategies," IRTG 1792 Discussion Papers 2018-058, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Tomić, Bojan, 2020. "BITCOIN: Systematic Force of Cryptocurrency Portfolio," MPRA Paper 101290, University Library of Munich, Germany, revised 26 May 2020.
    2. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    3. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    5. Nasekin, Sergey & Chen, Cathy Yi-Hsuan, 2018. "Deep learning-based cryptocurrency sentiment construction," IRTG 1792 Discussion Papers 2018-066, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Ma, Yechi & Ahmad, Ferhana & Liu, Miao & Wang, Zilong, 2020. "Portfolio optimization in the era of digital financialization using cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    7. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    8. Nils Bundi & Marc Wildi, 2019. "Bitcoin and market-(in)efficiency: a systematic time series approach," Digital Finance, Springer, vol. 1(1), pages 47-65, November.

  39. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  40. Härdle, Wolfgang Karl & Chen, Shi & Liang, Chong & Schienle, Melanie, 2018. "Time-varying Limit Order Book Networks," IRTG 1792 Discussion Papers 2018-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Kara Karpman & Sumanta Basu & David Easley, 2022. "Learning Financial Networks with High-frequency Trade Data," Papers 2208.03568, arXiv.org.
    14. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    17. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  41. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Hou, Ai Jun & Wang, Weining, 2018. "Pricing Cryptocurrency options: the case of CRIX and Bitcoin," IRTG 1792 Discussion Papers 2018-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    Cited by:

    1. Dilip B. Madan & Sofie Reyners & Wim Schoutens, 2019. "Advanced model calibration on bitcoin options," Digital Finance, Springer, vol. 1(1), pages 117-137, November.
    2. Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
    3. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
    4. Härdle, Wolfgang Karl & Harvey, Campbell R. & Reule, Raphael C. G., 2018. "Understanding Cryptocurrencies," IRTG 1792 Discussion Papers 2018-044, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Alessandra Cretarola & Gianna Figà-Talamanca, 2021. "Detecting bubbles in Bitcoin price dynamics via market exuberance," Annals of Operations Research, Springer, vol. 299(1), pages 459-479, April.
    6. da Gama Silva, Paulo Vitor Jordão & Klotzle, Marcelo Cabus & Pinto, Antonio Carlos Figueiredo & Gomes, Leonardo Lima, 2019. "Herding behavior and contagion in the cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 41-50.
    7. Chen, Cathy Yi-Hsuan & Després, Roméo & Guo, Li & Renault, Thomas, 2019. "What makes cryptocurrencies special? Investor sentiment and return predictability during the bubble," IRTG 1792 Discussion Papers 2019-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
    9. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018. "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers 2018-056, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Fabian Woebbeking, 2021. "Cryptocurrency volatility markets," Digital Finance, Springer, vol. 3(3), pages 273-298, December.

  42. Yi-Hsuan Chen, Cathy & Fengler, Matthias & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," Economics Working Paper Series 1808, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Joshua Zoen Git Hiew & Xin Huang & Hao Mou & Duan Li & Qi Wu & Yabo Xu, 2019. "BERT-based Financial Sentiment Index and LSTM-based Stock Return Predictability," Papers 1906.09024, arXiv.org, revised Jul 2022.
    2. Zhong, Wei & Liu, Xi & Ma, Shuangge, 2018. "Variable selection and direction estimation for single-index models via DC-TGDR method," IRTG 1792 Discussion Papers 2018-050, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Kuczmaszewska, Anna & Yan, Ji Gao, 2018. "On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables," IRTG 1792 Discussion Papers 2018-041, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Yatracos, Yannis G., 2018. "Residual'S Influence Index (Rinfin), Bad Leverage And Unmasking In High Dimensional L2-Regression," IRTG 1792 Discussion Papers 2018-060, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Zbonakova, Lenka & Li, Xinjue & Härdle, Wolfgang Karl, 2018. "Penalized Adaptive Forecasting with Large Information Sets and Structural Changes," IRTG 1792 Discussion Papers 2018-039, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Packham, Natalie, 2018. "Optimal contracts under competition when uncertainty from adverse selection and moral hazard are present," IRTG 1792 Discussion Papers 2018-033, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Wang, Honglin & Yu, Fan & Zhou, Yinggang, 2018. "Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach," IRTG 1792 Discussion Papers 2018-051, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    9. Chiu, Hsin-Yu & Chiang, Mi-Hsiu & Kuo, Wei-Yu, 2018. "Predicative Ability of Similarity-based Futures Trading Strategies," IRTG 1792 Discussion Papers 2018-045, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Guo, Shaojun & Li, Dong & Li, Muyi, 2018. "Strict Stationarity Testing and GLAD Estimation of Double Autoregressive Models," IRTG 1792 Discussion Papers 2018-049, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    11. Koziuk, Andzhey & Spokoiny, Vladimir, 2018. "Toolbox: Gaussian comparison on Eucledian balls," IRTG 1792 Discussion Papers 2018-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Nasekin, Sergey & Chen, Cathy Yi-Hsuan, 2018. "Deep learning-based cryptocurrency sentiment construction," IRTG 1792 Discussion Papers 2018-066, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Fan, Qingliang & Zhong, Wei, 2018. "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective," IRTG 1792 Discussion Papers 2018-052, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Guo, Li & Tao, Yubo & Härdle, Wolfgang Karl, 2018. "Understanding Latent Group Structure of Cryptocurrencies Market: A Dynamic Network Perspective," IRTG 1792 Discussion Papers 2018-032, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Packham, Natalie & Woebbeking, Fabian, 2018. "A factor-model approach for correlation scenarios and correlation stress-testing," IRTG 1792 Discussion Papers 2018-034, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    16. Xiaojia Bao & Qingliang Fan, 2020. "The impact of temperature on gaming productivity: evidence from online games," Empirical Economics, Springer, vol. 58(2), pages 835-867, February.
    17. Packham, Natalie & Kalkbrener, Michael & Overbeck, Ludger, 2018. "Default probabilities and default correlations under stress," IRTG 1792 Discussion Papers 2018-037, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    19. Cai, Zongwu & Fang, Ying & Lin, Ming & Su, Jia, 2018. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," IRTG 1792 Discussion Papers 2018-047, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    20. Kalkbrener, Michael & Packham, Natalie, 2018. "Correlation Under Stress In Normal Variance Mixture Models," IRTG 1792 Discussion Papers 2018-035, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  43. Lining Yu & Wolfgang Karl Härdle & Lukas Borke & Thijs Benschop, 2017. "FRM: a Financial Risk Meter based on penalizing tail events occurrence," SFB 649 Discussion Papers SFB649DP2017-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Zbonakova, Lenka & Pio Monti, Ricardo & Härdle, Wolfgang Karl, 2018. "Towards the interpretation of time-varying regularization parameters in streaming penalized regression models," IRTG 1792 Discussion Papers 2018-059, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Lukas Borke, 2017. "RiskAnalytics: an R package for real time processing of Nasdaq and Yahoo finance data and parallelized quantile lasso regression methods," SFB 649 Discussion Papers SFB649DP2017-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Mihoci, Andrija & Althof, Michael & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2019. "FRM Financial Risk Meter," IRTG 1792 Discussion Papers 2019-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  44. Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Data Science & Digital Society," SFB 649 Discussion Papers SFB649DP2017-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Bianca Haas & Marcus Haward & Jeffrey McGee & Aysha Fleming, 0. "Explicit targets and cooperation: regional fisheries management organizations and the sustainable development goals," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 0, pages 1-13.

  45. Simon Trimborn & Mingyang Li & Wolfgang Karl Härdle, 2017. "Investing with cryptocurrencies - A liquidity constrained investment approach," SFB 649 Discussion Papers SFB649DP2017-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Romi Kher & Siri Terjesen & Chen Liu, 2021. "Blockchain, Bitcoin, and ICOs: a review and research agenda," Small Business Economics, Springer, vol. 56(4), pages 1699-1720, April.
    2. Alla Petukhina & Erin Sprünken, 2021. "Evaluation of multi-asset investment strategies with digital assets," Digital Finance, Springer, vol. 3(1), pages 45-79, March.
    3. Wei Zhang & Yi Li, 2023. "Liquidity risk and expected cryptocurrency returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 472-492, January.
    4. Christoph J. Borner & Ingo Hoffmann & Jonas Krettek & Lars M. Kurzinger & Tim Schmitz, 2021. "Bitcoin: Like a Satellite or Always Hardcore? A Core-Satellite Identification in the Cryptocurrency Market," Papers 2105.12336, arXiv.org.
    5. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Pascal Bruhn & Dietmar Ernst, 2022. "Assessing the Risk Characteristics of the Cryptocurrency Market: A GARCH-EVT-Copula Approach," JRFM, MDPI, vol. 15(8), pages 1-28, August.
    7. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    8. Moreno, David & Antoli, Marcos & Quintana, David, 2022. "Benefits of investing in cryptocurrencies when liquidity is a factor," Research in International Business and Finance, Elsevier, vol. 63(C).
    9. Chunling Li & Nosherwan Khaliq & Leslie Chinove & Usama Khaliq & József Popp & Judit Oláh, 2023. "Cryptocurrency Acceptance Model to Analyze Consumers’ Usage Intention: Evidence From Pakistan," SAGE Open, , vol. 13(1), pages 21582440231, March.
    10. Paweł Sakowski & Anna Turovtseva, 2020. "Verification of Investment Opportunities on the Cryptocurrency Market within the Markowitz Framework," Working Papers 2020-41, Faculty of Economic Sciences, University of Warsaw.
    11. Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
    12. Ćosić Karlo & Časni Anita Čeh, 2019. "The impact of cryptocurrency on the efficient frontier of emerging markets," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(2), pages 64-75, December.
    13. da Gama Silva, Paulo Vitor Jordão & Klotzle, Marcelo Cabus & Pinto, Antonio Carlos Figueiredo & Gomes, Leonardo Lima, 2019. "Herding behavior and contagion in the cryptocurrency market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 41-50.
    14. Christoph J. Börner & Ingo Hoffmann & Jonas Krettek & Tim Schmitz, 2022. "Bitcoin: like a satellite or always hardcore? A core–satellite identification in the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 310-321, July.
    15. Hafner, Christian M. & Majeri , Sabrine, 2022. "Analysis of cryptocurrency connectedness based on network to transaction volume ratios," LIDAM Reprints ISBA 2022033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Christoph J. Borner & Ingo Hoffmann & Jonas Krettek & Lars M. Kurzinger & Tim Schmitz, 2021. "On the Return Distributions of a Basket of Cryptocurrencies and Subsequent Implications," Papers 2105.12334, arXiv.org.
    17. Petukhina, Alla & Trimborn, Simon & Härdle, Wolfgang Karl & Elendner, Hermann, 2018. "Investing with cryptocurrencies - evaluating the potential of portfolio allocation strategies," IRTG 1792 Discussion Papers 2018-058, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Ma, Yechi & Ahmad, Ferhana & Liu, Miao & Wang, Zilong, 2020. "Portfolio optimization in the era of digital financialization using cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    19. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    20. Paul P Momtaz, 2020. "Initial Coin Offerings," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-30, May.

  46. Wolfgang Karl Härdle & Lukas Borke, 2017. "GitHub API based QuantNet Mining infrastructure in R," SFB 649 Discussion Papers SFB649DP2017-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Lux, Marius & Härdle, Wolfgang Karl & Lessmann, Stefan, 2018. "Data Driven Value-at-Risk Forecasting using a SVR-GARCH-KDE Hybrid," IRTG 1792 Discussion Papers 2018-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Lining Yu & Wolfgang Karl Hardle & Lukas Borke & Thijs Benschop, 2020. "An AI approach to measuring financial risk," Papers 2009.13222, arXiv.org.
    4. Yingxing Li & Chen Huang & Wolfgang Karl Härdle, 2017. "Spatial Functional Principal Component Analysis with Applications to Brain Image Data," SFB 649 Discussion Papers SFB649DP2017-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Zharova, Alona & Härdle, Wolfgang Karl & Lessmann, Stefan, 2023. "Data-driven support for policy and decision-making in university research management: A case study from Germany," European Journal of Operational Research, Elsevier, vol. 308(1), pages 353-368.
    6. Adamyan, Larisa & Efimov, Kirill & Spokoiny, Vladimir, 2019. "Adaptive Nonparametric Community Detection," IRTG 1792 Discussion Papers 2019-006, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  47. Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Yaya Su & Zhehao Huang & Benjamin M. Drakeford, 2019. "Monetary Policy, Industry Heterogeneity and Systemic Risk—Based on a High Dimensional Network Analysis," Sustainability, MDPI, vol. 11(22), pages 1-15, November.

  48. CMaria Osipenko & Wolfgang Karl Härdle, 2017. "Dynamic Valuation of Weather Derivatives under Default Risk," SFB 649 Discussion Papers SFB649DP2017-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.

  49. Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & Yarema Okhrin, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers SFB649DP2017-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.

  50. Yingxing Li & Chen Huang & Wolfgang Karl Härdle, 2017. "Spatial Functional Principal Component Analysis with Applications to Brain Image Data," SFB 649 Discussion Papers SFB649DP2017-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Colin Lewis-Beck & Zhengyuan Zhu & Victoria Walker & Brian Hornbuckle, 2020. "Modeling Crop Phenology in the US Corn Belt Using Spatially Referenced SMOS Satellite Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 657-675, December.
    2. Tomasz Górecki & Lajos Horváth & Piotr Kokoszka, 2020. "Tests of Normality of Functional Data," International Statistical Review, International Statistical Institute, vol. 88(3), pages 677-697, December.
    3. Park, Yeonjoo & Kim, Hyunsung & Lim, Yaeji, 2023. "Functional principal component analysis for partially observed elliptical process," Computational Statistics & Data Analysis, Elsevier, vol. 184(C).
    4. Giraldo, Ramón & Dabo-Niang, Sophie & Martínez, Sergio, 2018. "Statistical modeling of spatial big data: An approach from a functional data analysis perspective," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 126-129.
    5. Dennis Schroers, 2024. "Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions," Papers 2401.16286, arXiv.org.
    6. Haozhe Zhang & Yehua Li, 2020. "Unified Principal Component Analysis for Sparse and Dense Functional Data under Spatial Dependency," Papers 2006.13489, arXiv.org, revised Jun 2021.

  51. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.

  52. Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2016. "Factorisable Multi-Task Quantile Regression," SFB 649 Discussion Papers SFB649DP2016-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wang, Weining & Wooldridge, Jeffrey M. & Xu, Mengshan, 2020. "Improved Estimation of Dynamic Models of Conditional Means and Variances," IRTG 1792 Discussion Papers 2020-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Perkiss, Stephanie & Bernardi, Cristiana & Dumay, John & Haslam, Jim, 2021. "A sticky chocolate problem: Impression management and counter accounts in the shaping of corporate image," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 81(C).
    4. Cuicui Lu & Weining Wang & Jeffrey M. Wooldridge, 2018. "Using generalized estimating equations to estimate nonlinear models with spatial data," Papers 1810.05855, arXiv.org.
    5. Meng, Lina & Zhou, Yinggang & Zhang, Ruige & Ye, Zhen & Xia, Senmao & Cerulli, Giovanni & Casady, Carter & Härdle, Wolfgang Karl, 2020. "The Effect of Control Measures on COVID-19 Transmission and Work Resumption: International Evidence," IRTG 1792 Discussion Papers 2020-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Smith, Lisa C. & Frankenberger, Timothy R., 2022. "Recovering from severe drought in the drylands of Ethiopia: Impact of Comprehensive Resilience Programming," World Development, Elsevier, vol. 156(C).
    7. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.

  53. Xuening Zhu & Wolfgang K. Härdle & Weining Wang & Hangsheng Wang, 2016. "Network Quantile Autoregression," SFB 649 Discussion Papers SFB649DP2016-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
    3. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).
    4. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    5. Xiao, Xuan & Xu, Xingbai & Zhong, Wei, 2023. "Huber estimation for the network autoregressive model," Statistics & Probability Letters, Elsevier, vol. 203(C).
    6. Yiming Tang & Yang Bai & Tao Huang, 2021. "Network vector autoregression with individual effects," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(6), pages 875-893, August.
    7. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    8. Guo, Hongfeng & Zhao, Xinyao & Yu, Hang & Zhang, Xin, 2021. "Analysis of global stock markets’ connections with emphasis on the impact of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    9. Guo, Hongfeng & Xia, Shengxiang & An, Qiguang & Zhang, Xin & Sun, Weihua & Zhao, Xinyao, 2020. "Empirical study of financial crises based on topological data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    10. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    11. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Chen, Yu & Gao, Yu & Shu, Lei & Zhu, Xiaonan, 2023. "Network effects on risk co-movements: A network quantile autoregression-based analysis," Finance Research Letters, Elsevier, vol. 56(C).
    13. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," Economic Modelling, Elsevier, vol. 109(C).
    14. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    15. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Dec 2023.
    16. Jiang, Wen & Xu, Qiuhua & Zhang, Ruige, 2022. "Tail-event driven network of cryptocurrencies and conventional assets," Finance Research Letters, Elsevier, vol. 46(PB).
    17. Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & Yarema Okhrin, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers SFB649DP2017-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Feng, Yusen & Wang, Gang-Jin & Zhu, You & Xie, Chi, 2023. "Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries," Emerging Markets Review, Elsevier, vol. 55(C).
    20. Mihoci, Andrija & Althof, Michael & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2019. "FRM Financial Risk Meter," IRTG 1792 Discussion Papers 2019-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    21. Hu, Junjie & Härdle, Wolfgang, 2021. "Networks of news and cross-sectional returns," IRTG 1792 Discussion Papers 2021-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    22. Chen, Elynn Y. & Fan, Jianqing & Zhu, Xuening, 2023. "Community network auto-regression for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1239-1256.
    23. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

  54. Wolfgang Karl Härdle & Sergey Nasekin & Zhiwu Hong, 2016. "Leveraged ETF options implied volatility paradox: a statistical study," SFB 649 Discussion Papers SFB649DP2016-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Hongkai Cao & Rupak Chatterjee & Zhenyu Cui, 2019. "Options valuation and calibration for leveraged exchange-traded funds with Heston–Nandi and inverse Gaussian GARCH models," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 1-37, September.

  55. Simon Trimborn & Wolfgang Karl Härdle, 2016. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers SFB649DP2016-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Simon Trimborn & Mingyang Li & Wolfgang Karl Härdle, 2020. "Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 280-306.
    2. Schilling, Linda & Uhlig, Harald, 2019. "Some simple bitcoin economics," Journal of Monetary Economics, Elsevier, vol. 106(C), pages 16-26.
    3. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "A first econometric analysis of the CRIX family," Papers 2009.12129, arXiv.org.
    5. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    6. Stefan Cristian, 2018. "Tales from the crypt: might cryptocurrencies spell the death of traditional money? - A quantitative analysis -," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 12(1), pages 918-930, May.
    7. Hermann Elendner & Simon Trimborn & Bobby Ong & Teik Ming Lee, 2016. "The Cross-Section of Crypto-Currencies as Financial Assets: An Overview," SFB 649 Discussion Papers SFB649DP2016-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    9. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Hou, Ai Jun & Wang, Weining, 2018. "Pricing Cryptocurrency options: the case of CRIX and Bitcoin," IRTG 1792 Discussion Papers 2018-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating Cryptocurrency Prices Using Machine Learning," Complexity, Hindawi, vol. 2018, pages 1-16, November.
    11. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & TM Lee & Bobby Ong, 2016. "A first econometric analysis of the CRIX family," SFB 649 Discussion Papers SFB649DP2016-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Nadler, Philip & Guo, Yike, 2020. "The fair value of a token: How do markets price cryptocurrencies?," Research in International Business and Finance, Elsevier, vol. 52(C).

  56. Shi Chen & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & TM Lee & Bobby Ong, 2016. "A first econometric analysis of the CRIX family," SFB 649 Discussion Papers SFB649DP2016-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Pavel Ciaian & d'Artis Kancs & Miroslava Rajcaniova, 2018. "The Price of BitCoin: GARCH Evidence from High Frequency Data," EERI Research Paper Series EERI RP 2018/14, Economics and Econometrics Research Institute (EERI), Brussels.
    2. Gergana Taneva, 2019. "An analysis and a forecast of the cryptomarket based on the ARIMA model," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 66-84.
    3. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    4. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    5. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
    6. Rehman, Mobeen Ur & Apergis, Nicholas, 2019. "Determining the predictive power between cryptocurrencies and real time commodity futures: Evidence from quantile causality tests," Resources Policy, Elsevier, vol. 61(C), pages 603-616.
    7. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  57. Xiu Xu & Wolfgang K. Härdle & Cathy Yi-Hsuan Chen, 2016. "Dynamic credit default swaps curves in a network topology," SFB 649 Discussion Papers SFB649DP2016-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Bingkai Wang & Xi Luo & Yi Zhao & Brian Caffo, 2021. "Semiparametric partial common principal component analysis for covariance matrices," Biometrics, The International Biometric Society, vol. 77(4), pages 1175-1186, December.
    2. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    3. Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).

  58. Marco Linton & Wolfgang K. Härdle & Ernie Gin Swee Teo & Elisabeth Bommes & Cathy Yi-Hsuan Chen, 2016. "Dynamic Topic Modelling for Cryptocurrency Community Forums," SFB 649 Discussion Papers SFB649DP2016-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Young Bin Kim & Jurim Lee & Nuri Park & Jaegul Choo & Jong-Hyun Kim & Chang Hun Kim, 2017. "When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    2. Ni, Xinwen & Härdle, Wolfgang Karl & Xie, Taojun, 2020. "A Machine Learning Based Regulatory Risk Index for Cryptocurrencies," IRTG 1792 Discussion Papers 2020-013, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  59. Denis Belomestny & Shujie Ma & Wolfgang Karl Härdle, 2015. "Pricing Kernel Modeling," SFB 649 Discussion Papers SFB649DP2015-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Bünning, Felix & Sangi, Roozbeh & Müller, Dirk, 2017. "A Modelica library for the agent-based control of building energy systems," Applied Energy, Elsevier, vol. 193(C), pages 52-59.

  60. Lei Fang & Wolfgang K. Härdle, 2015. "Stochastic Population Analysis: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2015-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Han Lin Shang & Rob J Hyndman, 2016. "Grouped functional time series forecasting: An application to age-specific mortality rates," Monash Econometrics and Business Statistics Working Papers 4/16, Monash University, Department of Econometrics and Business Statistics.
    2. Lei Fang & Wolfgang K. Härdle & Juhyun Park, 2016. "A Mortality Model for Multi-populations A Semi-Parametric Approach," SFB 649 Discussion Papers SFB649DP2016-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  61. Ying Chen & Wolfgang K. Härdle & Qiang He & Piotr Majer, 2015. "Risk Related Brain Regions Detected with 3D Image FPCA," SFB 649 Discussion Papers SFB649DP2015-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Li, Yingxing & Huang, Chen & Härdle, Wolfgang K., 2019. "Spatial functional principal component analysis with applications to brain image data," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 263-274.

  62. Junni L. Zhang & Wolfgang K. Härdle & Cathy Y. Chen & Elisabeth Bommes, 2015. "Distillation of News Flow into Analysis of Stock Reactions," SFB 649 Discussion Papers SFB649DP2015-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Dautel, Alexander J. & Härdle, Wolfgang Karl & Lessmann, Stefan & Seow, Hsin-Vonn, 2019. "Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks," IRTG 1792 Discussion Papers 2019-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  63. P. Burdejova & W.K. Härdle & Kokoszka & Q.Xiong, 2015. "Change point and trend analyses of annual expectile curves of tropical storms," SFB 649 Discussion Papers SFB649DP2015-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Kokoszka, Piotr & Oja, Hanny & Park, Byeong & Sangalli, Laura, 2017. "Special issue on functional data analysis," Econometrics and Statistics, Elsevier, vol. 1(C), pages 99-100.
    3. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.

  64. Wei Cui & Wolfgang K. Härdle & Weining Wang, 2015. "Estimation of NAIRU with Inflation Expectation Data," SFB 649 Discussion Papers SFB649DP2015-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Arnoud Stevens & Joris Wauters, 2021. "Is euro area lowflation here to stay? Insights from a time‐varying parameter model with survey data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 566-586, August.
    2. Dana Kloudová, 2016. "Does Using Nairu In The Production Function Influence Estimation Of Potential Output And Output Gap?," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 5(2), pages 1-21, June.
    3. Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2018. "Inflation, real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4540-4555, September.

  65. Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2015. "Factorisable Sparse Tail Event Curves," SFB 649 Discussion Papers SFB649DP2015-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Wolfgang K. Härdle & Chen Huang & Shih-Kang Chao, 2016. "Calculating Joint Confidence Bands for Impulse Response Functions using Highest Density Regions," SFB 649 Discussion Papers SFB649DP2016-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  66. Philipp Gschöpf & Wolfgang Karl Härdle & Andrija Mihoci, 2015. "TERES - Tail Event Risk Expectile based Shortfall," SFB 649 Discussion Papers SFB649DP2015-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
    2. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.

  67. Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Karl Härdle, 2014. "Portfolio Decisions and Brain Reactions via the CEAD method," SFB 649 Discussion Papers SFB649DP2014-036, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Ying Chen & Wolfgang K. Härdle & Qiang He & Piotr Majer, 2015. "Risk Related Brain Regions Detected with 3D Image FPCA," SFB 649 Discussion Papers SFB649DP2015-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    5. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
    6. Morawetz, Carmen & Mohr, Peter N. C. & Heekeren, Hauke R. & Bode, Stefan, 2019. "The effect of emotion regulation on risk-taking and decision-related activity in prefrontal cortex," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14(10), pages 1109-1118.

  68. Stephan Stahlschmidt & Matthias Eckardt & Wolfgang K. Härdle, 2014. "Expectile Treatment Effects: An efficient alternative to compute the distribution of treatment effects," SFB 649 Discussion Papers SFB649DP2014-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Farooq, Muhammad & Steinwart, Ingo, 2017. "An SVM-like approach for expectile regression," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 159-181.

  69. Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & Hien Pham-Thu, 2014. "The integration of credit default swap markets in the pre and post-subprime crisis in common stochastic trends," SFB 649 Discussion Papers SFB649DP2014-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Atil, Ahmed & Bradford, Marc & Elmarzougui, Abdelaziz & Lahiani, Amine, 2016. "Conditional dependence of US and EU sovereign CDS: A time-varying copula-based estimation," Finance Research Letters, Elsevier, vol. 19(C), pages 42-53.

  70. Lijie Gu & Li Wang & Wolfgang Karl Härdle & Lijian Yang, 2014. "A Simultaneous Confidence Corridor for Varying Coefficient Regression with Sparse Functional Data," SFB 649 Discussion Papers SFB649DP2014-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Cao, Guanqun & Wang, Li, 2018. "Simultaneous inference for the mean of repeated functional data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 279-295.
    2. Li Cai & Lisha Li & Simin Huang & Liang Ma & Lijian Yang, 2020. "Oracally efficient estimation for dense functional data with holiday effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 282-306, March.
    3. Italo R. Lima & Guanqun Cao & Nedret Billor, 2019. "M-based simultaneous inference for the mean function of functional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 577-598, June.
    4. Gu, Lijie & Wang, Suojin & Yang, Lijian, 2021. "Smooth simultaneous confidence band for the error distribution function in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    5. Li Cai & Lijie Gu & Qihua Wang & Suojin Wang, 2021. "Simultaneous confidence bands for nonparametric regression with missing covariate data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1249-1279, December.
    6. Yuanyuan Zhang & Lijian Yang, 2018. "A smooth simultaneous confidence band for correlation curve," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 247-269, June.
    7. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.
    8. Jie Li & Jiangyan Wang & Lijian Yang, 2022. "Kolmogorov–Smirnov simultaneous confidence bands for time series distribution function," Computational Statistics, Springer, vol. 37(3), pages 1015-1039, July.
    9. Wang, Jiangyan & Gu, Lijie & Yang, Lijian, 2022. "Oracle-efficient estimation for functional data error distribution with simultaneous confidence band," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    10. Kun Huang & Sijie Zheng & Lijian Yang, 2022. "Inference for dependent error functional data with application to event-related potentials," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1100-1120, December.
    11. Li, Yehua & Qiu, Yumou & Xu, Yuhang, 2022. "From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    12. Jiangyan Wang & Suojin Wang & Lijian Yang, 2016. "Simultaneous confidence bands for the distribution function of a finite population and of its superpopulation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 692-709, December.
    13. Chen Zhong & Lijian Yang, 2021. "Simultaneous confidence bands for comparing variance functions of two samples based on deterministic designs," Computational Statistics, Springer, vol. 36(2), pages 1197-1218, June.
    14. Lijie Gu & Suojin Wang & Lijian Yang, 2019. "Simultaneous confidence bands for the distribution function of a finite population in stratified sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 983-1005, August.
    15. Yueying Wang & Guannan Wang & Li Wang & R. Todd Ogden, 2020. "Simultaneous confidence corridors for mean functions in functional data analysis of imaging data," Biometrics, The International Biometric Society, vol. 76(2), pages 427-437, June.

  71. Ngoc Mai Tran & Maria Osipenko & Wolfgang Karl Härdle, 2014. "Principal Component Analysis in an Asymmetric Norm," SFB 649 Discussion Papers SFB649DP2014-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Brenda Lopez Cabrera & Franziska Schulz, 2014. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2014-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    4. Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & Yarema Okhrin, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers SFB649DP2017-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  72. Shiyi Chen & Dengke Chen & Wolfgang K. Härdle, 2014. "The Influence of Oil Price Shocks on China’s Macroeconomy : A Perspective of International Trade," SFB 649 Discussion Papers SFB649DP2014-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Muhammad Ahad & Zaheer Anwer, 2021. "Asymmetric impact of oil price on trade balance in BRICS countries: Multiplier dynamic analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2177-2197, April.
    2. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Bachmeier, Lance, 2019. "Modelling systemic risk and dependence structure between the prices of crude oil and exchange rates in BRICS economies: Evidence using quantile coherency and NGCoVaR approaches," Energy Economics, Elsevier, vol. 81(C), pages 1011-1028.

  73. Wolfgang Karl Härdle & Sergey Nasekin & David Lee Kuo Chuen & Phoon Kok Fai, 2014. "TEDAS - Tail Event Driven ASset Allocation," SFB 649 Discussion Papers SFB649DP2014-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2015. "Asset Allocation Strategies Based On Penalized Quantile Regression," "Marco Fanno" Working Papers 0199, Dipartimento di Scienze Economiche "Marco Fanno".
    2. Wolfgang Karl Härdle & David Kuo Chuen Lee & Sergey Nasekin & Alla Petukhina, 2018. "Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(1), pages 49-63, January.
    3. Cathy Yi-Hsuan Chen & Thomas C. Chiang & Wolfgang Karl Härdle, 2016. "Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries," SFB 649 Discussion Papers SFB649DP2016-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  74. Wolfgang Karl Härdle & Natalia Sirotko-Sibirskaya & Weining Wang, 2014. "TENET: Tail-Event driven NETwork risk," SFB 649 Discussion Papers SFB649DP2014-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Somnath Chatterjee & Marea Sing, 2021. "Measuring Systemic Risk in South African Banks," Working Papers 11004, South African Reserve Bank.
    2. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    3. Wang, Bo & Xiao, Yang, 2023. "Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    4. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Verma, Ramprasad & Ahmad, Wasim & Uddin, Gazi Salah & Bekiros, Stelios, 2019. "Analysing the systemic risk of Indian banks," Economics Letters, Elsevier, vol. 176(C), pages 103-108.
    6. Wen, Shigang & Li, Jianping & Huang, Chuangxia & Zhu, Xiaoqian, 2023. "Extreme risk spillovers among traditional financial and FinTech institutions: A complex network perspective," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 190-202.
    7. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    8. Arreola Hernandez, Jose & Kang, Sang Hoon & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2020. "Spillovers and diversification potential of bank equity returns from developed and emerging America," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    9. Dai, Zhifeng & Zhu, Haoyang, 2023. "Dynamic risk spillover among crude oil, economic policy uncertainty and Chinese financial sectors," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 421-450.
    10. Naifar, Nader & Shahzad, Syed Jawad Hussain, 2022. "Tail event-based sovereign credit risk transmission network during COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    11. Fang, Libing & Sun, Boyang & Li, Huijing & Yu, Honghai, 2018. "Systemic risk network of Chinese financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 190-206.
    12. Darko Vukovic & Moinak Maiti & Zoran Grubisic & Elena M. Grigorieva & Michael Frömmel, 2021. "COVID-19 Pandemic: Is the Crypto Market a Safe Haven? The Impact of the First Wave," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    13. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
    14. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    15. Wang, Gang-Jin & Xiong, Lu & Zhu, You & Xie, Chi & Foglia, Matteo, 2022. "Multilayer network analysis of investor sentiment and stock returns," Research in International Business and Finance, Elsevier, vol. 62(C).
    16. Lenka Zbonakova & Wolfgang Karl Härdle & Weining Wang, 2016. "Time Varying Quantile Lasso," SFB 649 Discussion Papers SFB649DP2016-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Martin Waltz & Abhay Kumar Singh & Ostap Okhrin, 2022. "Vulnerability-CoVaR: Investigating the Crypto-market," Papers 2203.10777, arXiv.org.
    18. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2020. "Tail Risk Measurement In Crypto-Asset Markets," DEM Working Papers Series 186, University of Pavia, Department of Economics and Management.
    19. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
    20. Le, Chau & Dickinson, David & Le, Anh, 2022. "Sovereign risk spillovers: A network approach," Journal of Financial Stability, Elsevier, vol. 60(C).
    21. Deng, Yang & Zhang, Ziqing & Zhu, Li, 2021. "A model-based index for systemic risk contribution measurement in financial networks," Economic Modelling, Elsevier, vol. 95(C), pages 35-48.
    22. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    23. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    24. Huynh, Toan Luu Duc & Foglia, Matteo & Doukas, John A., 2022. "COVID-19 and Tail-event Driven Network Risk in the Eurozone," Finance Research Letters, Elsevier, vol. 44(C).
    25. Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    26. Kalpakam G & Krina TRIVEDI, 2021. "Systemic Risk in Indian Banking: Measurement and Impact of COVID-19," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 143-151.
    27. Georg Keilbar & Weining Wang, 2022. "Modelling systemic risk using neural network quantile regression," Empirical Economics, Springer, vol. 62(1), pages 93-118, January.
    28. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    29. Lyubov Y. Matich, 2017. "Roadmaps as a Tool for Modeling Complex Systems," HSE Working papers WP BRP 73/STI/2017, National Research University Higher School of Economics.
    30. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    31. Chen, Wei & Hou, Xiaoli & Jiang, Manrui & Jiang, Cheng, 2022. "Identifying systemically important financial institutions in complex network: A case study of Chinese stock market," Emerging Markets Review, Elsevier, vol. 50(C).
    32. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    33. Daniel Traian PELE & Alexandra Ioana CONDA & Raul Cristian BAG & Miruna MAZURENCU-MARINESCU-PELE & Vasile Alecsandru STRAT, 2023. "Financial Risk Meter for The Romanian Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-24, March.
    34. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2022. "Asymmetric Network Connectedness of Fears," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1304-1316, November.
    35. Ren, Rui & Althof, Michael & Härdle, Wolfgang Karl, 2020. "Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis," IRTG 1792 Discussion Papers 2020-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    36. Ren, Yinghua & Tan, Anqi & Zhu, Huiming & Zhao, Wanru, 2022. "Does economic policy uncertainty drive nonlinear risk spillover in the commodity futures market?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    37. Li, Xinjue & Zboňáková, Lenka & Wang, Weining & Härdle, Wolfgang Karl, 2019. "Combining Penalization and Adaption in High Dimension with Application in Bond Risk Premia Forecasting," IRTG 1792 Discussion Papers 2019-030, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    38. Naeem, Muhammad Abubakr & Karim, Sitara & Tiwari, Aviral Kumar, 2022. "Quantifying systemic risk in US industries using neural network quantile regression," Research in International Business and Finance, Elsevier, vol. 61(C).
    39. Beibei Zhang & Xuemei Xie & Chunmei Li, 2023. "How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    40. Chen, Muzi & Li, Nan & Zheng, Lifen & Huang, Difang & Wu, Boyao, 2022. "Dynamic correlation of market connectivity, risk spillover and abnormal volatility in stock price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    41. Hué, Sullivan & Lucotte, Yannick & Tokpavi, Sessi, 2019. "Measuring network systemic risk contributions: A leave-one-out approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 86-114.
    42. Yang, Xin & Wen, Shigang & Zhao, Xian & Huang, Chuangxia, 2020. "Systemic importance of financial institutions: A complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    43. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    44. Dai, Zhifeng & Tang, Rui & Zhang, Xiaotong, 2023. "A new multilayer network for measuring interconnectedness among the energy firms," Energy Economics, Elsevier, vol. 124(C).
    45. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    46. Cerqueti, Roy & Ciciretti, Rocco & Dalò, Ambrogio & Nicolosi, Marco, 2022. "A new measure of the resilience for networks of funds with applications to socially responsible investments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    47. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    48. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    49. Wang, Weining & Yu, Lining & Wang, Bingling, 2020. "Tail Event Driven Factor Augmented Dynamic Model," IRTG 1792 Discussion Papers 2020-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    50. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    51. Barigozzi, Matteo & Brownlees, Christian T., 2018. "Nets: network estimation for time series," LSE Research Online Documents on Economics 90493, London School of Economics and Political Science, LSE Library.
    52. Sullivan HUE & Yannick LUCOTTE & Sessi TOKPAVI, 2018. "Measuring Network Systemic Risk Contributions: A Leave-one-out Approach," LEO Working Papers / DR LEO 2608, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    53. Jiang, Cheng & Sun, Qian & Ye, Tanglin & Wang, Qingyun, 2023. "Identification of systemically important financial institutions in a multiplex financial network: A multi-attribute decision-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    54. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions," Research in International Business and Finance, Elsevier, vol. 65(C).
    55. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    56. Jian, Zhihong & Lu, Haisong & Zhu, Zhican & Xu, Huiling, 2023. "Frequency heterogeneity of tail connectedness: Evidence from global stock markets," Economic Modelling, Elsevier, vol. 125(C).
    57. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series 188, University of Pavia, Department of Economics and Management.
    58. Foglia, Matteo & Addi, Abdelhamid & Wang, Gang-Jin & Angelini, Eliana, 2022. "Bearish Vs Bullish risk network: A Eurozone financial system analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    59. Dai, Zhifeng & Tang, Rui & Zhang, Xinhua, 2023. "Multilayer network analysis for measuring the inter-connectedness between the oil market and G20 stock markets," Energy Economics, Elsevier, vol. 120(C).
    60. Hu, Yunchao & Lu, Guibin & Gao, Wenyu, 2022. "A study on China’s systemically important financial institutions based on multi-time scale causality networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    61. Dong, Xiyong & Yoon, Seong-Min, 2023. "Effect of weather and environmental attentions on financial system risks: Evidence from Chinese high- and low-carbon assets," Energy Economics, Elsevier, vol. 121(C).
    62. Nguyen, Linh Hoang & Lambe, Brendan John, 2021. "International tail risk connectedness: Network and determinants," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    63. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Vo, Xuan Vinh, 2023. "Oil tail risks and the realized variance of consumer prices in advanced economies," Resources Policy, Elsevier, vol. 83(C).
    64. Wu, Shihao & Li, Zhe & Zhu, Xuening, 2023. "A distributed community detection algorithm for large scale networks under stochastic block models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    65. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    66. Kara Karpman & Samriddha Lahiry & Diganta Mukherjee & Sumanta Basu, 2022. "Exploring Financial Networks Using Quantile Regression and Granger Causality," Papers 2207.10705, arXiv.org, revised Jul 2022.
    67. Song, Xiaoni & Fang, Tong, 2023. "Temperature shocks and bank systemic risk: Evidence from China," Finance Research Letters, Elsevier, vol. 51(C).
    68. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    69. Daniel Felix Ahelegbey, 2020. "Statistical Modelling of Downside Risk Spillovers," DEM Working Papers Series 193, University of Pavia, Department of Economics and Management.
    70. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    71. Gong, Xiao-Li & Feng, Yong-Kang & Liu, Jian-Min & Xiong, Xiong, 2023. "Study on international energy market and geopolitical risk contagion based on complex network," Resources Policy, Elsevier, vol. 82(C).
    72. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    73. Fenghua Wen & Kaiyan Weng & Wei-Xing Zhou, 2020. "Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach," Risk Management, Palgrave Macmillan, vol. 22(4), pages 310-337, December.
    74. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    75. Lining Yu & Wolfgang Karl Hardle & Lukas Borke & Thijs Benschop, 2020. "An AI approach to measuring financial risk," Papers 2009.13222, arXiv.org.
    76. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    77. Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018. "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers 2018-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    78. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    79. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).
    80. Erick Treviño Aguilar, 2020. "The interdependency structure in the Mexican stock exchange: A network approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-31, October.
    81. Wang, Ruting & Althof, Michael & Härdle, Wolfgang Karl, 2023. "A financial risk meter for China," Emerging Markets Review, Elsevier, vol. 56(C).
    82. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    83. Wang, Gang-Jin & Si, Hui-Bin & Chen, Yang-Yang & Xie, Chi & Chevallier, Julien, 2021. "Time domain and frequency domain Granger causality networks: Application to China’s financial institutions," Finance Research Letters, Elsevier, vol. 39(C).
    84. Habibi, Hamidreza & Mohammadi, Hassan, 2022. "Return and volatility spillovers across the Western and MENA countries," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    85. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    86. Xinjue Li & Lenka Zbonakova & Wolfgang Karl Härdle, 2017. "Penalized Adaptive Method in Forecasting with Large Information Set and Structure Change," SFB 649 Discussion Papers SFB649DP2017-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    87. Bernardi, M. & Durante, F. & Jaworski, P., 2017. "CoVaR of families of copulas," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 8-17.
    88. Victor Chernozhukov & Chen Huang & Weining Wang, 2021. "Uniform Inference on High-dimensional Spatial Panel Networks," Papers 2105.07424, arXiv.org, revised Sep 2023.
    89. Lining Yu & Wolfgang Karl Härdle & Lukas Borke & Thijs Benschop, 2017. "FRM: a Financial Risk Meter based on penalizing tail events occurrence," SFB 649 Discussion Papers SFB649DP2017-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    90. Chen, Na & Jin, Xiu, 2020. "Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    91. Yunhan Zhang & Qiang Ji & David Gabauer & Rangan Gupta, 2024. "How Connected is the Oil-Bank Network? Firm-Level and High-Frequency Evidence," Working Papers 202405, University of Pretoria, Department of Economics.
    92. Liu, Zhenhua & Shi, Xunpeng & Zhai, Pengxiang & Wu, Shan & Ding, Zhihua & Zhou, Yuqin, 2021. "Tail risk connectedness in the oil-stock nexus: Evidence from a novel quantile spillover approach," Resources Policy, Elsevier, vol. 74(C).
    93. Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    94. Wang, Ruting & Althof, Michael & Härdle, Wolfgang, 2021. "A financial risk meter for China," IRTG 1792 Discussion Papers 2021-022, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    95. Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.
    96. Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.
    97. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    98. Chen, Yan & Mo, Dongxu & Xu, Zezhou, 2022. "A study of interconnections and contagion among Chinese financial institutions using a ΔCoV aR network," Finance Research Letters, Elsevier, vol. 45(C).
    99. Zhu, Huiming & Li, Shuang & Huang, Zishan, 2023. "Frequency domain quantile dependence and connectedness between crude oil and exchange rates: Evidence from oil-importing and exporting countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 1-30.
    100. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Dec 2023.
    101. Jiang, Wen & Xu, Qiuhua & Zhang, Ruige, 2022. "Tail-event driven network of cryptocurrencies and conventional assets," Finance Research Letters, Elsevier, vol. 46(PB).
    102. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    103. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2019. "Tail event driven networks of SIFIs," Journal of Econometrics, Elsevier, vol. 208(1), pages 282-298.
    104. Zbonakova, L. & Härdle, W.K. & Wang, W., 2016. "Time Varying Quantile Lasso," Working Papers 16/07, Department of Economics, City University London.
    105. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
    106. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).
    107. Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter for emerging markets," Research in International Business and Finance, Elsevier, vol. 60(C).
    108. Zhang, Xingmin & Zhang, Shuai & Lu, Liping, 2022. "The banking instability and climate change: Evidence from China," Energy Economics, Elsevier, vol. 106(C).
    109. Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    110. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    111. Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle & Yarema Okhrin, 2017. "Tail event driven networks of SIFIs," SFB 649 Discussion Papers SFB649DP2017-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    112. Anna Denkowska & Stanisław Wanat, 2020. "A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector," Risks, MDPI, vol. 8(2), pages 1-22, April.
    113. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhai, Kaikai, 2021. "Multiscale and partial correlation networks analysis of risk connectedness in global equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    114. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "Systemic risk in financial networks: the effects of asymptotic independence," Papers 2309.15511, arXiv.org.
    115. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    116. Huang, Wei-Qiang & Wang, Dan, 2020. "Financial network linkages to predict economic output," Finance Research Letters, Elsevier, vol. 33(C).
    117. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhu, Huiming, 2022. "Multiscale features of extreme risk spillover networks among global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    118. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    119. Daniel Felix Ahelegbey & Paolo Giudici & Fatemeh Mojtahedi, 2022. "Crypto Asset Portfolio Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
    120. Shoukun Jiao & Wuyi Ye, 2022. "Dependence and Systemic Risk Analysis Between S&P 500 Index and Sector Indexes: A Conditional Value-at-Risk Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1203-1229, March.
    121. Feng, Yusen & Wang, Gang-Jin & Zhu, You & Xie, Chi, 2023. "Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries," Emerging Markets Review, Elsevier, vol. 55(C).
    122. Weihuan Huang, 2023. "Estimating Systemic Risk within Financial Networks: A Two-Step Nonparametric Method," Papers 2310.18658, arXiv.org.
    123. Liang, Qi & Lu, Yanchen & Li, Zheng, 2020. "Business connectedness or market risk? Evidence from financial institutions in China," China Economic Review, Elsevier, vol. 62(C).
    124. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    125. Wang, Dan & Huang, Wei-Qiang, 2021. "Centrality-based measures of financial institutions’ systemic importance: A tail dependence network view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    126. Papież, Monika & Rubaszek, Michał & Szafranek, Karol & Śmiech, Sławomir, 2022. "Are European natural gas markets connected? A time-varying spillovers analysis," Resources Policy, Elsevier, vol. 79(C).
    127. Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
    128. Mihoci, Andrija & Althof, Michael & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2019. "FRM Financial Risk Meter," IRTG 1792 Discussion Papers 2019-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    129. Keilbar, Georg & Wang, Weining, 2019. "Modelling Systemic Risk Using Neural Network Quantile Regression," IRTG 1792 Discussion Papers 2019-019, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    130. Yaya Su & Zhehao Huang & Benjamin M. Drakeford, 2019. "Monetary Policy, Industry Heterogeneity and Systemic Risk—Based on a High Dimensional Network Analysis," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    131. Li Guo & Lin Peng & Yubo Tao & Jun Tu, 2017. "Joint News, Attention Spillover,and Market Returns," Papers 1703.02715, arXiv.org, revised Nov 2022.
    132. Ye, Wuyi & Li, Mingge & Wu, Yuehua, 2022. "A novel estimation of time-varying quantile correlation for financial contagion detection," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    133. Foglia, Matteo & Angelini, Eliana, 2020. "From me to you: Measuring connectedness between Eurozone financial institutions," Research in International Business and Finance, Elsevier, vol. 54(C).
    134. Liu, Ruicheng & Pun, Chi Seng, 2022. "Machine-Learning-enhanced systemic risk measure: A Two-Step supervised learning approach," Journal of Banking & Finance, Elsevier, vol. 136(C).
    135. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost,Tomáš, 2020. "From physical to financial contagion: the COVID-19 pandemic and increasing systemic risk among banks," EconStor Preprints 218944, ZBW - Leibniz Information Centre for Economics.
    136. Pacelli, Vincenzo & Miglietta, Federica & Foglia, Matteo, 2022. "The extreme risk connectedness of the new financial system: European evidence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    137. Hu, Junjie & Härdle, Wolfgang, 2021. "Networks of news and cross-sectional returns," IRTG 1792 Discussion Papers 2021-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    138. Chen, Elynn Y. & Fan, Jianqing & Zhu, Xuening, 2023. "Community network auto-regression for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1239-1256.
    139. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2023. "Tail dependence structure and extreme risk spillover effects between the international agricultural futures and spot markets," Papers 2303.11030, arXiv.org.
    140. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    141. Zhu, Xuening & Chang, Xiangyu & Li, Runze & Wang, Hansheng, 2019. "Portal nodes screening for large scale social networks," Journal of Econometrics, Elsevier, vol. 209(2), pages 145-157.
    142. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

  75. Wolfgang Karl Härdle & Andrija Mihoci & Christopher Hian-Ann Ting, 2014. "Adaptive Order Flow Forecasting with Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2014-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    2. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  76. Mengmeng Guo & Lhan Zhou & Jianhua Z. Huang & Wolfgang Karl Härdle, 2013. "Functional Data Analysis of Generalized Quantile Regressions," SFB 649 Discussion Papers SFB649DP2013-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Alona Zharova & Andrija Mihoci & Wolfgang Karl Härdle, 2016. "Academic Ranking Scales in Economics: Prediction and Imputation," SFB 649 Discussion Papers SFB649DP2016-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Brenda Lopez Cabrera & Franziska Schulz, 2014. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," SFB 649 Discussion Papers SFB649DP2014-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. T. Górecki & Ł. Smaga, 2017. "Multivariate analysis of variance for functional data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2172-2189, September.

  77. Wolfgang Karl Härdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
    2. Santiago Gamba-Santamaria & Luis Fernando Melo-Velandia & Camilo Orozco-Vanegas, 2021. "What can credit vintages tell us about non-performing loans?," Borradores de Economia 1154, Banco de la Republica de Colombia.

  78. Yan Fan & Wolfgang Karl Härdle & Weining Wang & Lixing Zhu, 2013. "Composite Quantile Regression for the Single-Index Model," SFB 649 Discussion Papers SFB649DP2013-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Kangning Wang & Lu Lin, 2017. "Robust and efficient direction identification for groupwise additive multiple-index models and its applications," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 22-45, March.
    2. Jing Sun, 2016. "Composite quantile regression for single-index models with asymmetric errors," Computational Statistics, Springer, vol. 31(1), pages 329-351, March.
    3. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Lining Yu & Wolfgang Karl Hardle & Lukas Borke & Thijs Benschop, 2020. "An AI approach to measuring financial risk," Papers 2009.13222, arXiv.org.
    5. Yazhao Lv & Riquan Zhang & Weihua Zhao & Jicai Liu, 2015. "Quantile regression and variable selection of partial linear single-index model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 375-409, April.
    6. Lining Yu & Wolfgang Karl Härdle & Lukas Borke & Thijs Benschop, 2017. "FRM: a Financial Risk Meter based on penalizing tail events occurrence," SFB 649 Discussion Papers SFB649DP2017-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  79. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.

  80. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Ying Chen & Wolfgang K. Härdle & Qiang He & Piotr Majer, 2015. "Risk Related Brain Regions Detected with 3D Image FPCA," SFB 649 Discussion Papers SFB649DP2015-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Trebesch, Christoph & Chamon, Marcos & Schumacher, Julian, 2018. "Foreign-Law Bonds: Can They Reduce Sovereign Borrowing Costs?," CEPR Discussion Papers 13020, C.E.P.R. Discussion Papers.
    4. Trebesch, Christoph & Zettelmeyer, Jeromin, 2015. "ECB Interventions in Distressed Sovereign Debt Markets: The Case of Greek Bonds," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112809, Verein für Socialpolitik / German Economic Association.
    5. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    6. Zongwu Cai & Jiazi Chen & Linlin Niu, 2021. "A Semiparametric Model for Bond Pricing with Life Cycle Fundamental," Working Papers 2021-01-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    7. Zongwu Cai & Jiazi Chen & Linlin Liu, 2021. "Estimating Impact of Age Distribution on Bond Pricing: A Semiparametric Functional Data Analysis Approach," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202102, University of Kansas, Department of Economics, revised Jan 2021.
    8. Lorenzo Boldrini & Eric Hillebrand, 2015. "The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach," CREATES Research Papers 2015-39, Department of Economics and Business Economics, Aarhus University.
    9. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Siem Jan Koopman & Julia Schaumburg & Quint Wiersma, 2021. "Joint Modelling and Estimation of Global and Local Cross-Sectional Dependence in Large Panels," Tinbergen Institute Discussion Papers 21-008/III, Tinbergen Institute.
    11. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    12. Marius Acatrinei, 2017. "Macroeconomic fundamentals and latent factor of the EU yield curve," EIOPA Financial Stability Report - Thematic Articles 11, EIOPA, Risks and Financial Stability Department.
    13. Shi Chen & Wolfgang Karl Härdle & Weining Wang, "undated". "Inflation Co-movement across Countries in Multi-maturity Term Structure: An Arbitrage-Free Approach," SFB 649 Discussion Papers SFB649DP2015-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  81. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.

    Cited by:

    1. Kim, Jeonghyun & Seo, Byeongseon, 2015. "Transaction Costs And Nonlinear Mean Reversion In The Eu Emission Trading Scheme," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 56(2), pages 281-296, December.
    2. Stefan Trück & Rafal Weron, 2015. "Convenience yields and risk premiums in the EU-ETS - Evidence from the Kyoto commitment period," HSC Research Reports HSC/15/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. Gil-Alana, Luis A. & Gupta, Rangan & de Gracia, Fernando Perez, 2016. "Modeling persistence of carbon emission allowance prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 221-226.
    4. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "What explains the short," Working Papers 2014-81, Department of Research, Ipag Business School.
    5. Don Bredin and John Parsons, 2016. "Why is Spot Carbon so Cheap and Future Carbon so Dear? The Term Structure of Carbon Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "What explains the short-term dynamics of the prices of CO2 emissions?," NIPE Working Papers 04/2014, NIPE - Universidade do Minho.
    7. Thijs Benschopa & Brenda López Cabrera, 2014. "Volatility Modelling of CO2 Emission Allowance Spot Prices with Regime-Switching GARCH Models," SFB 649 Discussion Papers SFB649DP2014-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Hintermann, Beat & Peterson, Sonja & Rickels, Wilfried, 2014. "Price and market behavior in Phase II of the EU ETS," Kiel Working Papers 1962, Kiel Institute for the World Economy (IfW Kiel).
    9. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    10. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  82. Wolfgang Karl Härdle & Yuichi Mori & Jürgen Symanzik, 2012. "Computational Statistics (Journal)," SFB 649 Discussion Papers SFB649DP2012-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    2. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, University Library of Munich, Germany.
    3. Krzysztof Burnecki & Joanna Janczura & Rafał Weron, 2010. "Building Loss Models," SFB 649 Discussion Papers SFB649DP2010-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    5. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Sarno, Lucio & Valente, Giorgio, 2005. "Empirical exchange rate models and currency risk: some evidence from density forecasts," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 363-385, March.
    7. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    9. Burnecki, Krzysztof & Misiorek, Adam & Weron, Rafal, 2010. "Loss Distributions," MPRA Paper 22163, University Library of Munich, Germany.
    10. Ziegenhagen, Uwe & Klinke, Sigbert & Härdle, Wolfgang Karl, 2004. "Yxilon: Designing The Next Generation, Vertically Integrable Statistical Software Environment," Papers 2004,40, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    11. Lubos Briatka, 2006. "How Big is Big Enough? Justifying Results of the iid Test Based on the Correlation Integral in the Non-Normal World," CERGE-EI Working Papers wp308, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    12. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.

  83. Toshio Honda & Wolfgang Karl Härdle, 2012. "Variable selection in Cox regression models with varying coefficients," SFB 649 Discussion Papers SFB649DP2012-061, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Honda, Toshio & 本田, 敏雄, 2019. "The de-biased group Lasso estimation for varying coefficient models," Discussion Papers 2018-04, Graduate School of Economics, Hitotsubashi University.
    2. Toshio Honda, 2021. "The de-biased group Lasso estimation for varying coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(1), pages 3-29, February.
    3. HONDA, Toshio & 本田, 敏雄 & YABE, Ryota & 矢部, 竜太, 2017. "Variable selection and structure identification for varying coefficient Cox models," Discussion Papers 2016-05, Graduate School of Economics, Hitotsubashi University.
    4. Ling Zhou & Lu Tang & Angela T. Song & Diane M. Cibrik & Peter X.-K. Song, 2017. "A LASSO Method to Identify Protein Signature Predicting Post-transplant Renal Graft Survival," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 431-452, December.

  84. Wolfgang Karl Härdle & Dedy Dwi Prastyo & Christian Hafner, 2012. "Support Vector Machines with Evolutionary Feature Selection for Default Prediction," SFB 649 Discussion Papers SFB649DP2012-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Karl Härdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Maciej Zieba & Wolfgang K. Härdle, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers SFB649DP2016-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Dedy Dwi Prastyo & Wolfgang Karl Härdle, 2014. "Localising Forward Intensities for Multiperiod Corporate Default," SFB 649 Discussion Papers SFB649DP2014-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  85. Wolfgang Karl Härdle & Elena Silyakova, 2012. "Implied Basket Correlation Dynamics," SFB 649 Discussion Papers SFB649DP2012-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Schadner, 2021. "Feasible Implied Correlation Matrices from Factor Structures," Papers 2107.00427, arXiv.org.
    2. Markopoulou, Chryssa & Skintzi, Vasiliki & Refenes, Apostolos, 2016. "On the predictability of model-free implied correlation," International Journal of Forecasting, Elsevier, vol. 32(2), pages 527-547.

  86. Wolfgang Karl Härdle & Brenda López-Cabrera & Matthias Ritter, 2012. "Forecast based Pricing of Weather Derivatives," SFB 649 Discussion Papers SFB649DP2012-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Füss, Roland & Mahringer, Steffen & Prokopczuk, Marcel, 2013. "Electricity Derivatives Pricing with Forward-Looking Information," Working Papers on Finance 1317, University of St. Gallen, School of Finance.
    2. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    3. G. Geoffrey Booth & Sanders S. Chang, 2017. "Domestic exchange rate determination in Renaissance Florence," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(3), pages 405-445, September.
    4. Cobuloglu, Halil I. & Büyüktahtakın, İ. Esra, 2015. "Food vs. biofuel: An optimization approach to the spatio-temporal analysis of land-use competition and environmental impacts," Applied Energy, Elsevier, vol. 140(C), pages 418-434.
    5. Sinha, Pankaj & Nagarnaik, Ankit & Raj, Kislay & Suman, Vineeta, 2016. "Forecasting United States Presidential election 2016 using multiple regression models," MPRA Paper 74641, University Library of Munich, Germany, revised 17 Oct 2016.
    6. Brenda López Cabrera & Martin Odening & Matthias Ritter, 2013. "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers SFB649DP2013-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    8. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.

  87. Wolfgang Karl Härdle & Nikolaus Hautsch & Andrija Mihoci, 2012. "Local Adaptive Multiplicative Error Models for High-Frequency Forecasts," SFB 649 Discussion Papers SFB649DP2012-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    3. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    4. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    5. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    6. Ying Chen & Wolfgang K. Härdle & Wee Song Chua, 2016. "Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional AutoRegressive Dynamics," SFB 649 Discussion Papers SFB649DP2016-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Wolfgang Karl Härdle & Andrija Mihoci & Christopher Hian-Ann Ting, 2014. "Adaptive Order Flow Forecasting with Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2014-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    9. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    10. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    11. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    12. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    14. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    15. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    16. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    17. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    18. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.

  88. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Lea Petrella & Alessandro G. Laporta & Luca Merlo, 2019. "Cross-Country Assessment of Systemic Risk in the European Stock Market: Evidence from a CoVaR Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 169-186, November.
    2. Marcelo Bianconi & Xiaxin Hua & Chih Ming Tan, 2013. "Determinants of Systemic Risk and Information Dissemination," Discussion Papers Series, Department of Economics, Tufts University 0776, Department of Economics, Tufts University.
    3. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    4. Wolfgang Karl Härdle & Natalia Sirotko-Sibirskaya & Weining Wang, 2014. "TENET: Tail-Event driven NETwork risk," SFB 649 Discussion Papers SFB649DP2014-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    6. Dong, Xiyong & Yoon, Seong-Min, 2023. "Effect of weather and environmental attentions on financial system risks: Evidence from Chinese high- and low-carbon assets," Energy Economics, Elsevier, vol. 121(C).
    7. Zhiwei Zhang & Dayong Zhang & Fei Wu & Qiang Ji, 2021. "Systemic risk in the Chinese financial system: A copula‐based network approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2044-2063, April.
    8. Takashi Miyazaki, 2019. "Clarifying the Response of Gold Return to Financial Indicators: An Empirical Comparative Analysis Using Ordinary Least Squares, Robust and Quantile Regressions," JRFM, MDPI, vol. 12(1), pages 1-18, February.
    9. Zevallos, Mauricio & Villarreal, Fernanda & Del Carpio, Carlos & Abbara, Omar, 2014. "Influencia de los precios de los metales y el mercado internacional en el riesgo bursátil peruano," Working Papers 2014-023, Banco Central de Reserva del Perú.
    10. Mauro Bernardi & Ghislaine Gayraud & Lea Petrella, 2013. "Bayesian inference for CoVaR," Papers 1306.2834, arXiv.org, revised Nov 2013.
    11. Caporin, Massimiliano & Garcia-Jorcano, Laura & Jimenez-Martin, Juan-Angel, 2021. "TrAffic LIght system for systemic Stress: TALIS3," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    12. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    13. Mauro Bernardi & Leopoldo Catania, 2016. "Portfolio Optimisation Under Flexible Dynamic Dependence Modelling," Papers 1601.05199, arXiv.org.

  89. Wolfgang Karl Härdle & Ostap Okhrin & Weining Wang, 2012. "HMM in dynamic HAC models," SFB 649 Discussion Papers SFB649DP2012-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.

  90. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    9. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    10. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    14. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    15. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    18. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  91. Esra Akdeniz Duran & Wolfgang Karl Härdle & Maria Osipenko, 2011. "Difference based Ridge and Liu type Estimators in Semiparametric Regression Models," SFB 649 Discussion Papers SFB649DP2011-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Shao, Zhen & Gao, Fei & Zhang, Qiang & Yang, Shan-Lin, 2015. "Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting i," Applied Energy, Elsevier, vol. 156(C), pages 502-518.
    2. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Fikri Akdeniz & Mahdi Roozbeh, 2019. "Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models," Statistical Papers, Springer, vol. 60(5), pages 1717-1739, October.
    6. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Roozbeh, Mahdi, 2015. "Shrinkage ridge estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 56-74.
    10. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    13. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Roozbeh, Mahdi, 2016. "Robust ridge estimator in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 127-144.
    16. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    17. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    23. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    24. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    28. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. Hadi Emami, 2018. "Local influence for Liu estimators in semiparametric linear models," Statistical Papers, Springer, vol. 59(2), pages 529-544, June.
    31. Roozbeh, Mahdi, 2018. "Optimal QR-based estimation in partially linear regression models with correlated errors using GCV criterion," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 45-61.
    32. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Emami, Hadi, 2015. "Influence diagnostic in ridge semiparametric models," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 106-113.
    35. Wolfgang Karl Härdle & Maria Osipenko, 2011. "Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity," SFB 649 Discussion Papers SFB649DP2011-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Chien-Chia L. Huang & Yow-Jen Jou & Hsun-Jung Cho, 2017. "Difference-based matrix perturbation method for semi-parametric regression with multicollinearity," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2161-2171, September.
    37. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    38. Massimiliano Giacalone & Demetrio Panarello & Raffaele Mattera, 2018. "Multicollinearity in regression: an efficiency comparison between Lp-norm and least squares estimators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1831-1859, July.
    39. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    40. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    41. Roozbeh, M. & Arashi, M., 2013. "Feasible ridge estimator in partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 35-44.
    42. M. Arashi & Mahdi Roozbeh, 2019. "Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data," Statistical Papers, Springer, vol. 60(3), pages 667-686, June.
    43. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    44. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    45. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  92. Weining Wang & Ihtiyor Bobojonov & Wolfgang Karl Härdle & Martin Odening, 2011. "Increasing Weather Risk: Fact or Fiction?," SFB 649 Discussion Papers SFB649DP2011-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    4. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  93. Shuzhuan Zheng & Lijian Yang & Wolfgang Karl Härdle, 2011. "A Confidence Corridor for Sparse Longitudinal Data Curves," SFB 649 Discussion Papers SFB649DP2011-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Mechtenberg, Lydia & Münster, Johannes, 2012. "A strategic mediator who is biased in the same direction as the expert can improve information transmission," Economics Letters, Elsevier, vol. 117(2), pages 490-492.
    8. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    13. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    18. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    19. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    22. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    24. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  94. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.

  95. Rong Liu & Lijian Yang & Wolfgang Karl Härdle, 2011. "Oracally Efficient Two-Step Estimation of Generalized Additive Model," SFB 649 Discussion Papers SFB649DP2011-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    12. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Miao Yang & Lan Xue & Lijian Yang, 2016. "Variable selection for additive model via cumulative ratios of empirical strengths total," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 595-616, September.
    16. Rong Liu & Yichuan Zhao, 2021. "Empirical likelihood inference for generalized additive partially linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 569-585, September.
    17. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.
    18. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    20. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    21. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    24. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers CWP59/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    25. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Li Cai & Lijian Yang, 2015. "A smooth simultaneous confidence band for conditional variance function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 632-655, September.
    27. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Hu, Jianhua & You, Jinhong & Zhou, Xian, 2017. "Improved estimation of fixed effects panel data partially linear models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 96-111.
    31. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    37. Hu, Lixia & Huang, Tao & You, Jinhong, 2019. "Two-step estimation of time-varying additive model for locally stationary time series," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 94-110.

  96. Lu Lin & Feng Li & Lixing Zhu & Wolfgang Karl Härdle, 2011. "Mean Volatility Regressions," SFB 649 Discussion Papers SFB649DP2011-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Mechtenberg, Lydia & Münster, Johannes, 2012. "A strategic mediator who is biased in the same direction as the expert can improve information transmission," Economics Letters, Elsevier, vol. 117(2), pages 490-492.
    8. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    11. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    14. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    20. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    21. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    25. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  97. Esra Akdeniz Duran & Mengmeng Guo & Wolfgang Karl Härdle, 2011. "A Confidence Corridor for Expectile Functions," SFB 649 Discussion Papers SFB649DP2011-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Mechtenberg, Lydia & Münster, Johannes, 2012. "A strategic mediator who is biased in the same direction as the expert can improve information transmission," Economics Letters, Elsevier, vol. 117(2), pages 490-492.
    8. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    11. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    14. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    20. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    21. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    25. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Stephan Stahlschmidt & Matthias Eckardt & Wolfgang K. Härdle, 2014. "Expectile Treatment Effects: An efficient alternative to compute the distribution of treatment effects," SFB 649 Discussion Papers SFB649DP2014-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  98. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Ritter, Matthias & Musshoff, Oliver & Odening, Martin, 2012. "Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122527, European Association of Agricultural Economists.
    3. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    7. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    9. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Brenda López Cabrera & Martin Odening & Matthias Ritter, 2013. "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers SFB649DP2013-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  99. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    6. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Sahu, Atma Ram & Palei, Sanjay Kumar, 2022. "Fault analysis of dragline subsystem using Bayesian network model," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    12. Robinson, Peter & Taylor, Luke, 2017. "Adaptive estimation in multiple time series with independent component errors," LSE Research Online Documents on Economics 68345, London School of Economics and Political Science, LSE Library.
    13. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  100. Wolfgang Karl Härdle & Brenda López Cabrera & Ostap Okhrin & Weining Wang, 2011. "Localising temperature risk," SFB 649 Discussion Papers SFB649DP2011-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    6. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Mechtenberg, Lydia & Münster, Johannes, 2012. "A strategic mediator who is biased in the same direction as the expert can improve information transmission," Economics Letters, Elsevier, vol. 117(2), pages 490-492.
    10. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    13. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    16. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    22. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    23. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    27. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    29. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    30. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    33. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    34. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    37. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    38. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    39. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    40. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  101. Wolfgang Karl Härdle & Maria Osipenko, 2011. "Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity," SFB 649 Discussion Papers SFB649DP2011-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    10. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    13. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    19. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    20. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Å tulec, Ivana & Petljak, Kristina & Naletina, Dora, 2019. "Weather impact on retail sales: How can weather derivatives help with adverse weather deviations?," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 1-10.
    22. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    25. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Zhuoxin Liu & Laijun Zhao & Chenchen Wang & Yong Yang & Jian Xue & Xin Bo & Deqiang Li & Dengguo Liu, 2019. "An Actuarial Pricing Method for Air Quality Index Options," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    28. Hesamzadeh, Mohammad Reza & Biggar, Darryl R., 2021. "Generalized FTRs for hedging inter-nodal pricing risk," Energy Economics, Elsevier, vol. 94(C).
    29. Rosella Castellano & Roy Cerqueti & Giulia Rotundo, 2020. "Exploring the financial risk of a temperature index: a fractional integrated approach," Annals of Operations Research, Springer, vol. 284(1), pages 225-242, January.
    30. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. Lu Zong & Manuela Ender, 2016. "Spatially-Aggregated Temperature Derivatives: Agricultural Risk Management in China," IJFS, MDPI, vol. 4(3), pages 1-17, September.
    33. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    37. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    38. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  102. Wolfgang Karl Härdle & Vladimir Spokoiny & Weining Wang, 2011. "Local Quantile Regression," SFB 649 Discussion Papers SFB649DP2011-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Raffaele Fiocco & Carlo Scarpa, 2011. "The Regulation of Interdependent Markets," SFB 649 Discussion Papers SFB649DP2011-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Gökhan Cebiro˜glu & Ulrich Horst, 2011. "Optimal liquidation in dark pools," SFB 649 Discussion Papers SFB649DP2011-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Patrick Cheridito & Ulrich Horst & Michael Kupper & Traian A. Pirvu, 2011. "Equilibrium Pricing in Incomplete Markets under Translation Invariant Preferences," SFB 649 Discussion Papers SFB649DP2011-083, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Bertrand, Aurelie & Hafner, Christian, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," LIDAM Discussion Papers ISBA 2011028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Santiago Moreno-Bromberg & Luca Taschini, 2011. "Pollution permits, Strategic Trading and Dynamic Technology Adoption," SFB 649 Discussion Papers SFB649DP2011-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Alona Zharova & Andrija Mihoci & Wolfgang Karl Härdle, 2016. "Academic Ranking Scales in Economics: Prediction and Imputation," SFB 649 Discussion Papers SFB649DP2016-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Mechtenberg, Lydia & Münster, Johannes, 2012. "A strategic mediator who is biased in the same direction as the expert can improve information transmission," Economics Letters, Elsevier, vol. 117(2), pages 490-492.
    10. Ray-Bing Chen & Ying Chen & Wolfgang Härdle, 2011. "TVICA - Time Varying Independent Component Analysis and Its Application to Financial Data," SFB 649 Discussion Papers SFB649DP2011-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2013. "Financial network systemic risk contributions," CFS Working Paper Series 2013/20, Center for Financial Studies (CFS).
    13. Johanna Kappus & Markus Reiß, 2011. "Estimation of the characteristics of a Lévy process observed at arbitrary frequency," SFB 649 Discussion Papers SFB649DP2011-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Yang, Linchuan & Chau, K.W. & Wang, Xu, 2019. "Are low-end housing purchasers more willing to pay for access to basic public services? Evidence from China," Research in Transportation Economics, Elsevier, vol. 76(C).
    15. James E. Gentle & Wolfgang Karl Härdle & Yuichi Mori, 2011. "How Computational Statistics Became the Backbone of Modern Data Science," SFB 649 Discussion Papers SFB649DP2011-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    17. Alexander Meyer-Gohde, 2011. "Monetary Policy, Determinacy, and the Natural Rate Hypothesis," SFB 649 Discussion Papers SFB649DP2011-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2011. "Bayesian Networks and Sex-related Homicides," SFB 649 Discussion Papers SFB649DP2011-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Ulrich Horst & Michael Kupper & Andrea Macrina & Christoph Mainberger, 2011. "Continuous Equilibrium under Base Preferences and Attainable Initial Endowments," SFB 649 Discussion Papers SFB649DP2011-082, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Lai, Yani & Zheng, Xian & Choy, Lennon H.T. & Wang, Jiayuan, 2017. "Property rights and housing prices: An empirical study of small property rights housing in Shenzhen, China," Land Use Policy, Elsevier, vol. 68(C), pages 429-437.
    21. Xiaoqi Zhang & Yanqiao Zheng & Lei Sun & Qiwen Dai, 2019. "Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
    22. Sven Tischer & Lutz Hildebrandt, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers SFB649DP2011-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Ulrich Bindseil & Philipp Johann König, 2011. "The economics of TARGET2 balances," SFB 649 Discussion Papers SFB649DP2011-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    25. Raffaele Fiocco & Mario Gilli, 2011. "Bargaining and Collusion in a Regulatory Model," Working Papers 207, University of Milano-Bicocca, Department of Economics, revised Mar 2011.
    26. Santiago Moreno-Bromberg & Traian A. Pirvu & Anthony Réveillac, 2011. "CRRA Utility Maximization under Risk Constraints," SFB 649 Discussion Papers SFB649DP2011-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Wolfgang Härdle & Maria Osipenko, 2011. "Pricing Chinese rain: a multi-site multi-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers SFB649DP2011-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    29. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    30. Dirk Hofmann & Salmai Qari, 2011. "The Law of Attraction: Bilateral Search and Horizontal Heterogeneity," SFB 649 Discussion Papers SFB649DP2011-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    32. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    33. Markus Bibinger, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers SFB649DP2011-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    36. Gökhan Cebiroğlu & Ulrich Horst, 2011. "Optimal Display of Iceberg Orders," SFB 649 Discussion Papers SFB649DP2011-057, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    37. Congbo Chen & Azhong Ye, 2021. "Heterogeneous Effects of ICT across Multiple Economic Development in Chinese Cities: A Spatial Quantile Regression Model," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    38. Felix Naujokat & Ulrich Horst, 2011. "When to Cross the Spread: Curve Following with Singular Control," SFB 649 Discussion Papers SFB649DP2011-053, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    39. Markus Reiß & Yves Rozenholc & Charles A. Cuenod, 2011. "Pointwise adaptive estimation for quantile regression," SFB 649 Discussion Papers SFB649DP2011-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    40. Markus Bibinger, 2011. "Asymptotics of Asynchronicity," SFB 649 Discussion Papers SFB649DP2011-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    41. Juliane Scheffel, 2011. "Compensation of Unusual Working Schedules," SFB 649 Discussion Papers SFB649DP2011-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    42. Gregor Heyne & Michael Kupper & Christoph Mainberger, 2011. "Minimal Supersolutions of BSDEs with Lower Semicontinuous Generators," SFB 649 Discussion Papers SFB649DP2011-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  103. Maria Grith & Wolfgang Karl Härdle & Melanie Schienle, 2010. "Nonparametric Estimation of Risk-Neutral Densities," SFB 649 Discussion Papers SFB649DP2010-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Alexander L. Baranovski, 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers SFB649DP2010-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Carlo Marinelli & Stefano d'Addona, 2015. "Nonparametric estimates of pricing functionals," Papers 1506.06568, arXiv.org, revised Sep 2017.
    3. Arnerić Josip, 2020. "Realized density estimation using intraday prices," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 1-9, May.
    4. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    5. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Ana M. Monteiro & Antonio A. F. Santos, 2020. "Conditional risk-neutral density from option prices by local polynomial kernel smoothing with no-arbitrage constraints," Review of Derivatives Research, Springer, vol. 23(1), pages 41-61, April.
    7. Carolin Hecht & Katja Hanewald, 2010. "Sociodemographic, Economic, and Psychological Drivers of the Demand for Life Insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers SFB649DP2010-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Ben Boukai, 2021. "On the RND under Heston's stochastic volatility model," Papers 2101.03626, arXiv.org.
    9. Ana M. Monteiro & António A. F. Santos, 2022. "Option prices for risk‐neutral density estimation using nonparametric methods through big data and large‐scale problems," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 152-171, January.
    10. Wolfgang Karl Härdle & Rouslan Moro & Linda Hoffmann, 2010. "Learning Machines Supporting Bankruptcy Prediction," SFB 649 Discussion Papers SFB649DP2010-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Ben Boukai, 2021. "The Generalized Gamma distribution as a useful RND under Heston's stochastic volatility model," Papers 2108.07937, arXiv.org, revised Aug 2021.
    12. Duca, Ioana Andreea & Ruxanda, Gheorghe, 2013. "A View on the Risk-Neutral Density Forecasting of the Dax30 Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 101-114, June.
    13. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.

  104. Wolfgang Karl Härdle & Elena Silyakova, 2010. "Volatility Investing with Variance Swaps," SFB 649 Discussion Papers SFB649DP2010-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Christian Basteck & Tijmen R. Daniëls, 2010. "Every Symmetric 3 x 3 Global Game of Strategic Complementarities Is Noise Independent," SFB 649 Discussion Papers SFB649DP2010-061, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    4. Carolin Hecht & Katja Hanewald, 2010. "Sociodemographic, Economic, and Psychological Drivers of the Demand for Life Insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers SFB649DP2010-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Wolfgang Karl Härdle & Rouslan Moro & Linda Hoffmann, 2010. "Learning Machines Supporting Bankruptcy Prediction," SFB 649 Discussion Papers SFB649DP2010-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Ralf Sabiwalsky, 2010. "Executive Compensation Regulation and the Dynamics of the Pay-Performance Sensitivity," SFB 649 Discussion Papers SFB649DP2010-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Vladimir Panov, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers SFB649DP2010-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  105. Wolfgang Karl Härdle & Stefan Trück, 2010. "The dynamics of hourly electricity prices," SFB 649 Discussion Papers SFB649DP2010-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    2. Michail I. Seitaridis & Nikolaos S. Thomaidis & Pandelis N. Biskas, 2021. "Fundamental Responsiveness in European Electricity Prices," Energies, MDPI, vol. 14(22), pages 1-14, November.
    3. Christian Pape & Arne Vogler & Oliver Woll & Christoph Weber, 2017. "Forecasting the distributions of hourly electricity spot prices," EWL Working Papers 1705, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised May 2017.
    4. Katarzyna Maciejowska & Rafał Weron, 2015. "Forecasting of daily electricity prices with factor models: utilizing intra-day and inter-zone relationships," Computational Statistics, Springer, vol. 30(3), pages 805-819, September.
    5. Cludius, Johanna & Hermann, Hauke & Matthes, Felix Chr. & Graichen, Verena, 2014. "The merit order effect of wind and photovoltaic electricity generation in Germany 2008–2016: Estimation and distributional implications," Energy Economics, Elsevier, vol. 44(C), pages 302-313.
    6. Liebl, Dominik, 2010. "Modeling hourly Electricity Spot Market Prices as non stationary functional times series," MPRA Paper 25017, University Library of Munich, Germany.
    7. Liebl, Dominik, 2010. "Estimation of the Semiparametric Factor Model: Application to Modelling Time Series of Electricity Spot Prices," MPRA Paper 26800, University Library of Munich, Germany.
    8. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  106. Wolfgang Karl Härdle & Ostap Okhrin & Yarema Okhrin, 2010. "Time varying Hierarchical Archimedean Copulae," SFB 649 Discussion Papers SFB649DP2010-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Krzysztof Burnecki & Joanna Janczura & Rafał Weron, 2010. "Building Loss Models," SFB 649 Discussion Papers SFB649DP2010-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Nikolaus Hautsch & Julia Schuamburg & Melanie Schienle, 2012. "Modeling Time-Varying Dependencies between Positive-Valued High-Frequency Time Series," SFB 649 Discussion Papers SFB649DP2012-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Francis X. Diebold & Kamil Yilmaz, 2011. "On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms," Koç University-TUSIAD Economic Research Forum Working Papers 1124, Koc University-TUSIAD Economic Research Forum.

  107. Wolfgang Karl Härdle & Ya’acov Ritov & Song Song, 2010. "Partial Linear Quantile Regression and Bootstrap Confidence Bands," SFB 649 Discussion Papers SFB649DP2010-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Christian Basteck & Tijmen R. Daniëls, 2010. "Every Symmetric 3 x 3 Global Game of Strategic Complementarities Is Noise Independent," SFB 649 Discussion Papers SFB649DP2010-061, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Alexander L. Baranovski, 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers SFB649DP2010-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    4. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Wolfgang Karl Härdle & Ya'acov Ritov & Weining Wang, 2013. "Tie the straps: uniform bootstrap confidence bands for bounded influence curve estimators," SFB 649 Discussion Papers SFB649DP2013-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    7. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Carolin Hecht & Katja Hanewald, 2010. "Sociodemographic, Economic, and Psychological Drivers of the Demand for Life Insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers SFB649DP2010-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Wolfgang Karl Härdle & Rouslan Moro & Linda Hoffmann, 2010. "Learning Machines Supporting Bankruptcy Prediction," SFB 649 Discussion Papers SFB649DP2010-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Ralf Sabiwalsky, 2010. "Executive Compensation Regulation and the Dynamics of the Pay-Performance Sensitivity," SFB 649 Discussion Papers SFB649DP2010-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Vladimir Panov, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers SFB649DP2010-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Mengmeng Guo & Wolfgang Härdle, 2012. "Simultaneous confidence bands for expectile functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(4), pages 517-541, October.
    17. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  108. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2010. "High Dimensional Nonstationary Time Series Modelling with Generalized Dynamic Semiparametric Factor Model," SFB 649 Discussion Papers SFB649DP2010-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Christian Basteck & Tijmen R. Daniëls, 2010. "Every Symmetric 3 x 3 Global Game of Strategic Complementarities Is Noise Independent," SFB 649 Discussion Papers SFB649DP2010-061, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    4. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Wolfgang Karl Härdle & Elena Silyakova, 2012. "Implied Basket Correlation Dynamics," SFB 649 Discussion Papers SFB649DP2012-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    11. Ralf Sabiwalsky, 2010. "Executive Compensation Regulation and the Dynamics of the Pay-Performance Sensitivity," SFB 649 Discussion Papers SFB649DP2010-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Vladimir Panov, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers SFB649DP2010-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  109. Fred Benth & Wolfgang Karl Härdle & Brenda López Cabrera, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers SFB649DP2009-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    2. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    4. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    5. Heng Xiong & Rogemar Mamon, 2018. "Putting a price tag on temperature," Computational Management Science, Springer, vol. 15(2), pages 259-296, June.
    6. Wolfgang Karl Härdle & Brenda López-Cabrera & Matthias Ritter, 2012. "Forecast based Pricing of Weather Derivatives," SFB 649 Discussion Papers SFB649DP2012-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, January.
    8. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.

  110. Barbara Choros & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO Pricing with Copulae," SFB 649 Discussion Papers SFB649DP2009-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    2. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  111. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Barbara Choroś-Tomczyk & Wolfgang Karl H�rdle & Ludger Overbeck, 2014. "Copula dynamics in CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1573-1585, September.
    2. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    3. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  112. Xia Cui & Wolfgang Karl Härdle & Lixing Zhu, 2009. "Generalized single-index models: The EFM approach," SFB 649 Discussion Papers SFB649DP2009-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Gerhard Tutz & Sebastian Petry, 2016. "Generalized additive models with unknown link function including variable selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2866-2885, November.

  113. Wolfgang Härdle & Alena Mysickova, 2009. "Stochastic Population Forecast for Germany and its Consequence for the German Pension System," SFB 649 Discussion Papers SFB649DP2009-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    2. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Markéta Arltová & Jitka Langhamrová & Jana Langhamrová, 2013. "Development of Life Expectancy in the Czech Republic in Years 1920-2010 with an Outlook to 2050," Prague Economic Papers, Prague University of Economics and Business, vol. 2013(1), pages 125-143.

  114. Wolfgang Karl Härdle & Nikolaus Hautsch & Andrija Mihoci, 2009. "Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2009-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    2. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
    3. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Ying Chen & Wolfgang K. Härdle & Wee Song Chua, 2016. "Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional AutoRegressive Dynamics," SFB 649 Discussion Papers SFB649DP2016-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    6. Geir H. Bjønnes & Carol L. Osler & Dagfinn Rime, 2021. "Price discovery in two‐tier markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3109-3133, April.
    7. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.
    8. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
    9. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
    10. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
    11. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
    12. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Nikolaus Hautsch & Ruihong Huang, 2011. "Limit Order Flow, Market Impact and Optimal Order Sizes: Evidence from NASDAQ TotalView-ITCH Data," SFB 649 Discussion Papers SFB649DP2011-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    17. Siikanen, Milla & Kanniainen, Juho & Luoma, Arto, 2017. "What drives the sensitivity of limit order books to company announcement arrivals?," Economics Letters, Elsevier, vol. 159(C), pages 65-68.
    18. Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
    19. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.

  115. Wolfgang Härdle & Brenda López Cabrera, 2009. "Implied Market Price of Weather Risk," SFB 649 Discussion Papers SFB649DP2009-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Fred Espen Benth, 2021. "Pricing of Commodity and Energy Derivatives for Polynomial Processes," Mathematics, MDPI, vol. 9(2), pages 1-30, January.
    2. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    3. Benth, Fred Espen & Koekebakker, Steen, 2015. "Pricing of forwards and other derivatives in cointegrated commodity markets," Energy Economics, Elsevier, vol. 52(PA), pages 104-117.
    4. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    5. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    7. Jr‐Wei Huang & Sharon S. Yang & Chuang‐Chang Chang, 2018. "Modeling temperature behaviors: Application to weather derivative valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1152-1175, September.
    8. Benth, Fred Espen & Taib, Che Mohd Imran Che, 2013. "On the speed towards the mean for continuous time autoregressive moving average processes with applications to energy markets," Energy Economics, Elsevier, vol. 40(C), pages 259-268.
    9. Šaltytė Benth, Jūratė & Benth, Fred Espen, 2012. "A critical view on temperature modelling for application in weather derivatives markets," Energy Economics, Elsevier, vol. 34(2), pages 592-602.
    10. Christensen, Troels Sønderby & Pircalabu, Anca & Høg, Esben, 2019. "A seasonal copula mixture for hedging the clean spark spread with wind power futures," Energy Economics, Elsevier, vol. 78(C), pages 64-80.
    11. Larsson, Karl & Green, Rikard & Benth, Fred Espen, 2023. "A stochastic time-series model for solar irradiation," Energy Economics, Elsevier, vol. 117(C).
    12. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    13. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    15. Matthias Ritter & Oliver Mußhoff & Martin Odening, 2010. "Meteorological forecasts and the pricing of weather derivatives," SFB 649 Discussion Papers SFB649DP2010-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. L. Kermiche & N. Vuillermet, 2016. "Weather derivatives structuring and pricing: a sustainable agricultural approach in Africa," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 165-177, January.
    17. Wolfgang Karl Härdle & Brenda López Cabrera & Ostap Okhrin & Weining Wang, 2016. "Localizing Temperature Risk," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1491-1508, October.
    18. Mengmeng Guo & Lhan Zhou & Jianhua Z. Huang & Wolfgang Karl Härdle, 2013. "Functional Data Analysis of Generalized Quantile Regressions," SFB 649 Discussion Papers SFB649DP2013-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Fred Benth & Wolfgang Karl Härdle & Brenda López Cabrera, 2009. "Pricing of Asian temperature risk," SFB 649 Discussion Papers SFB649DP2009-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Dorfleitner, Gregor & Wimmer, Maximilian, 2010. "The pricing of temperature futures at the Chicago Mercantile Exchange," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1360-1370, June.
    21. Brenda López Cabrera & Martin Odening & Matthias Ritter, 2013. "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers SFB649DP2013-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Ahčan, Aleš, 2012. "Statistical analysis of model risk concerning temperature residuals and its impact on pricing weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 131-138.
    23. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    24. Evarest Emmanuel & Berntsson Fredrik & Singull Martin & Yang Xiangfeng, 2018. "Weather derivatives pricing using regime switching model," Monte Carlo Methods and Applications, De Gruyter, vol. 24(1), pages 13-27, March.
    25. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    26. Wolfgang Karl Härdle & Maria Osipenko, 2011. "Spatial Risk Premium on Weather Derivatives and Hedging Weather Exposure in Electricity," SFB 649 Discussion Papers SFB649DP2011-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Kanamura, Takashi, 2019. "Volumetric Risk Hedging Strategies and Basis Risk Premium for Solar Power," MPRA Paper 92009, University Library of Munich, Germany.
    28. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    29. Wolfgang Karl Härdle & Brenda López-Cabrera & Matthias Ritter, 2012. "Forecast based Pricing of Weather Derivatives," SFB 649 Discussion Papers SFB649DP2012-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Fred Espen Benth & Anca Pircalabu, 2018. "A non-Gaussian Ornstein–Uhlenbeck model for pricing wind power futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 25(1), pages 36-65, January.
    31. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, January.
    32. Fred Espen Benth & Paul Kruhner, 2014. "Representation of infinite dimensional forward price models in commodity markets," Papers 1403.4111, arXiv.org.
    33. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    34. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 1-30, February.
    35. Ragnhild Noven & Almut Veraart & Axel Gandy, 2015. "A Lévy-driven rainfall model with applications to futures pricing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 403-432, October.

  116. Wolfgang Härdle & Ostap Okhrin, 2009. "De copulis non est disputandum - Copulae: An Overview," SFB 649 Discussion Papers SFB649DP2009-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Fabrizio Durante & Roberto Ghiselli-Ricci, 2012. "Supermigrative copulas and positive dependence," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 327-342, July.
    2. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    3. Thorsten Dickhaus & Jakob Gierl, 2012. "Simultaneous test procedures in terms of p-value copulae," SFB 649 Discussion Papers SFB649DP2012-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Christian Schellhase & Torben Kuhlenkasper, 2017. "Semi-parametric estimation of income mobility with D‑vines using bivariate penalised splines," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 11(2), pages 107-134, October.
    6. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.

  117. Ji Cao & Wolfgang Härdle & Julius Mungo, 2009. "A Joint Analysis of the KOSPI 200 Option and ODAX Option Markets Dynamics," SFB 649 Discussion Papers SFB649DP2009-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    2. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    3. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  118. Yingcun Xia & Wolfgang Härdle & Oliver Linton, 2009. "Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator," SFB 649 Discussion Papers SFB649DP2009-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    2. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Chuan Goh, 2009. "Bootstrap-based Bandwidth Selection for Semiparametric Generalized Regression Estimators," Working Papers tecipa-375, University of Toronto, Department of Economics.
    5. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  119. Wolfgang Härdle & Volker Krätschmer & Rouslan Moro, 2009. "A Microeconomic Explanation of the EPK Paradox," SFB 649 Discussion Papers SFB649DP2009-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    2. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
    3. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.

  120. Wolfgang Härdle & Nikolaus Hautsch & Uta Pigorsch, 2008. "Measuring and Modeling Risk Using High-Frequency Data," SFB 649 Discussion Papers SFB649DP2008-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Enzo Weber & Yanqun Zhang, 2008. "Common Influences, Spillover and Integration in Chinese Stock Markets," SFB 649 Discussion Papers SFB649DP2008-072, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Zhang, Zhengjun & Zhu, Bin, 2016. "Copula structured M4 processes with application to high-frequency financial data," Journal of Econometrics, Elsevier, vol. 194(2), pages 231-241.
    3. Till Dannewald & Lutz Hildebrandt, 2008. "A Brand Specific Investigation of International Cost Shock Threats on Price and Margin with a Manufacturer-Wholesaler-Retailer Model," SFB 649 Discussion Papers SFB649DP2008-070, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Enzo Weber, 2008. "Structural Dynamic Conditional Correlation," SFB 649 Discussion Papers SFB649DP2008-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  121. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Peter Christoffersen & Kris Jacobs & Bo Young Chang, 2011. "Forecasting with Option Implied Information," CREATES Research Papers 2011-46, Department of Economics and Business Economics, Aarhus University.
    3. Wolfgang Karl Hardle & Elena Silyakova, 2020. "Implied Basket Correlation Dynamics," Papers 2009.09770, arXiv.org.
    4. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    6. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    7. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    8. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    9. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.
    10. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.

  122. Taleb Ahmad & Wolfgang Härdle, 2008. "Statistics E-learning Platforms Evaluation: Case Study," SFB 649 Discussion Papers SFB649DP2008-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Cezar Scarlat & Cornel Ghita & Ioana Barda-Miron & Ioana Ceausu & Cornel Chira, 2011. "Improving the Managerial Skills of Romanian University Managers by a Country-Wide E-Training Programme," MIC 2011: Managing Sustainability? Proceedings of the 12th International Conference, Portorož, 23–26 November 2011 [Selected Papers],, University of Primorska, Faculty of Management Koper.
    2. Wocken, Meike & Jens-Peter, Loy, 2011. "Evaluation of eLearning - A study of Undergraduate Agricultural Economics course," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115764, European Association of Agricultural Economists.

  123. Pavel Cizek & Wolfgang Härdle & Vladimir Spokoiny, 2008. "Adaptive pointwise estimation in time-inhomogeneous time-series models," SFB 649 Discussion Papers SFB649DP2008-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Schröder, Anna Louise & Fryzlewicz, Piotr, 2013. "Adaptive trend estimation in financial time series via multiscale change-point-induced basis recovery," MPRA Paper 52379, University Library of Munich, Germany.
    2. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    4. Giammarino, Flavia & Barrieu, Pauline, 2009. "A semiparametric model for the systematic factors of portfolio credit risk premia," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 655-670, September.
    5. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.

  124. Kiho Jeong & Wolfgang Härdle, 2008. "A Consistent Nonparametric Test for Causality in Quantile," SFB 649 Discussion Papers SFB649DP2008-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Härdle, Wolfgang K. & Song, Song, 2010. "Confidence Bands In Quantile Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1180-1200, August.

  125. Wolfgang Härdle & Alena Mysickova, 2008. "Numerics of Implied Binomial Trees," SFB 649 Discussion Papers SFB649DP2008-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Jansen, Jeroen & Das, Sanjiv R. & Fabozzi, Frank J., 2018. "Local volatility and the recovery rate of credit default swaps," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 1-29.

  126. Yuri Golubev & Wolfgang Härdle & Roman Timonfeev, 2008. "Testing Monotonicity of Pricing Kernels," SFB 649 Discussion Papers SFB649DP2008-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    2. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Wolfgang Härdle & Volker Krätschmer & Rouslan Moro, 2009. "A Microeconomic Explanation of the EPK Paradox," SFB 649 Discussion Papers SFB649DP2009-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
    5. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.

  127. Wolfgang Härdle & Julius Mungo, 2008. "Value-at-Risk and Expected Shortfall when there is long range dependence," SFB 649 Discussion Papers SFB649DP2008-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Mohamed Chikhi & Anne Peguin-Feissolle & Michel Terraza, 2012. "SEMIFARMA-HYGARCH Modeling of Dow Jones Return Persistence," Working Papers halshs-00793203, HAL.
    2. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    3. Sebastian Letmathe & Yuanhua Feng & André Uhde, 2021. "Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall," Working Papers CIE 141, Paderborn University, CIE Center for International Economics.
    4. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
    5. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    6. Chaker Aloui, 2011. "Latin American stock markets’ volatility spillovers during the financial crises: a multivariate FIAPARCH-DCC framework," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 4(2), pages 289-326, May.
    7. Yin Liao, 2012. "Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction," CAMA Working Papers 2012-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    9. Degiannakis, Stavros & Floros, Christos & Dent, Pamela, 2013. "Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: International evidence," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 21-33.

  128. Ray-Bing Chen & Meihui Guo & Wolfgang Härdle & Shih-Feng Huang, 2008. "Independent Component Analysis Via Copula Techniques," SFB 649 Discussion Papers SFB649DP2008-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Kumiega, Andrew & Neururer, Thaddeus & Van Vliet, Ben, 2011. "Independent component analysis for realized volatility: Analysis of the stock market crash of 2008," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 292-302, June.

  129. Wolfgang Härdle & Ostap Okhrin & Yarema Okhrin, 2008. "Modeling Dependencies in Finance using Copulae," SFB 649 Discussion Papers SFB649DP2008-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Xu, Wei & Filler, Gunther & Odening, Martin & Okhrin, Ostap, 2009. "On the Systemic Nature of Weather Risk," 2009 Conference, August 16-22, 2009, Beijing, China 51426, International Association of Agricultural Economists.
    2. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Liu, X. & Xu, W. & Odening, M., 2011. "Lassen sich Ertragsrisiken in der Landwirtschaft global diversifizieren?," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.
    4. Raushan Bokusheva, 2011. "Measuring dependence in joint distributions of yield and weather variables," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(1), pages 120-141, May.

  130. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2007. "Yxilon – A Client/Server Based Statistical Environment," SFB 649 Discussion Papers SFB649DP2007-036, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  131. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2007. "On the Utility of E-Learning in Statistics," SFB 649 Discussion Papers SFB649DP2007-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  132. Enzo Giacomini & Wolfgang Härdle, 2007. "Statistics of Risk Aversion," SFB 649 Discussion Papers SFB649DP2007-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Yuri Golubev & Wolfgang Härdle & Roman Timonfeev, 2008. "Testing Monotonicity of Pricing Kernels," SFB 649 Discussion Papers SFB649DP2008-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  133. Wen-Jen Tsay & Wolfgang Härdle, 2007. "A Generalized ARFIMA Process with Markov-Switching Fractional Differencing Parameter," SFB 649 Discussion Papers SFB649DP2007-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Chen, Shyh-Wei, 2013. "Long memory and regime switching properties of current account deficits in the US," Economic Modelling, Elsevier, vol. 35(C), pages 78-87.
    3. Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
    4. Massimiliano Caporin & Rangan Gupta, 2017. "Time-varying persistence in US inflation," Empirical Economics, Springer, vol. 53(2), pages 423-439, September.
    5. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2010. "Long Memory and Volatility Dynamics in the US Dollar Exchange Rate," Discussion Papers of DIW Berlin 975, DIW Berlin, German Institute for Economic Research.
    6. Di Sanzo, Silvestro, 2018. "A Markov switching long memory model of crude oil price return volatility," Energy Economics, Elsevier, vol. 74(C), pages 351-359.
    7. Boubaker Heni, 2018. "A Generalized ARFIMA Model with Smooth Transition Fractional Integration Parameter," Journal of Time Series Econometrics, De Gruyter, vol. 10(1), pages 1-20, January.
    8. M. A. Limam & V. Terraza & M. Terraza, 2017. "Hedge Fund Return Dynamics: Long Memory and Regime Switching," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 8(4), pages 148-166, October.

  134. Wolfgang Härdle & Rouslan Moro & Dorothea Schäfer, 2007. "Estimating Probabilities of Default With Support Vector Machines," SFB 649 Discussion Papers SFB649DP2007-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Natalia Nehrebecka, 2021. "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 719-736.
    2. Tyler Pike & Horacio Sapriza & Tom Zimmermann, 2019. "Bottom-up Leading Macroeconomic Indicators: An Application to Non-Financial Corporate Defaults using Machine Learning," Finance and Economics Discussion Series 2019-070, Board of Governors of the Federal Reserve System (U.S.).
    3. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2009. "Variable selection and oversampling in the use of smooth support vector machines for predicting the default risk of companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 512-534.
    4. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2007. "The Default Risk of Firms Examined with Smooth Support Vector Machines," Discussion Papers of DIW Berlin 757, DIW Berlin, German Institute for Economic Research.
    5. Nehrebecka Natalia, 2018. "Predicting the Default Risk of Companies. Comparison of Credit Scoring Models: Logit Vs Support Vector Machines," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(2), pages 54-73, June.
    6. Jakubik, Petr & Moinescu, Bogdan, 2015. "Assessing optimal credit growth for an emerging banking system," Economic Systems, Elsevier, vol. 39(4), pages 577-591.
    7. Junni L. Zhang & Wolfgang Härdle, 2008. "The Bayesian Additive Classification Tree Applied to Credit Risk Modelling," SFB 649 Discussion Papers SFB649DP2008-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  135. Taleb Ahmed & Wolfgang Härdle & Sigbert Klinke, 2007. "Using Wiki to Build an E-learning System in Statistics in Arabic Language," SFB 649 Discussion Papers SFB649DP2007-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2007. "On the Utility of E-Learning in Statistics," SFB 649 Discussion Papers SFB649DP2007-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  136. Kai Detlefsen & Wolfgang Härdle & Rouslan Moro, 2007. "Empirical Pricing Kernels and Investor Preferences," SFB 649 Discussion Papers SFB649DP2007-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Yuri Golubev & Wolfgang Härdle & Roman Timonfeev, 2008. "Testing Monotonicity of Pricing Kernels," SFB 649 Discussion Papers SFB649DP2008-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    3. Wolfgang Härdle & Volker Krätschmer & Rouslan Moro, 2009. "A Microeconomic Explanation of the EPK Paradox," SFB 649 Discussion Papers SFB649DP2009-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.

  137. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2007. "The Default Risk of Firms Examined with Smooth Support Vector Machines," Discussion Papers of DIW Berlin 757, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Natalia Nehrebecka, 2021. "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 719-736.
    2. Nehrebecka Natalia, 2018. "Predicting the Default Risk of Companies. Comparison of Credit Scoring Models: Logit Vs Support Vector Machines," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(2), pages 54-73, June.
    3. Jan-Henning Trustorff & Paul Konrad & Jens Leker, 2011. "Credit risk prediction using support vector machines," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 565-581, May.

  138. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    2. Enno Mammen & Byeong U. Park & Melanie Schienle, 2012. "Additive Models: Extensions and Related Models," SFB 649 Discussion Papers SFB649DP2012-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Mestekemper, Thomas & Windmann, Michael & Kauermann, Göran, 2010. "Functional hourly forecasting of water temperature," International Journal of Forecasting, Elsevier, vol. 26(4), pages 684-699, October.
    5. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    9. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Rong Liu & Yichuan Zhao, 2021. "Empirical likelihood inference for generalized additive partially linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 569-585, September.
    11. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2010. "High Dimensional Nonstationary Time Series Modelling with Generalized Dynamic Semiparametric Factor Model," SFB 649 Discussion Papers SFB649DP2010-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Alena Bömmel & Song Song & Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Härdle, 2014. "Risk Patterns and Correlated Brain Activities. Multidimensional Statistical Analysis of fMRI Data in Economic Decision Making Study," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 489-514, July.
    14. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    15. Borak, Szymon & Weron, Rafal, 2008. "A semiparametric factor model for electricity forward curve dynamics," MPRA Paper 10421, University Library of Munich, Germany.
    16. Katarzyna Maciejowska & Rafał Weron, 2015. "Forecasting of daily electricity prices with factor models: utilizing intra-day and inter-zone relationships," Computational Statistics, Springer, vol. 30(3), pages 805-819, September.
    17. Thorsten Dickhaus, 2012. "Simultaneous Statistical Inference in Dynamic Factor Models," SFB 649 Discussion Papers SFB649DP2012-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Alena MyÅ¡iÄ ková & Song Song & Piotr Majer & Peter N.C. Mohr & Hauke R. Heekeren & Wolfgang K. Härdle, 2011. "Risk Patterns and Correlated Brain Activities. Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers SFB649DP2011-085, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Borus Jungbacker & Siem Jan Koopman & Michel van der Wel, 0000. "Dynamic Factor Models with Smooth Loadings for Analyzing the Term Structure of Interest Rates," Tinbergen Institute Discussion Papers 09-041/4, Tinbergen Institute, revised 17 Sep 2010.
    20. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    21. Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Karl Härdle, 2014. "Portfolio Decisions and Brain Reactions via the CEAD method," SFB 649 Discussion Papers SFB649DP2014-036, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    23. Enzo Giacomini & Wolfgang Härdle, 2007. "Statistics of Risk Aversion," SFB 649 Discussion Papers SFB649DP2007-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2014. "Generalized dynamic semi‐parametric factor models for high‐dimensional non‐stationary time series," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 101-131, June.
    25. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    26. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers 02/13, Institute for Fiscal Studies.
    27. Liebl, Dominik, 2010. "Modeling hourly Electricity Spot Market Prices as non stationary functional times series," MPRA Paper 25017, University Library of Munich, Germany.
    28. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    29. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    30. Markus Pelger & Ruoxuan Xiong, 2022. "State-Varying Factor Models of Large Dimensions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1315-1333, June.
    31. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
    32. He, Lingyu & Huang, Fei & Shi, Jianjie & Yang, Yanrong, 2021. "Mortality forecasting using factor models: Time-varying or time-invariant factor loadings?," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 14-34.
    33. Liebl, Dominik, 2010. "Estimation of the Semiparametric Factor Model: Application to Modelling Time Series of Electricity Spot Prices," MPRA Paper 26800, University Library of Munich, Germany.
    34. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    36. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    37. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    38. Liebl, Dominik, 2013. "Modeling and Forecasting Electricity Spot Prices: A Functional Data Perspective," MPRA Paper 50881, University Library of Munich, Germany.

  139. Anton Andriyashin & Wolfgang Härdle, 2007. "QuantNet – A Database-Driven Online Repository of Scientific Information," SFB 649 Discussion Papers SFB649DP2007-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  140. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Feng, Yuanhua & Beran, Jan, 2007. "Optimal convergence rates in nonparametric regression with fractional time series errors," CoFE Discussion Papers 07/15, University of Konstanz, Center of Finance and Econometrics (CoFE).
    2. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Ranjit Kumar Paul & Bishal Gurung & Sandipan Samanta, 2015. "Analyzing the Effect of Dual Long Memory Process in Forecasting Agricultural Prices in Different Markets of India," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(4), pages 235-249.

  141. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Other publications TiSEM 51a09fbd-293b-4386-bfe9-b, Tilburg University, School of Economics and Management.

    Cited by:

    1. Mia Hubert & Irène Gijbels & Dina Vanpaemel, 2013. "Reducing the mean squared error of quantile-based estimators by smoothing," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 448-465, September.

  142. Szymon Borak & Wolfgang Härdle & Stefan Trück & Rafal Weron, 2006. "Convenience Yields for CO2 Emission Allowance Futures Contracts," SFB 649 Discussion Papers SFB649DP2006-076, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Panagiotis G. Papaioannou & George P. Papaioannou & Kostas Siettos & Akylas Stratigakos & Christos Dikaiakos, 2017. "Dynamic Conditional Correlation between Electricity and Stock markets during the Financial Crisis in Greece," Papers 1708.07063, arXiv.org.
    2. Veith, Stefan & Werner, Jörg R. & Zimmermann, Jochen, 2009. "Capital market response to emission rights returns: Evidence from the European power sector," Energy Economics, Elsevier, vol. 31(4), pages 605-613, July.
    3. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2013. "Market efficiency in the European carbon markets," Energy Policy, Elsevier, vol. 60(C), pages 785-792.
    4. Maria Mansanet-Bataller, 2011. "CO2 Prices and Portfolio Management during Phase II of the EU ETS," Working Papers 1101, Chaire Economie du climat.
    5. Amélie Charles & Olivier Darné & Jessica Fouilloux, 2010. "Testing the Martingale Difference Hypothesis in the EU ETS Markets for the CO2 Emission Allowances: Evidence from Phase I and Phase II," Working Papers hal-00473727, HAL.
    6. Rittler, Daniel, 2012. "Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 774-785.
    7. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    8. Rickels, Wilfried & Duscha, Vicki & Keller, Andreas & Peterson, Sonja, 2007. "The determinants of allowance prices in the European emissions trading scheme: Can we expect an efficient allowance market 2008?," Kiel Working Papers 1387, Kiel Institute for the World Economy (IfW Kiel).
    9. Marliese Uhrig-Homburg & Michael Wagner, 2008. "Derivative Instruments in the EU Emissions Trading Scheme — An Early Market Perspective," Energy & Environment, , vol. 19(5), pages 635-655, September.
    10. Daskalakis, George & Psychoyios, Dimitris & Markellos, Raphael N., 2009. "Modeling CO2 emission allowance prices and derivatives: Evidence from the European trading scheme," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1230-1241, July.
    11. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Tisdell, John G. & Grainger, Corinne, 2008. "An Experimental Economic Analysis of Carbon Trading Options for Australia," 2008 Conference, August 28-29, 2008, Nelson, New Zealand 96661, New Zealand Agricultural and Resource Economics Society.
    13. Vicente Medina Martínez & Ángel Pardo Tornero, 2012. "Stylized facts of CO2 returns," Working Papers. Serie AD 2012-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    14. Rittler, Daniel, 2009. "Price Discovery, Causality and Volatility Spillovers in European Union Allowances Phase II: A High Frequency Analysis," Working Papers 0492, University of Heidelberg, Department of Economics.
    15. Don Bredin and John Parsons, 2016. "Why is Spot Carbon so Cheap and Future Carbon so Dear? The Term Structure of Carbon Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    16. Philip, Dennis & Shi, Yukun, 2015. "Impact of allowance submissions in European carbon emission markets," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 27-37.
    17. Dorota Ciesielska-Maciągowska & Dawid Klimczak & Małgorzata Skrzek-Lubasińska, 2021. "Central and Eastern European CO 2 Market—Challenges of Emissions Trading for Energy Companies," Energies, MDPI, vol. 14(4), pages 1-14, February.
    18. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1), pages 27-35.
    19. Kim, Jungmu & Park, Yuen Jung & Ryu, Doojin, 2017. "Stochastic volatility of the futures prices of emission allowances: A Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 714-724.
    20. Koch, Nicolas & Bassen, Alexander, 2013. "Valuing the carbon exposure of European utilities. The role of fuel mix, permit allocation and replacement investments," Energy Economics, Elsevier, vol. 36(C), pages 431-443.
    21. Rotfuß, Waldemar, 2009. "Intraday price formation and volatility in the European Union emissions trading scheme: an introductory analysis," ZEW Discussion Papers 09-018, ZEW - Leibniz Centre for European Economic Research.
    22. Julien Chevallier, 2010. "A Note on Cointegrating and Vector Autoregressive Relationships between CO2 allowances spot and futures prices," Economics Bulletin, AccessEcon, vol. 30(2), pages 1564-1584.
    23. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    24. Julien Chevallier, 2010. "Modelling the convenience yield in carbon prices using daily and realized measures," Working Papers halshs-00463921, HAL.
    25. Heinzel, Christoph, 2008. "Implications of diverging social and private discount rates for investments in the German power industry: a new case for nuclear energy?," Dresden Discussion Paper Series in Economics 03/08, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    26. Feria-Domínguez, José Manuel & Rodriguez-Carrillero, David & Guerra-Martinez, José Carlos, 2018. "Measuring the risk-adjusted performance of CO2 emission markets: Evidence from SENDECO2," Utilities Policy, Elsevier, vol. 50(C), pages 124-132.
    27. Viteva, Svetlana & Veld-Merkoulova, Yulia V. & Campbell, Kevin, 2014. "The forecasting accuracy of implied volatility from ECX carbon options," Energy Economics, Elsevier, vol. 45(C), pages 475-484.
    28. Palao, Fernando & Pardo, Ángel, 2021. "The inconvenience yield of carbon futures," Energy Economics, Elsevier, vol. 101(C).
    29. Emilie Alberola & Benoît Chèze & Julien Chevallier, 2008. "The EU Emissions Trading Scheme : Disentangling the Effects of Industrial Production and CO2 Emissions on Carbon Prices," EconomiX Working Papers 2008-12, University of Paris Nanterre, EconomiX.
    30. Carlos Pinho & Mara Madaleno, 2011. "Links between spot and futures allowances: ECX and EEX markets comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 35(2/3/4), pages 101-131.
    31. Batten, Jonathan A. & Maddox, Grace E. & Young, Martin R., 2021. "Does weather, or energy prices, affect carbon prices?," Energy Economics, Elsevier, vol. 96(C).
    32. Rammerstorfer, Margarethe & Eisl, Roland, 2011. "Carbon capture and storage—Investment strategies for the future?," Energy Policy, Elsevier, vol. 39(11), pages 7103-7111.
    33. Leon Vinokur, 2009. "Disposition in the Carbon Market and Institutional Constraints," Working Papers 652, Queen Mary University of London, School of Economics and Finance.
    34. Chevallier, Julien & Ielpo, Florian & Mercier, Ludovic, 2009. "Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event," Energy Policy, Elsevier, vol. 37(1), pages 15-28, January.
    35. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, January.
    36. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    37. Vicente Medina & Angel Pardo, 2013. "Is the EUA a new asset class?," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 637-653, March.

  143. Shiyi Chen & Wolfgang Härdle & Rouslan Moro, 2006. "Estimation of Default Probabilities with Support Vector Machines," SFB 649 Discussion Papers SFB649DP2006-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Selçuk BAYRACI & Orkun SUSUZ, 2019. "A Deep Neural Network (DNN) based classification model in application to loan default prediction," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 75-84, Winter.
    2. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2007. "The Default Risk of Firms Examined with Smooth Support Vector Machines," Discussion Papers of DIW Berlin 757, DIW Berlin, German Institute for Economic Research.

  144. Enzo Giacomini & Michael Handel & Wolfgang K. Härdle, 2006. "Time Dependent Relative Risk Aversion," SFB 649 Discussion Papers SFB649DP2006-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Yuri Golubev & Wolfgang Härdle & Roman Timonfeev, 2008. "Testing Monotonicity of Pricing Kernels," SFB 649 Discussion Papers SFB649DP2008-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Bedoui, Rihab & Hamdi, Haykel, 2015. "Option-implied risk aversion estimation," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 142-152.
    4. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.

  145. Anton Andriyashin & Michal Benko & Wolfgang Härdle & Roman Timofeev & Uwe Ziegenhagen, 2006. "Color Harmonization in Car Manufacturing Process," SFB 649 Discussion Papers SFB649DP2006-071, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    2. Weining Wang & Ihtiyor Bobojonov & Wolfgang Karl Härdle & Martin Odening, 2011. "Increasing Weather Risk: Fact or Fiction?," SFB 649 Discussion Papers SFB649DP2011-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  146. Taleb Ahmad & Wolfgang Härdle & Julius Mungo, 2006. "On the Difficulty to Design Arabic E-learning System in Statistics," SFB 649 Discussion Papers SFB649DP2006-062, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Taleb Ahmad & Wolfgang Härdle & Sigbert Klinke & Shafiqah Alawadhi, 2013. "Using wiki to build an e-learning system in statistics in the Arabic language," Computational Statistics, Springer, vol. 28(2), pages 481-491, April.
    2. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2007. "On the Utility of E-Learning in Statistics," SFB 649 Discussion Papers SFB649DP2007-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Taleb Ahmad & Wolfgang Härdle & Sigbert Klinke & Shafeeqah Al Awadhi, 2008. "Using R, LaTeX and Wiki for an Arabic e-learning platform," SFB 649 Discussion Papers SFB649DP2008-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  147. Kai Detlefsen & Wolfgang Härdle, 2006. "Forecasting the Term Structure of Variance Swaps," SFB 649 Discussion Papers SFB649DP2006-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Cayetano, Gea, 2007. "Studying the Properties of the Correlation Trades," MPRA Paper 22318, University Library of Munich, Germany.

  148. Wolfgang Härdle & Rouslan Moro & Dorothea Schäfer, 2006. "Graphical Data Representation in Bankruptcy Analysis," SFB 649 Discussion Papers SFB649DP2006-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015. "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 273-292.
    2. Shiyi Chen & Kiho Jeong & Wolfgang K. Härdle, 2008. "Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns," SFB 649 Discussion Papers SFB649DP2008-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
    4. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015. "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, vol. 30(3), pages 821-843, September.

  149. Enzo Giacomini & Wolfgang Härdle & Ekaterina Ignatieva & Vladimir Spokoiny, 2006. "Inhomogeneous Dependency Modelling with Time Varying Copulae," SFB 649 Discussion Papers SFB649DP2006-075, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2014. "Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas," SIRE Discussion Papers 2015-25, Scottish Institute for Research in Economics (SIRE).
    2. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Matkovskyy, Roman, 2019. "Centralized and decentralized bitcoin markets: Euro vs USD vs GBP," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 270-279.
    4. Stelios Bekiros & Shawkat Hammoudeh & Rania Jammazi & Duc Khuong Nguyen, 2018. "Sovereign bond market dependencies and crisis transmission around the eurozone debt crisis: a dynamic copula approach," Applied Economics, Taylor & Francis Journals, vol. 50(47), pages 5031-5049, October.
    5. Tian, Maoxi & Ji, Hao, 2022. "GARCH copula quantile regression model for risk spillover analysis," Finance Research Letters, Elsevier, vol. 44(C).
    6. Udichibarna Bose & Ronald MacDonald & Serafeim Tsoukas, 2014. "The role of education in equity portfolios during the recent financial crisis," Working Papers 2014_17, Business School - Economics, University of Glasgow.
    7. Kojadinovic, Ivan & Yan, Jun, 2010. "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i09).
    8. Zongwu Cai & Guannan Liu & Wei Long & Xuelong Luo, 2024. "Semiparametric Conditional Mixture Copula Models with Copula Selection," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202401, University of Kansas, Department of Economics, revised Jan 2024.
    9. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    10. Penikas, Henry, 2014. "Investment portfolio risk modelling based on hierarchical copulas," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 35(3), pages 18-38.
    11. Barbara Choroś-Tomczyk & Wolfgang Karl H�rdle & Ludger Overbeck, 2014. "Copula dynamics in CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1573-1585, September.
    12. Boubaker, Heni & Sghaier, Nadia, 2013. "Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 361-377.
    13. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula," Working Papers 2015_15, Business School - Economics, University of Glasgow.
    14. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    15. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Ostap Okhrin, 2010. "Fitting high-dimensional Copulae to Data," SFB 649 Discussion Papers SFB649DP2010-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Juwon Seo, 2018. "Randomization Tests for Equality in Dependence Structure," Papers 1811.02105, arXiv.org.
    18. Bücher, Axel & Ruppert, Martin, 2013. "Consistent testing for a constant copula under strong mixing based on the tapered block multiplier technique," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 208-229.
    19. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    20. Yang, Bingduo & Hafner, Christian M. & Liu, Guannan & Long, Wei, 2022. "Semiparametric estimation and variable selection for single-index copula models," LIDAM Reprints ISBA 2022011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Giammarino, Flavia & Barrieu, Pauline, 2009. "A semiparametric model for the systematic factors of portfolio credit risk premia," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 655-670, September.
    22. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    23. Muteba Mwamba, John & Mokwena, Paula, 2013. "International diversification and dependence structure of equity portfolios during market crashes: the Archimedean copula approach," MPRA Paper 64384, University Library of Munich, Germany.
    24. Guannan Liu & Wei Long & Bingduo Yang & Zongwu Cai, 2022. "Semiparametric estimation and model selection for conditional mixture copula models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 287-330, March.
    25. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    26. Akanksha Jalan & Roman Matkovskyy & Larisa Yarovaya, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," Post-Print hal-03512893, HAL.
    27. Härdle Wolfgang Karl & Okhrin Ostap & Okhrin Yarema, 2013. "Dynamic structured copula models," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 361-388, December.
    28. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    29. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    30. Syed Abul, Basher & Salem, Nechi & Hui, Zhu, 2014. "Dependence patterns across Gulf Arab stock markets: a copula approach," MPRA Paper 56566, University Library of Munich, Germany.
    31. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    32. Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    33. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    34. Almeida, Carlos & Czado, Claudia, 2012. "Efficient Bayesian inference for stochastic time-varying copula models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1511-1527.
    35. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    36. Wu, Chih-Chiang & Liang, Shin-Shun, 2011. "The economic value of range-based covariance between stock and bond returns with dynamic copulas," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 711-727, September.
    37. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    38. Bing-Yue Liu & Qiang Ji & Ying Fan, 2017. "A new time-varying optimal copula model identifying the dependence across markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 437-453, March.
    39. Okhrin Ostap, 2013. "Editorial to the special issue on Copulae of Statistics & Risk Modeling," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 281-286, December.
    40. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    41. Manner, Hans & Stark, Florian & Wied, Dominik, 2019. "Testing for structural breaks in factor copula models," Journal of Econometrics, Elsevier, vol. 208(2), pages 324-345.
    42. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    43. Pedro Antonio Martín Cervantes & Salvador Cruz Rambaud & María del Carmen Valls Martínez, 2020. "An Application of the SRA Copulas Approach to Price-Volume Research," Mathematics, MDPI, vol. 8(11), pages 1-28, October.
    44. Okhrin, Ostap & Okhrin, Yarema & Schmid, Wolfgang, 2013. "On the structure and estimation of hierarchical Archimedean copulas," Journal of Econometrics, Elsevier, vol. 173(2), pages 189-204.
    45. Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel, 2014. "A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 723-736.
    46. Rémillard, Bruno & Papageorgiou, Nicolas & Soustra, Frédéric, 2012. "Copula-based semiparametric models for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 30-42.
    47. Dedy Dwi Prastyo & Wolfgang Karl Härdle, 2014. "Localising Forward Intensities for Multiperiod Corporate Default," SFB 649 Discussion Papers SFB649DP2014-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  150. Kai Detlefsen & Wolfgang Härdle, 2006. "Calibration Risk for Exotic Options," SFB 649 Discussion Papers SFB649DP2006-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Stahl, Gerhard & Sibbertsen, Philipp & Bertram, Philip, 2011. "Modellrisiko = Spezifikation + Validierung," Hannover Economic Papers (HEP) dp-468, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  151. Ying Chen & Wolfgang Härdle & Vladimir Spokoiny, 2006. "GHICA - Risk Analysis with GH Distributions and Independent Components," SFB 649 Discussion Papers SFB649DP2006-078, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    2. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.

  152. Ralf Brüggemann & Wolfgang Härdle & Julius Mungo & Carsten Trenkler, 2006. "VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings," SFB 649 Discussion Papers SFB649DP2006-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  153. Wolfgang Härdle & Rouslan A. Moro & Dorothea Schäfer, 2005. "Predicting Bankruptcy with Support Vector Machines," SFB 649 Discussion Papers SFB649DP2005-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Shiyi Chen & Kiho Jeong & Wolfgang K. Härdle, 2008. "Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns," SFB 649 Discussion Papers SFB649DP2008-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015. "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, vol. 30(3), pages 821-843, September.
    3. Neuberg Richard & Hannah Lauren, 2017. "Loan pricing under estimation risk," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 69-87, June.
    4. Wei Li & Wolfgang Karl Hardle & Stefan Lessmann, 2022. "A Data-driven Case-based Reasoning in Bankruptcy Prediction," Papers 2211.00921, arXiv.org.
    5. Jurij Weinblat, 2018. "Forecasting European high-growth Firms - A Random Forest Approach," Journal of Industry, Competition and Trade, Springer, vol. 18(3), pages 253-294, September.
    6. Yu, Lean & Yao, Xiao & Zhang, Xiaoming & Yin, Hang & Liu, Jia, 2020. "A novel dual-weighted fuzzy proximal support vector machine with application to credit risk analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    7. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    8. Llano Monelos Pablo De & Piñeiro Sánchez Carlos & Rodríguez López Manuel, 2014. "DEA as a business failure prediction tool. Application to the case of galician SMEs," Contaduría y Administración, Accounting and Management, vol. 59(2), pages 65-96, abril-jun.
    9. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.

  154. Wolfgang Härdle & Heiko Lehmann, 2005. "Working with the XQC," SFB 649 Discussion Papers SFB649DP2005-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2005. "Integrable e-lements for Statistics Education," SFB 649 Discussion Papers SFB649DP2005-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2006. "e-Learning Statistics - A Selective Review," SFB 649 Discussion Papers SFB649DP2006-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  155. Szymon Borak & Wolfgang Härdle & Rafal Weron, 2005. "Stable Distributions," SFB 649 Discussion Papers SFB649DP2005-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Jozef Barunik & Lukas Vacha, 2012. "Monte Carlo-based tail exponent estimator," Papers 1201.4781, arXiv.org.
    2. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    3. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    4. Annika Krutto, 2016. "Parameter Estimation in Stable Law," Risks, MDPI, vol. 4(4), pages 1-15, November.
    5. Edoardo Gaffeo & Antonello E. Scorcu & Laura Vici, 2008. "Demand Distribution Dynamics in Creative Industries: the Market for Books in Italy," Working Paper series 09_08, Rimini Centre for Economic Analysis.
    6. Kenneth Bruninx & Erik Delarue & William D'haeseleer, 2013. "Statistical description of the error on wind power forecasts via a Lévy α-stable distribution," RSCAS Working Papers 2013/50, European University Institute.
    7. José Antonio Climent Hernández & Luis Fernando Hoyos Reyes & Domingo Rodríguez Benavides, 2017. "The a-stable processes and their relationship with theexponent of self-similarity: Exchange rates of USADollar, Canadian Dollar, Euro and Yen," Contaduría y Administración, Accounting and Management, vol. 62(5), pages 11-12, Diciembre.
    8. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    9. Dufour, Jean-Marie & Kurz-Kim, Jeong-Ryeol, 2010. "Exact inference and optimal invariant estimation for the stability parameter of symmetric [alpha]-stable distributions," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 180-194, March.
    10. Jozef Barunik & Ladislav Kristoufek, 2012. "On Hurst exponent estimation under heavy-tailed distributions," Papers 1201.4786, arXiv.org.
    11. José Antonio Climent Hernández & Carolina Cruz Matú, 2017. "Pricing of a structured product on the SX5E when the uncertainty of returns is modeled as a log-stable process," Contaduría y Administración, Accounting and Management, vol. 62(4), pages 1160-1182, Octubre-D.
    12. Brahimi, Brahim & Abdelli, Jihane, 2016. "Estimating the distortion parameter of the proportional hazards premium for heavy-tailed losses under Lévy-stable regime," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 135-143.
    13. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    14. José Antonio Climent Hernández & Luis Fernando Hoyos Reyes & Domingo Rodríguez Benavides, 2017. "Los procesos alfa estables y su relación con el exponentede autosimilitud: paridades de los tipos de cambio dólarestadounidense, dólar canadiense, euro y yen," Contaduría y Administración, Accounting and Management, vol. 62(5), pages 9-10, Diciembre.
    15. Ece Oral, 2013. "Consumer Inflation Expectations in Turkey," IFC Working Papers 10, Bank for International Settlements.
    16. José Antonio Climent Hernández & Carolina Cruz Matú, 2017. "Valuación de un producto estructurado de compra sobre el SX5E cuando la incertidumbre de los rendimientos está modelada con procesos log-estables," Contaduría y Administración, Accounting and Management, vol. 62(4), pages 1136-1159, Octubre-D.
    17. Raul Matsushita & Iram Gleria & Annibal Figueiredo & Sergio Da Silva, 2004. "The Econophysics of the Brazilian Real-US Dollar Rate," Finance 0407012, University Library of Munich, Germany.
    18. Fajardo, J., 2004. "Equivalent Martingale Measures and Lévy Processes," Finance Lab Working Papers flwp_61, Finance Lab, Insper Instituto de Ensino e Pesquisa.
    19. Weron, Rafał, 2004. "Computationally intensive Value at Risk calculations," Papers 2004,32, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    20. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
    21. Figueiredo, Annibal & Gleria, Iram & Matsushita, Raul & Da Silva, Sergio, 2005. "Financial volatility and independent and identically distributed variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 484-498.
    22. Sandro Sapio, 2009. "Modelling the distribution of day-ahead electricity returns: a comparison," LEM Papers Series 2009/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    23. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    24. Daniel Traian Pele & Vasile Nicolae Stanciulescu, 2015. "On a Class of Alpha-stable Distributions and Its Applications in Estimating Market Risk," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 7(2), pages 007-015, December.
    25. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2020. "Market-crash forecasting based on the dynamics of the alpha-stable distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    26. Sebastian, Orzeł & Agnieszka, Wyłomańska, 2010. "Calibration of the subdiffusive arithmetic Brownian motion with tempered stable waiting-times," MPRA Paper 28593, University Library of Munich, Germany.
    27. Yuan Hu & Svetlozar T. Rachev & Frank J. Fabozzi, 2019. "Modelling Crypto Asset Price Dynamics, Optimal Crypto Portfolio, and Crypto Option Valuation," Papers 1908.05419, arXiv.org.
    28. Taleb, Nassim Nicholas, 2009. "Errors, robustness, and the fourth quadrant," International Journal of Forecasting, Elsevier, vol. 25(4), pages 744-759, October.
    29. Nassim N. Taleb, 2012. "How We Tend To Overestimate Powerlaw Tail Exponents," Papers 1210.1966, arXiv.org.
    30. Ece Oral, 2016. "Measuring Consumer Inflation Expectations in Turkey," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 2(1), pages 43-74.
    31. Dominik Krezolek, 2012. "Non-Classical Measures of Investment Risk on the Market of Precious Non-Ferrous Metals Using the Methodology of Stable Distributions," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 89-104.
    32. Serttas, Fatma Ozgu, 2010. "Essays on infinite-variance stable errors and robust estimation procedures," ISU General Staff Papers 201001010800002742, Iowa State University, Department of Economics.
    33. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    34. Sigbert Klinke & Uwe Ziegenhagen & Yuval Guri, 2005. "Yxilon – a Modular Open-Source Statistical Programming Language," SFB 649 Discussion Papers SFB649DP2005-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Sebastian J. Goerg & Johannes Kaiser, 2009. "Nonparametric testing of distributions—the Epps–Singleton two-sample test using the empirical characteristic function," Stata Journal, StataCorp LP, vol. 9(3), pages 454-465, September.

  156. Wolfgang Härdle & Seok-Oh Jeong, 2005. "Nonparametric Productivity Analysis," SFB 649 Discussion Papers SFB649DP2005-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Jugal Mahabir, 2014. "Quantifying Inefficient Expenditure in Local Government: A Free Disposable Hull Analysis of a Sample of South African Municipalities," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 493-517, December.

  157. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Ralf Brüggemann & Wolfgang Härdle & Julius Mungo & Carsten Trenkler, 2006. "VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings," SFB 649 Discussion Papers SFB649DP2006-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  158. Cizek, P. & Härdle, W.K., 2005. "Robust Estimation of Dimension Reduction Space," Discussion Paper 2005-31, Tilburg University, Center for Economic Research.

    Cited by:

    1. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    2. Yao, Weixin & Wang, Qin, 2013. "Robust variable selection through MAVE," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 42-49.
    3. Wang, Qin & Yao, Weixin, 2012. "An adaptive estimation of MAVE," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 88-100, February.
    4. Bura, E. & Yang, J., 2011. "Dimension estimation in sufficient dimension reduction: A unifying approach," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 130-142, January.
    5. Zhou, Jingke & Xu, Wangli & Zhu, Lixing, 2015. "Robust estimating equation-based sufficient dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 99-118.

  159. Ying Chen & Wolfgang Härdle & Vladimir Spokoiny, 2005. "Portfolio Value at Risk Based on Independent Components Analysis," SFB 649 Discussion Papers SFB649DP2005-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Kritski, Oleg & Ulyanova, Marina, 2007. "Assessment of Multivariate Financial Risks of a Stock Share Portfolio," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 3-17.

  160. Wolfgang Härdle & Zdenek Hlavka, 2005. "Dynamics of State Price Densities," SFB 649 Discussion Papers SFB649DP2005-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Hans Buehler, 2006. "Expensive martingales," Quantitative Finance, Taylor & Francis Journals, vol. 6(3), pages 207-218.
    2. Matthias R. Fengler, 2005. "Arbitrage-Free Smoothing of the Implied Volatility Surface," SFB 649 Discussion Papers SFB649DP2005-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  161. Michal Benko & Wolfgang Härdle, 2005. "Common Functional Implied Volatility Analysis," SFB 649 Discussion Papers SFB649DP2005-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    2. Bali, Juan Lucas & Boente, Graciela, 2017. "Robust estimators under a functional common principal components model," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 424-440.
    3. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  162. Szymon Borak & Kai Detlefsen & Wolfgang Härdle, 2005. "FFT Based Option Pricing," SFB 649 Discussion Papers SFB649DP2005-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Srikanth Iyer & Seema Nanda & Swapnil Kumar, 2013. "An Empirical Comparison of Two Stochastic Volatility Models using Indian Market Data," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 20(3), pages 243-259, September.
    2. A S Hurn & Kenenth A Lindsay & Andrew McClelland, 2013. "On the Efficacy of Fourier Series Approximations for Pricing European and Digital Options," NCER Working Paper Series 90, National Centre for Econometric Research.
    3. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Horacio Alberto Ruiz Olvera, 2011. "Valuación de opciones europeas mediante procesos de Lévy exponenciales y transformada rápida de Fourier," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 6(2), pages 16-33.
    5. Chen, Ying & Härdle, Wolfgang & Spokoiny, Vladimir, 2010. "GHICA -- Risk analysis with GH distributions and independent components," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 255-269, March.
    6. Emmanuel Hanert & Aanand Venkatramanan, 2008. "Meshfree Approximation for Multi-Asset Options," ICMA Centre Discussion Papers in Finance icma-dp2009-07, Henley Business School, University of Reading, revised Jun 2009.
    7. Sigbert Klinke & Uwe Ziegenhagen & Yuval Guri, 2005. "Yxilon – a Modular Open-Source Statistical Programming Language," SFB 649 Discussion Papers SFB649DP2005-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  163. Enzo Giacomini & Wolfgang Härdle, 2005. "Value-at-Risk Calculations with Time Varying Copulae," SFB 649 Discussion Papers SFB649DP2005-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Xu, Wei & Filler, Gunther & Odening, Martin & Okhrin, Ostap, 2009. "On the Systemic Nature of Weather Risk," 2009 Conference, August 16-22, 2009, Beijing, China 51426, International Association of Agricultural Economists.
    2. Enzo Giacomini & Wolfgang Härdle & Ekaterina Ignatieva & Vladimir Spokoiny, 2006. "Inhomogeneous Dependency Modelling with Time Varying Copulae," SFB 649 Discussion Papers SFB649DP2006-075, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Giovanni De Luca & Giorgia Rivieccio, 2009. "Archimedean copulae for risk measurement," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(8), pages 907-924.
    4. Bhatti, M. Ishaq & Nguyen, Cuong C., 2012. "Diversification evidence from international equity markets using extreme values and stochastic copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 622-646.
    5. Sigbert Klinke & Uwe Ziegenhagen & Yuval Guri, 2005. "Yxilon – a Modular Open-Source Statistical Programming Language," SFB 649 Discussion Papers SFB649DP2005-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  164. Matthias Fengler & Wolfgang Härdle & Enno Mammen, 2005. "A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics," SFB 649 Discussion Papers SFB649DP2005-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Michal Benko & Wolfgang Härdle & Alois Kneip, 2006. "Common Functional Principal Components," SFB 649 Discussion Papers SFB649DP2006-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Ralf Brüggemann & Wolfgang Härdle & Julius Mungo & Carsten Trenkler, 2006. "VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings," SFB 649 Discussion Papers SFB649DP2006-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Lam, Clifford & Yao, Qiwei & Bathia, Neil, 2011. "Estimation of latent factors for high-dimensional time series," LSE Research Online Documents on Economics 31549, London School of Economics and Political Science, LSE Library.
    4. Härdle, Wolfgang & Hlávka, Zdenek, 2009. "Dynamics of state price densities," Journal of Econometrics, Elsevier, vol. 150(1), pages 1-15, May.
    5. Liu, Xialu & Xiao, Han & Chen, Rong, 2016. "Convolutional autoregressive models for functional time series," Journal of Econometrics, Elsevier, vol. 194(2), pages 263-282.
    6. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    7. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  165. Wolfgang K. Härdle & Rouslan A. Moro & Dorothea Schäfer, 2004. "Rating Companies with Support Vector Machines," Discussion Papers of DIW Berlin 416, DIW Berlin, German Institute for Economic Research.

    Cited by:

    1. Laura Auria & Rouslan A. Moro, 2008. "Support Vector Machines (SVM) as a Technique for Solvency Analysis," Discussion Papers of DIW Berlin 811, DIW Berlin, German Institute for Economic Research.
    2. Prusak Błażej, 2019. "Corporate Bankruptcy Prediction in Poland Against the Background of Foreign Experience," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 15(1), pages 10-19, March.
    3. Błażej Prusak, 2018. "Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries," IJFS, MDPI, vol. 6(3), pages 1-28, June.

  166. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. Katarzyna Kopczewska, 2014. "L-moments skewness and kurtosis as measures of regional convergence and cohesion," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 251-266, November.
    2. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
    3. Huimin Zhao & Jin E. Zhang & Eric C. Chang, 2013. "The Relation between Physical and Risk-neutral Cumulants," International Review of Finance, International Review of Finance Ltd., vol. 13(3), pages 345-381, September.
    4. silvia Muzzioli & Alessio Ruggieri, 2013. "Option Implied Trees and Implied Moments," Department of Economics (DEMB) 0015, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".
    5. Julian Winkel & Wolfgang Karl Härdle, 2023. "Pricing Kernels and Risk Premia implied in Bitcoin Options," Risks, MDPI, vol. 11(5), pages 1-18, April.
    6. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  167. Härdle, Wolfgang Karl & Burnecki, Krzysztof & Weron, Rafał, 2004. "Simulation of risk processes," Papers 2004,01, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. Rafal Weron & Michael Bierbrauer & Stefan Trück, 2003. "Modeling electricity prices: jump diffusion and regime switching," HSC Research Reports HSC/03/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    2. Burnecki, Krzysztof & Weron, Rafal, 2010. "Simulation of Risk Processes," MPRA Paper 25444, University Library of Munich, Germany.
      • Härdle, Wolfgang Karl & Burnecki, Krzysztof & Weron, Rafał, 2004. "Simulation of risk processes," Papers 2004,01, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    3. Krzysztof Burnecki & Rafal Weron, 2006. "Visualization tools for insurance risk processes," HSC Research Reports HSC/06/06, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    5. Weron, Rafał & Burnecki, Krzysztof, 2004. "Modeling the risk process in the XploRe computing environment," Papers 2004,08, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    6. Krzysztof Burnecki & Joanna Janczura & Rafał Weron, 2010. "Building Loss Models," SFB 649 Discussion Papers SFB649DP2010-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. A. Christian Silva & Ju-Yi Yen, 2010. "Stochastic resonance and the trade arrival rate of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 461-466.
    8. Anna Chernobai & Krzysztof Burnecki & Svetlozar Rachev & Stefan Trueck & Rafal Weron, 2005. "Modeling catastrophe claims with left-truncated severity distributions (extended version)," HSC Research Reports HSC/05/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    9. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    10. Burnecki, Krzysztof & Misiorek, Adam & Weron, Rafal, 2010. "Loss Distributions," MPRA Paper 22163, University Library of Munich, Germany.
    11. Wolfgang Härdle & Brenda López Cabrera, 2007. "Calibrating CAT bonds for Mexican earthquakes," SFB 649 Discussion Papers SFB649DP2007-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  168. Krzysztof Burnecki & Wolfgang Hardle & Rafal Weron, 2003. "An introduction to simulation of risk processes," HSC Research Reports HSC/03/04, Hugo Steinhaus Center, Wroclaw University of Technology.

    Cited by:

    1. Weron, Rafał & Burnecki, Krzysztof, 2004. "Modeling the risk process in the XploRe computing environment," Papers 2004,08, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    2. Anna Chernobai & Krzysztof Burnecki & Svetlozar Rachev & Stefan Trueck & Rafal Weron, 2005. "Modeling catastrophe claims with left-truncated severity distributions (extended version)," HSC Research Reports HSC/05/01, Hugo Steinhaus Center, Wroclaw University of Technology.

  169. Kirman, Alan & Wolfgang Hardle & Rainer Schulz & Axel Werwatz, 2003. "Transactions That Did Not Happen and Their Influence on Prices," Royal Economic Society Annual Conference 2003 123, Royal Economic Society.

    Cited by:

    1. Alan Kirman & Sonia Moulet & Rainer Schulz, 2008. "Price Discrimination and Customer Behaviour: Empirical Evidence from Marseille," Working Papers halshs-00349036, HAL.
    2. Moulet, Sonia & Rouchier, Juliette, 2008. "The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2322-2348, July.
    3. Joshua Sherman & Avi Weiss, 2015. "Price Response, Asymmetric Information and Competition," Economic Journal, Royal Economic Society, vol. 125(589), pages 2077-2115, December.
    4. Eric Guerci & Alan Kirman & Sonia Moulet, 2014. "Learning to bid in sequential Dutch Auctions," Post-Print halshs-01069634, HAL.
    5. Alan Kirman & Sonia Moulet, 2008. "Impact de l'organisation du marché: Comparaison de la négociation de gré à gré et des enchères descendantes," Working Papers halshs-00349034, HAL.
    6. Franck Galtier & François Bousquet & Martine Antona & Pierre Bommel, 2012. "Markets as communication systems," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 161-201, January.
    7. Juliette Rouchier, 2013. "The Interest of Having Loyal Buyers in a Perishable Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 151-170, February.
    8. Giulioni, Gianfranco & Bucciarelli, Edgardo, 2011. "Agents’ ability to manage information in centralized markets: Comparing two wholesale fish markets," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 34-49.

  170. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, vol. 6(3), pages 179-202, October.
    2. Enno Mammen & Byeong U. Park & Melanie Schienle, 2012. "Additive Models: Extensions and Related Models," SFB 649 Discussion Papers SFB649DP2012-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Damiano Brigo & Francesco Rapisarda & Abir Sridi, 2013. "The arbitrage-free Multivariate Mixture Dynamics Model: Consistent single-assets and index volatility smiles," Papers 1302.7010, arXiv.org, revised Sep 2014.
    4. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," Papers 1106.3915, arXiv.org.
    5. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    6. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    9. Hans Buehler, 2006. "Consistent Variance Curve Models," Finance and Stochastics, Springer, vol. 10(2), pages 178-203, April.
    10. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2010. "High Dimensional Nonstationary Time Series Modelling with Generalized Dynamic Semiparametric Factor Model," SFB 649 Discussion Papers SFB649DP2010-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Borak, Szymon & Weron, Rafal, 2008. "A semiparametric factor model for electricity forward curve dynamics," MPRA Paper 10421, University Library of Munich, Germany.
    13. Michal Benko & Alois Kneip, 2005. "Common functional component modelling," SFB 649 Discussion Papers SFB649DP2005-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. M. Benko & M. Fengler & W. Härdle & M. Kopa, 2007. "On extracting information implied in options," Computational Statistics, Springer, vol. 22(4), pages 543-553, December.
    15. Bo Zhao & Stewart Hodges, 2013. "Parametric modeling of implied smile functions: a generalized SVI model," Review of Derivatives Research, Springer, vol. 16(1), pages 53-77, April.
    16. Bernd Engelmann & Matthias Fengler & Morten Nalholm & Peter Schwendner, 2006. "Static versus dynamic hedges: an empirical comparison for barrier options," Review of Derivatives Research, Springer, vol. 9(3), pages 239-264, November.
    17. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Denis Belomestny & Markus Reiß, 2006. "Spectral calibration of exponential Lévy models," Finance and Stochastics, Springer, vol. 10(4), pages 449-474, December.
    19. Enzo Giacomini & Wolfgang Härdle, 2007. "Statistics of Risk Aversion," SFB 649 Discussion Papers SFB649DP2007-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Hans Buehler, 2006. "Consistent Variance Curve Models," Finance and Stochastics, Springer, vol. 10(2), pages 178-203, April.
    21. René Carmona & Sergey Nadtochiy, 2009. "Local volatility dynamic models," Finance and Stochastics, Springer, vol. 13(1), pages 1-48, January.
    22. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    23. Matthias R. Fengler, 2005. "Arbitrage-Free Smoothing of the Implied Volatility Surface," SFB 649 Discussion Papers SFB649DP2005-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Wolfgang Karl Härdle & Elena Silyakova, 2012. "Implied Basket Correlation Dynamics," SFB 649 Discussion Papers SFB649DP2012-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Wolfgang Härdle & Zdenek Hlavka, 2005. "Dynamics of State Price Densities," SFB 649 Discussion Papers SFB649DP2005-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Wallmeier, Martin, 2012. "Smile in Motion: An Intraday Analysis of Asymmetric Implied Volatility," FSES Working Papers 427, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    27. Maria Grith & Wolfgang Karl Härdle & Melanie Schienle, 2010. "Nonparametric Estimation of Risk-Neutral Densities," SFB 649 Discussion Papers SFB649DP2010-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  171. Härdle, Wolfgang & Zheng, Jun, 2002. "How precise are price distributions predicted by implied binomial trees?," SFB 373 Discussion Papers 2002,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

  172. Wang, Qihua & Härdle, Wolfgang, 2002. "Empirical likelihood-based dimension reduction inference for linear error-in-responses models with validation study," SFB 373 Discussion Papers 2002,82, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Yang, Yiping & Li, Gaorong & Peng, Heng, 2014. "Empirical likelihood of varying coefficient errors-in-variables models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 1-18.
    2. Gengsheng Qin & Xiao-Hua Zhou, 2006. "Empirical Likelihood Inference for the Area under the ROC Curve," Biometrics, The International Biometric Society, vol. 62(2), pages 613-622, June.
    3. Xuemei Hu & Xiaohui Liu, 2013. "Empirical likelihood confidence regions for semi-varying coefficient models with linear process errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(1), pages 161-180, March.
    4. Wang, Qihua & Yu, Keming, 2007. "Likelihood-based kernel estimation in semiparametric errors-in-covariables models with validation data," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 455-480, March.

  173. Xia, Yingcun & Härdle, Wolfgang, 2002. "Semi-parametric estimation of generalized partially linear single-index models," SFB 373 Discussion Papers 2002,56, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    2. Aboura, Sofiane & Wagner, Niklas, 2016. "Extreme asymmetric volatility: Stress and aggregate asset prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 47-59.
    3. Tanha, Hassan & Dempsey, Michael, 2015. "The asymmetric response of volatility to market changes and the volatility smile: Evidence from Australian options," Research in International Business and Finance, Elsevier, vol. 34(C), pages 164-176.
    4. Ormos, Mihály & Timotity, Dusan, 2016. "Unravelling the asymmetric volatility puzzle: A novel explanation of volatility through anchoring," Economic Systems, Elsevier, vol. 40(3), pages 345-354.
    5. Michel Delecroix & Marian Hristache & Valentin Patilea, 2004. "On Semiparametric estimation in Single-Index Regression," Working Papers 2004-17, Center for Research in Economics and Statistics.
    6. Bugge, Sebastian A. & Guttormsen, Haakon J. & Molnár, Peter & Ringdal, Martin, 2016. "Implied volatility index for the Norwegian equity market," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 133-141.

  174. Yang, Lijian & Härdle, Wolfgang & Park, Byeong U., 2002. "Estimation and testing for varying coefficients in additive models with marginal integration," SFB 373 Discussion Papers 2002,75, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Lee, Kyeongeun & Lee, Young K. & Park, Byeong U. & Yang, Seong J., 2018. "Time-dynamic varying coefficient models for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 50-65.
    2. Song, Qiongxia & Yang, Lijian, 2010. "Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2008-2025, October.
    3. Enno Mammen & Byeong U. Park & Melanie Schienle, 2012. "Additive Models: Extensions and Related Models," SFB 649 Discussion Papers SFB649DP2012-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Olga Klopp & Marianna Pensky, 2013. "Sparse High-dimensional Varying Coefficient Model : Non-asymptotic Minimax Study," Working Papers 2013-30, Center for Research in Economics and Statistics.
    6. Miao Yang & Lan Xue & Lijian Yang, 2016. "Variable selection for additive model via cumulative ratios of empirical strengths total," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 595-616, September.
    7. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    8. Yang, Seong J. & Park, Byeong U., 2014. "Efficient estimation for partially linear varying coefficient models when coefficient functions have different smoothing variables," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 100-113.
    9. Xialu Liu & Zongwu Cai & Rong Chen, 2015. "Functional coefficient seasonal time series models with an application of Hawaii tourism data," Computational Statistics, Springer, vol. 30(3), pages 719-744, September.
    10. Lv, Shaogao & Fan, Zengyan & Lian, Heng & Suzuki, Taiji & Fukumizu, Kenji, 2020. "A reproducing kernel Hilbert space approach to high dimensional partially varying coefficient model," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    11. Rui Li & Yuanyuan Zhang, 2021. "Two-stage estimation and simultaneous confidence band in partially nonlinear additive model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(8), pages 1109-1140, November.
    12. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    13. Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
    14. Stefan Sperlich & Raoul Theler, 2015. "Modeling heterogeneity: a praise for varying-coefficient models in causal analysis," Computational Statistics, Springer, vol. 30(3), pages 693-718, September.
    15. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    16. Byeong U. Park & Enno Mammen & Young K. Lee & Eun Ryung Lee, 2015. "Varying Coefficient Regression Models: A Review and New Developments," International Statistical Review, International Statistical Institute, vol. 83(1), pages 36-64, April.
    17. Han, Kyunghee & Lee, Young K. & Park, Byeong U., 2020. "Smooth backfitting for errors-in-variables varying coefficient regression models," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    18. Wang, Taining & Henderson, Daniel J., 2022. "Estimation of a varying coefficient, fixed-effects Cobb–Douglas production function in levels," Economics Letters, Elsevier, vol. 213(C).

  175. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.

    Cited by:

    1. Wu, Ximing & Sickles, Robin, 2018. "Semiparametric estimation under shape constraints," Econometrics and Statistics, Elsevier, vol. 6(C), pages 74-89.
    2. Peter Hall & Joel L. Horowitz, 2013. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers CWP29/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
    4. Peter Pütz & Thomas Kneib, 2018. "A penalized spline estimator for fixed effects panel data models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 145-166, April.
    5. Roca-Pardinas, Javier & Cadarso-Suarez, Carmen & Tahoces, Pablo G. & Lado, Maria J., 2008. "Assessing continuous bivariate effects among different groups through nonparametric regression models: An application to breast cancer detection," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1958-1970, January.
    6. Roca-Pardinas, Javier & Sperlich, Stefan, 2007. "Testing the link when the index is semiparametric--a comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6565-6581, August.
    7. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Suneel Babu Chatla, 2023. "Nonparametric inference for additive models estimated via simplified smooth backfitting," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(1), pages 71-97, February.
    9. Bellemare, C. & Melenberg, B. & van Soest, A.H.O., 2002. "Semi-parametric Models for Satisfaction with Income," Other publications TiSEM a7ab8987-444a-4ab0-b566-c, Tilburg University, School of Economics and Management.
    10. de Uña Álvarez, Jacobo & Roca Pardiñas, Javier, 2009. "Additive models in censored regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3490-3501, July.
    11. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    12. Xu Guo & Tao Wang & Lixing Zhu, 2016. "Model checking for parametric single-index models: a dimension reduction model-adaptive approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 1013-1035, November.
    13. Krebs, Johannes & Rademacher, Daniel & von Sachs, Rainer, 2022. "Statistical inference for intrinsic wavelet estimators of SPD covariance matrices in a log-Euclidean manifold," LIDAM Discussion Papers ISBA 2022004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Gregory Connor & Thomas Flavin, 2013. "Irish Mortgage Default Optionality," Economics Department Working Paper Series n243-13.pdf, Department of Economics, National University of Ireland - Maynooth.
    15. Yu, Zhuoxi & Yang, Kai & Parmar, Milan, 2018. "Empirical likelihood based inference for generalized additive partial linear models," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 105-112.
    16. Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(I), pages 49-80, March.
    17. Krishna Pendakur & Stefan Sperlich, 2010. "Semiparametric estimation of consumer demand systems in real expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 420-457.
    18. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and Predicting Household Expenditures and Income Distributions," MAGKS Papers on Economics 201147, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    19. Joel L. Horowitz & Anand Krishnamurthy, 2017. "A bootstrap method for constructing pointwise and uniform confidence bands for conditional quantile functions," CeMMAP working papers CWP01/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Stefan Sperlich, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 419-427, September.
    21. Enno Mammen, 2007. "Comments on: Nonparametric inference with generalized likelihood ratio tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(3), pages 462-464, December.
    22. Peter Hall & Joel L. Horowitz, 2013. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers 29/13, Institute for Fiscal Studies.
    23. Li, Rui & Wan, Alan T.K. & You, Jinhong, 2016. "Semiparametric GMM estimation and variable selection in dynamic panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 401-423.
    24. María José Lombardía & Stefan Sperlich, 2008. "Semiparametric inference in generalized mixed effects models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 913-930, November.
    25. Yang, Jing & Yang, Hu, 2016. "A robust penalized estimation for identification in semiparametric additive models," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 268-277.
    26. Jing Yang & Hu Yang & Fang Lu, 2019. "Rank-based shrinkage estimation for identification in semiparametric additive models," Statistical Papers, Springer, vol. 60(4), pages 1255-1281, August.
    27. Charles Bellemare & Bertrand Melenberg & Arthur van Soest van Soest, 2002. "Semi-parametric models for satisfaction with income," CeMMAP working papers 12/02, Institute for Fiscal Studies.
    28. Joel L. Horowitz & Anand Krishnamurthy, 2017. "A bootstrap method for constructing pointwise and uniform confidence bands for conditional quantile functions," CeMMAP working papers 01/17, Institute for Fiscal Studies.
    29. Jing Wang, 2012. "Modelling time trend via spline confidence band," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 275-301, April.
    30. Rui Li & Chenlei Leng & Jinhong You, 2017. "A Semiparametric Regression Model for Longitudinal Data with Non-stationary Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 932-950, December.

  176. Fengler, Matthias R. & Härdle, Wolfgang & Schmidt, Peter, 2001. "The analysis of implied volatilities," SFB 373 Discussion Papers 2001,73, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Fengler, Matthias R. & Wang, Qihua, 2003. "Fitting the Smile Revisited: A Least Squares Kernel Estimator for the Implied Volatility Surface," SFB 373 Discussion Papers 2003,25, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Härdle, Wolfgang & Schmidt, Peter, 2000. "Common factors governing VDAX movements and the maximum loss," SFB 373 Discussion Papers 2000,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  177. Wolfgang Hardle & Torsten Kleinow & Alexander Korostelev & Camille Logeay & Eckhard Platen, 2001. "Semiparametric Diffusion Estimation and Application to a Stock Market Index," Research Paper Series 51, Quantitative Finance Research Centre, University of Technology, Sydney.

    Cited by:

    1. Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Liu, Hsing & Liao, Chi-Yo & Ko, Jing-Yuan & Lih, Jiann-Shing, 2017. "Anchoring effect on first passage process in Taiwan financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 114-127.
    3. Wolfgang Härdle & Joel Horowitz & Jens‐Peter Kreiss, 2003. "Bootstrap Methods for Time Series," International Statistical Review, International Statistical Institute, vol. 71(2), pages 435-459, August.

  178. Yang, Lijian & Sperlich, Stefan & Hardle, Wolfgang, 2000. "Derivative estimation and testing in generalized additive models," DES - Working Papers. Statistics and Econometrics. WS 10084, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  179. Chen, Song Xi & Härdle, Wolfgang & Kleinow, Torsten, 2000. "An empirical likelihood goodness-of-fit test for time series," SFB 373 Discussion Papers 2001,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chen, Song Xi & Gao, Jiti, 2007. "An adaptive empirical likelihood test for parametric time series regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 950-972, December.
    2. Peter Hall & Joel L. Horowitz, 2013. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers CWP29/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics and Public Policy Working Papers 2010-28, University of Adelaide, School of Economics and Public Policy.
    4. Nikolay Gospodinov & Taisuke Otsu, 2008. "Local GMM Estimation of Time Series Models with Conditional Moment Restrictions," Working Papers 08010, Concordia University, Department of Economics.
    5. Su, Liangjun & White, Halbert, 2014. "Testing conditional independence via empirical likelihood," Journal of Econometrics, Elsevier, vol. 182(1), pages 27-44.
    6. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    7. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
    8. Manuel Vega-Gordillo & José Luis à lvarez-Arce, 2005. "Heterogeneity In Economic Freedom: Free Clusters Or Free Countries," Faculty Working Papers 08/05, School of Economics and Business Administration, University of Navarra.
    9. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    10. Gao, Jiti & Gijbels, Irene, 2005. "Bandwidth selection for nonparametric kernel testing," MPRA Paper 11982, University Library of Munich, Germany, revised Jun 2007.
    11. Li, Ming & Li, Jia-Yue, 2017. "Generalized Cauchy model of sea level fluctuations with long-range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 309-335.
    12. Manuel Arapis & Jiti Gao, 2006. "Empirical Comparisons in Short-Term Interest Rate Models Using Nonparametric Methods," Journal of Financial Econometrics, Oxford University Press, vol. 4(2), pages 310-345.
    13. Juan Carlos Escanciano, 2004. "Model Checks Using Residual Marked Empirical Processes," Faculty Working Papers 13/04, School of Economics and Business Administration, University of Navarra.
    14. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    15. Escanciano, J. Carlos, 2006. "A Consistent Diagnostic Test For Regression Models Using Projections," Econometric Theory, Cambridge University Press, vol. 22(6), pages 1030-1051, December.
    16. Davit Varron & Ingrid Van Keilegom, 2011. "Uniform in bandwidth exact rates for a class of kernel estimators," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(6), pages 1077-1102, December.
    17. Joel L. Horowitz & Anand Krishnamurthy, 2017. "A bootstrap method for constructing pointwise and uniform confidence bands for conditional quantile functions," CeMMAP working papers CWP01/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Wang-Li Xu & Li-Xing Zhu, 2008. "Goodness-of-fit testing for varying-coefficient models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(2), pages 129-146, September.
    19. Carlos Velasco, 2009. "Comments on: A review on empirical likelihood methods for regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(3), pages 455-457, November.
    20. YABE, Ryota & 矢部, 竜太, 2014. "Empirical Likelihood Confidence Intervals for Nonparametric Nonlinear Nonstationary Regression Models," Discussion Papers 2014-20, Graduate School of Economics, Hitotsubashi University.
    21. Peter Hall & Joel L. Horowitz, 2013. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers 29/13, Institute for Fiscal Studies.
    22. Chen, Songxi & Peng, Liang & Yu, Cindy, 2013. "Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions," MPRA Paper 46273, University Library of Munich, Germany.
    23. Perera, Indeewara & Silvapulle, Mervyn J., 2023. "Bootstrap specification tests for dynamic conditional distribution models," Journal of Econometrics, Elsevier, vol. 235(2), pages 949-971.
    24. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    25. Hong, Yongmiao & Li, Haitao, 2002. "Nonparametric specification testing for continuous-time models with application to spot interest rates," SFB 373 Discussion Papers 2002,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    26. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    27. Joel L. Horowitz & Anand Krishnamurthy, 2017. "A bootstrap method for constructing pointwise and uniform confidence bands for conditional quantile functions," CeMMAP working papers 01/17, Institute for Fiscal Studies.
    28. Cai, Zongwu & Hong, Yongmiao, 2003. "Nonparametric Methods in Continuous-Time Finance: A Selective Review," SFB 373 Discussion Papers 2003,15, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    29. Shuzhi Zhu & Peixin Zhao, 2019. "Tests for the linear hypothesis in semi-functional partial linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(2), pages 125-148, March.

  180. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.

    Cited by:

    1. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
    2. Guozhi Hu & Weihu Cheng & Jie Zeng, 2023. "Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    3. A. Delaigle & P. Hall & J. R. Wishart, 2014. "New approaches to nonparametric and semiparametric regression for univariate and multivariate group testing data," Biometrika, Biometrika Trust, vol. 101(3), pages 567-585.
    4. Daniel Becker & Alois Kneip & Valentin Patilea, 2021. "Semiparametric inference for partially linear regressions with Box-Cox transformation," Papers 2106.10723, arXiv.org.
    5. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Przystalski, Marcin, 2014. "Estimation of the covariance matrix in multivariate partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 380-385.
    7. Lan, Wei & Ding, Yue & Fang, Zheng & Fang, Kuangnan, 2016. "Testing covariates in high dimension linear regression with latent factors," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 25-37.
    8. Marcelo M. Taddeo & Pedro A. Morettin, 2023. "Bayesian P-Splines Applied to Semiparametric Models with Errors Following a Scale Mixture of Normals," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1331-1355, August.
    9. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    10. Esra Akdeniz Duran & Wolfgang Karl Härdle & Maria Osipenko, 2011. "Difference based Ridge and Liu type Estimators in Semiparametric Regression Models," SFB 649 Discussion Papers SFB649DP2011-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Florens, Jean-Pierre & Johannes, Jan & Van Bellegem, Sébastien, 2009. "Instrumental Regression in Partially Linear Models," TSE Working Papers 10-167, Toulouse School of Economics (TSE).
    12. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    13. Lai, Peng & Wang, Qihua, 2014. "Semiparametric efficient estimation for partially linear single-index models with responses missing at random," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 33-50.
    14. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Estimation in semiparametric spatial regression," MPRA Paper 11979, University Library of Munich, Germany, revised Jul 2005.
    15. Chen, Xiaohong & Liao, Zhipeng & Sun, Yixiao, 2014. "Sieve inference on possibly misspecified semi-nonparametric time series models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 639-658.
    16. Germán Aneiros & Nengxiang Ling & Philippe Vieu, 2015. "Error variance estimation in semi-functional partially linear regression models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(3), pages 316-330, September.
    17. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    18. Roozbeh, Mahdi, 2015. "Shrinkage ridge estimators in semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 56-74.
    19. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
    21. Gao, Jiti & Anh, Vo & Heyde, Chris, 2002. "Statistical estimation of nonstationary Gaussian processes with long-range dependence and intermittency," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 295-321, June.
    22. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," LSE Research Online Documents on Economics 28868, London School of Economics and Political Science, LSE Library.
    23. Jun Zhang & Yao Yu & Li-Xing Zhu & Hua Liang, 2013. "Partial linear single index models with distortion measurement errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(2), pages 237-267, April.
    24. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    25. Dette, Holger & Marchlewski, Mareen, 2007. "A test for the parametric form of the variance function in apartial linear regression model," Technical Reports 2007,26, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    26. Boente, Graciela & Rodriguez, Daniela, 2010. "Robust inference in generalized partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2942-2966, December.
    27. Roozbeh, Mahdi, 2016. "Robust ridge estimator in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 127-144.
    28. Xiuli Wang & Gaorong Li & Lu Lin, 2011. "Empirical likelihood inference for semi-parametric varying-coefficient partially linear EV models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(2), pages 171-185, March.
    29. You, Jinhong & Chen, Gemai & Zhou, Yong, 2007. "Statistical inference of partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 98(8), pages 1539-1557, September.
    30. Feng Yao & Junsen Zhang, 2013. "Efficient Kernel-Based Semiparametric IV Estimation with an Application to Resolving a Puzzle on the Estimates of the Return to Schooling," Working Papers 13-01, Department of Economics, West Virginia University.
    31. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    32. Wong, Heung & Liu, Feng & Chen, Min & Ip, Wai Cheung, 2009. "Empirical likelihood based diagnostics for heteroscedasticity in partial linear models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3466-3477, July.
    33. Manzan, Sebastiano & Zerom, Dawit, 2005. "Kernel estimation of a partially linear additive model," Statistics & Probability Letters, Elsevier, vol. 72(4), pages 313-322, May.
    34. Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
    35. Lam, Clifford & Fan, Jianqing, 2008. "Profile-kernel likelihood inference with diverging number of parameters," LSE Research Online Documents on Economics 31548, London School of Economics and Political Science, LSE Library.
    36. Boente, Graciela & Cao, Ricardo & González Manteiga, Wenceslao & Rodriguez, Daniela, 2013. "Testing in generalized partially linear models: A robust approach," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 203-212.
    37. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    38. Aneiros-Pérez, Germán & Vieu, Philippe, 2006. "Semi-functional partial linear regression," Statistics & Probability Letters, Elsevier, vol. 76(11), pages 1102-1110, June.
    39. Hilafu, Haileab & Wu, Wenbo, 2017. "Partial projective resampling method for dimension reduction: With applications to partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 1-14.
    40. Ferraccioli, Federico & Sangalli, Laura M. & Finos, Livio, 2022. "Some first inferential tools for spatial regression with differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    41. Amini, Morteza & Roozbeh, Mahdi, 2015. "Optimal partial ridge estimation in restricted semiparametric regression models," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 26-40.
    42. Du, Pang & Cheng, Guang & Liang, Hua, 2012. "Semiparametric regression models with additive nonparametric components and high dimensional parametric components," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2006-2017.
    43. Jianhong Shi & Fanrong Zhao, 2018. "Statistical inference for heteroscedastic semi-varying coefficient EV models under restricted condition," Statistical Papers, Springer, vol. 59(2), pages 487-511, June.
    44. Shang, Suoping & Zou, Changliang & Wang, Zhaojun, 2012. "Local Walsh-average regression for semiparametric varying-coefficient models," Statistics & Probability Letters, Elsevier, vol. 82(10), pages 1815-1822.
    45. Raúl Sergio González Treviño, 2003. "Dividends and the Agency Cost of Free Cash Flows," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 1-18, May.
    46. Härdle, Wolfgang & Liang, Hua & Sommerfeld, Volker, 1997. "Bootstrap approximations in a partially linear regression model," SFB 373 Discussion Papers 1997,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    47. Cui, Xia & Lu, Ying & Peng, Heng, 2017. "Estimation of partially linear regression models under the partial consistency property," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 103-121.
    48. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    49. Xiaohong Chen & Yingyao Hu & Arthur Lewbel, 2007. "Nonparametric Identification and Estimation of Nonclassical Errors-in-Variables Models Without Additional Information," Boston College Working Papers in Economics 676, Boston College Department of Economics.
    50. You, Jinhong & Chen, Gemai, 2005. "Testing heteroscedasticity in partially linear regression models," Statistics & Probability Letters, Elsevier, vol. 73(1), pages 61-70, June.
    51. Jiti Gao & Peter C.B. Phillips, 2011. "Semiparametric Estimation in Multivariate Nonstationary Time Series Models," Monash Econometrics and Business Statistics Working Papers 17/11, Monash University, Department of Econometrics and Business Statistics.
    52. Boente, Graciela & Martínez, Alejandra Mercedes, 2023. "A robust spline approach in partially linear additive models," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    53. Wang, Xiaoguang & Shi, Xinyong, 2014. "Robust estimation for survival partially linear single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 140-152.
    54. Wang, Qihua & Sun, Zhihua, 2007. "Estimation in partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1470-1493, August.
    55. Yuejin Zhou & Yebin Cheng & Wenlin Dai & Tiejun Tong, 2018. "Optimal difference-based estimation for partially linear models," Computational Statistics, Springer, vol. 33(2), pages 863-885, June.
    56. Zhu, Xuehu & Wang, Tao & Zhao, Junlong & Zhu, Lixing, 2017. "Inference for biased transformation models," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 105-120.
    57. Liang, Han-Ying & Fan, Guo-Liang, 2009. "Berry-Esseen type bounds of estimators in a semiparametric model with linear process errors," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 1-15, January.
    58. Dong, Chaohua & Gao, Jiti & Tong, Howell, 2006. "Semiparametric penalty function method in partially linear model selection," MPRA Paper 11975, University Library of Munich, Germany, revised Aug 2006.
    59. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers CWP06/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Jun Zhang & Zhenghui Feng & Peirong Xu, 2015. "Estimating the conditional single-index error distribution with a partial linear mean regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 61-83, March.
    61. Eduardo de Carvalho Andrade & Márcio Laurini, 2010. "New Evidence on the Role of Cognitive Skill in Economic Development," IBMEC RJ Economics Discussion Papers 2010-01, Economics Research Group, IBMEC Business School - Rio de Janeiro.
    62. Moral, Ignacio & Rodriguez-Poo, Juan M., 2004. "An efficient marginal integration estimator of a semiparametric additive modelling," Statistics & Probability Letters, Elsevier, vol. 69(4), pages 451-463, October.
    63. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    64. Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
    65. Xuejun Ma & Yue Du & Jingli Wang, 2022. "Model detection and variable selection for mode varying coefficient model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 321-341, June.
    66. Raheem, S.M. Enayetur & Ahmed, S. Ejaz & Doksum, Kjell A., 2012. "Absolute penalty and shrinkage estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 874-891.
    67. Bertille Antoine & Xiaolin Sun, 2022. "Partially linear models with endogeneity: a conditional moment-based approach [Efficient estimation of models with conditional moment restrictions containing unknown functions]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 256-275.
    68. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    69. Chaohua Dong & Jiti Gao & Bin Peng, 2015. "Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity," Monash Econometrics and Business Statistics Working Papers 7/15, Monash University, Department of Econometrics and Business Statistics.
    70. Feng Li & Lu Lin & Yuxia Su, 2013. "Variable selection and parameter estimation for partially linear models via Dantzig selector," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 225-238, February.
    71. You, Jinhong & Chen, Gemai, 2006. "Wild bootstrap estimation in partially linear models with heteroscedasticity," Statistics & Probability Letters, Elsevier, vol. 76(4), pages 340-348, February.
    72. Lu Lin & Lili Liu & Xia Cui & Kangning Wang, 2021. "A generalized semiparametric regression and its efficient estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 1-24, March.
    73. Wang, Zhaoliang & Xue, Liugen & Liu, Juanfang, 2019. "Checking nonparametric component for partially nonlinear model with missing response," Statistics & Probability Letters, Elsevier, vol. 149(C), pages 1-8.
    74. Cai, Xizhen & Zhu, Yeying & Huang, Yuan & Ghosh, Debashis, 2022. "High-dimensional causal mediation analysis based on partial linear structural equation models," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
    75. Song, Lixin & Zhao, Yue & Wang, Xiaoguang, 2010. "Sieve least squares estimation for partially nonlinear models," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1271-1283, September.
    76. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    77. Aifen Feng & Xiaogai Chang & Jingya Fan & Zhengfen Jin, 2023. "Application of LADMM and As-LADMM for a High-Dimensional Partially Linear Model," Mathematics, MDPI, vol. 11(19), pages 1-14, October.
    78. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.
    79. Yangxin Huang & Tao Lu, 2017. "Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features," Computational Statistics, Springer, vol. 32(1), pages 179-196, March.
    80. Germán Aneiros-Pérez & Philippe Vieu, 2011. "Automatic estimation procedure in partial linear model with functional data," Statistical Papers, Springer, vol. 52(4), pages 751-771, November.
    81. Haiyan Su & Linlin Chen, 2024. "Empirical-Likelihood-Based Inference for Partially Linear Models," Mathematics, MDPI, vol. 12(1), pages 1-12, January.
    82. Moral-Arce, Ignacio & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 2011. "Low dimensional semiparametric estimation in a censored regression model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 118-129, January.
    83. Nengxiang Ling & Germán Aneiros & Philippe Vieu, 2020. "kNN estimation in functional partial linear modeling," Statistical Papers, Springer, vol. 61(1), pages 423-444, February.
    84. Aifen Feng & Xiaogai Chang & Youlin Shang & Jingya Fan, 2022. "Application of the ADMM Algorithm for a High-Dimensional Partially Linear Model," Mathematics, MDPI, vol. 10(24), pages 1-13, December.
    85. M. Christopher Auld, 2002. "Disentangling the effects of morbidity and life expectancy on labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 11(6), pages 471-483, September.
    86. Zhang, Yaowu & Zhu, Liping & Ma, Yanyuan, 2017. "Efficient dimension reduction for multivariate response data," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 187-199.
    87. Germán Aneiros & Philippe Vieu, 2015. "Partial linear modelling with multi-functional covariates," Computational Statistics, Springer, vol. 30(3), pages 647-671, September.
    88. Su, Liangjun & Jin, Sainan, 2010. "Profile quasi-maximum likelihood estimation of partially linear spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 157(1), pages 18-33, July.
    89. Liu, Jialuo & Chu, Tingjin & Zhu, Jun & Wang, Haonan, 2021. "Semiparametric method and theory for continuously indexed spatio-temporal processes," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    90. Heng Lian, 2020. "Asymptotics of the Non‐parametric Function for B‐splines‐based Estimation in Partially Linear Models," International Statistical Review, International Statistical Institute, vol. 88(1), pages 142-154, April.
    91. You, Jinhong & Zhou, Xian, 2005. "The law of iterated logarithm of estimators for partially linear panel data models," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 267-279, December.
    92. B. Ettinger & S. Perotto & L. M. Sangalli, 2016. "Spatial regression models over two-dimensional manifolds," Biometrika, Biometrika Trust, vol. 103(1), pages 71-88.
    93. Sigve Hovda, 2014. "Using pseudometrics in kernel density estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 669-696, December.
    94. Sang, Peijun & Lockhart, Richard A. & Cao, Jiguo, 2018. "Sparse estimation for functional semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 105-118.
    95. Bogomolov, Marina & Davidov, Ori, 2019. "Order restricted univariate and multivariate inference with adjustment for covariates in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 20-27.
    96. Lian, Heng & Liang, Hua, 2016. "Separation of linear and index covariates in partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 56-70.
    97. Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2012. "Inference on treatment effects after selection amongst high-dimensional controls," CeMMAP working papers CWP10/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    98. Radhey S. Singh & Lichun Wang, 2012. "A Note on Estimation in Seemingly Unrelated Semi-Parametric Regression Models," Journal of Quantitative Economics, The Indian Econometric Society, vol. 10(1), pages 56-69, January.
    99. Liang, Hua, 2006. "Estimation in partially linear models and numerical comparisons," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 675-687, February.
    100. Zhang, Chunming & Li, Jialiang & Meng, Jingci, 2008. "On Stein's lemma, dependent covariates and functional monotonicity in multi-dimensional modeling," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2285-2303, November.
    101. Li, Jinfang, 2020. "The momentum and reversal effects of investor sentiment on stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    102. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    103. Wolfgang Haerdle & Oliver Linton & Qihua Wang, 2003. "Semiparametric Regression Analysis under Imputation for Missing Response Data," STICERD - Econometrics Paper Series 454, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    104. Jun Zhang & Zhenghui Feng & Peirong Xu & Hua Liang, 2017. "Generalized varying coefficient partially linear measurement errors models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 97-120, February.
    105. Wang, Dewei & Kulasekera, K.B., 2012. "Parametric component detection and variable selection in varying-coefficient partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 117-129.
    106. Hu Yang & Ning Li & Jing Yang, 2020. "A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates," Statistical Papers, Springer, vol. 61(5), pages 1911-1937, October.
    107. Huang, Zhensheng & Pang, Zhen & Hu, Tao, 2013. "Testing structural change in partially linear single-index models with error-prone linear covariates," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 121-133.
    108. Boente, Graciela & Rodriguez, Daniela, 2008. "Robust bandwidth selection in semiparametric partly linear regression models: Monte Carlo study and influential analysis," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2808-2828, January.
    109. Germán Aneiros-Pérez & Philippe Vieu, 2013. "Testing linearity in semi-parametric functional data analysis," Computational Statistics, Springer, vol. 28(2), pages 413-434, April.
    110. Xin Lu & Brent A. Johnson, 2015. "Direct estimation of the mean outcome on treatment when treatment assignment and discontinuation compete," Biometrika, Biometrika Trust, vol. 102(4), pages 797-807.
    111. Boente, Graciela & Salibian-Barrera, Matías & Vena, Pablo, 2020. "Robust estimation for semi-functional linear regression models," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    112. Hsiao-Hsian Gao & Li-Shan Huang, 2016. "Sample size planning for testing significance of curves," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2019-2028, August.
    113. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    114. Gao, Jiti & Phillips, Peter C.B., 2013. "Semiparametric estimation in triangular system equations with nonstationarity," Journal of Econometrics, Elsevier, vol. 176(1), pages 59-79.
    115. Zhang, Jun & Feng, Zhenghui & Peng, Heng, 2018. "Estimation and hypothesis test for partial linear multiplicative models," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 87-103.
    116. Lin, Lu & Zhu, Lixing & Gai, Yujie, 2016. "Inference for biased models: A quasi-instrumental variable approach," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 22-36.
    117. Wang, Xiuli & Zhao, Shengli & Wang, Mingqiu, 2017. "Restricted profile estimation for partially linear models with large-dimensional covariates," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 71-76.
    118. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    119. Liang, Hua & Härdle, Wolfgang & Carroll, Raymond J., 1997. "Large sample theory in a semiparametric partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    120. Huang, Zhensheng & Zhou, Zhangong & Jiang, Rong & Qian, Weimin & Zhang, Riquan, 2010. "Empirical likelihood based inference for semiparametric varying coefficient partially linear models with error-prone linear covariates," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 497-504, March.
    121. Qinqin Hu & Lu Lin, 2018. "Conditional feature screening for mean and variance functions in models with multiple-index structure," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(4), pages 357-393, May.
    122. Yayi Yan & Jiti Gao & Bin peng, 2020. "A Class of Time-Varying Vector Moving Average (infinity) Models," Monash Econometrics and Business Statistics Working Papers 39/20, Monash University, Department of Econometrics and Business Statistics.
    123. Zhou, Xing-cai & Lin, Jin-guan, 2013. "Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 251-270.
    124. Graciela Boente & Daniela Rodriguez & Pablo Vena, 2020. "Robust estimators in a generalized partly linear regression model under monotony constraints," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 50-89, March.
    125. Pateiro-López, Beatriz & González-Manteiga, Wenceslao, 2006. "Multivariate partially linear models," Statistics & Probability Letters, Elsevier, vol. 76(14), pages 1543-1549, August.
    126. Jiti Gao & Peter C. B. Phillips, 2010. "Semiparametric Estimation in Time Series of Simultaneous Equations," Cowles Foundation Discussion Papers 1769, Cowles Foundation for Research in Economics, Yale University.
    127. Bianco, Ana M. & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2015. "Robust inference in partially linear models with missing responses," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 88-98.
    128. Yunlu Jiang, 2015. "Robust estimation in partially linear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2497-2508, November.
    129. Robinson, Peter M. & Thawornkaiwong, Supachoke, 2012. "Statistical inference on regression with spatial dependence," Journal of Econometrics, Elsevier, vol. 167(2), pages 521-542.
    130. Ana M. Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2019. "Plug-in marginal estimation under a general regression model with missing responses and covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 106-146, March.
    131. Huang, Zhensheng & Zhang, Riquan, 2009. "Empirical likelihood for nonparametric parts in semiparametric varying-coefficient partially linear models," Statistics & Probability Letters, Elsevier, vol. 79(16), pages 1798-1808, August.
    132. Guo-Liang Fan & Han-Ying Liang & Jiang-Feng Wang, 2013. "Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors," Statistical Papers, Springer, vol. 54(1), pages 85-112, February.
    133. Wei Lan & Ronghua Luo & Chih-Ling Tsai & Hansheng Wang & Yunhong Yang, 2015. "Testing the Diagonality of a Large Covariance Matrix in a Regression Setting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 76-86, January.
    134. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    135. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    136. Xue-Jun Ma & Jing-Xiao Zhang, 2016. "A new variable selection approach for varying coefficient models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 59-72, January.
    137. Samuele Centorrino & Jean-Pierre Florens, 2014. "Nonparametric Instrumental Variable Estimation of Binary Response Models," Department of Economics Working Papers 14-07, Stony Brook University, Department of Economics.
    138. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    139. Ana Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2011. "Asymptotic behavior of robust estimators in partially linear models with missing responses: the effect of estimating the missing probability on the simplified marginal estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 524-548, November.
    140. Wang, Xiaoguang & Lu, Dawei & Song, Lixin, 2013. "Statistical inference for partially linear stochastic models with heteroscedastic errors," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 150-160.
    141. Lu, Xuewen, 2009. "Empirical likelihood for heteroscedastic partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 387-396, March.
    142. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    143. Ying Lu & Jiang Du & Zhimeng Sun, 2014. "Functional partially linear quantile regression model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 317-332, February.
    144. Huang, Zhensheng, 2012. "Empirical likelihood for the parametric part in partially linear errors-in-function models," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 63-66.
    145. Q. Shao, 2009. "Seasonality analysis of time series in partial linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 827-837.
    146. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    147. Roozbeh, M. & Arashi, M., 2013. "Feasible ridge estimator in partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 35-44.
    148. Zhangong Zhou & Linjun Tang, 2019. "Testing for parametric component of partially linear models with missing covariates," Statistical Papers, Springer, vol. 60(3), pages 747-760, June.
    149. Zhou, Jianjun & Chen, Min, 2012. "Spline estimators for semi-functional linear model," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 505-513.
    150. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.
    151. M. Arashi & Mahdi Roozbeh, 2019. "Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data," Statistical Papers, Springer, vol. 60(3), pages 667-686, June.
    152. Zhang, Jun & Lin, Bingqing & Zhou, Yan, 2021. "Kernel density estimation for partial linear multivariate responses models," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    153. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.
    154. Yixin Fang & Heng Lian & Hua Liang, 2018. "A generalized partially linear framework for variance functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1147-1175, October.
    155. You, Jinhong & Chen, Gemai, 2006. "Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 324-341, February.
    156. Shuping Jiang & Lan Xue, 2015. "Globally consistent model selection in semi-parametric additive coefficient models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(4), pages 532-551, December.
    157. Boente, Graciela & Vahnovan, Alejandra, 2017. "Robust estimators in semi-functional partial linear regression models," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 59-84.
    158. Yang, Hu & Li, Tingting, 2010. "Empirical likelihood for semiparametric varying coefficient partially linear models with longitudinal data," Statistics & Probability Letters, Elsevier, vol. 80(2), pages 111-121, January.
    159. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers 06/12, Institute for Fiscal Studies.
    160. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    161. Zhang, Yuanqing & Sun, Yanqing, 2015. "Estimation of partially specified dynamic spatial panel data models with fixed-effects," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 37-46.
    162. You, Jinhong & Zhou, Xian & Zhu, Li-Xing, 2009. "Inference on a regression model with noised variables and serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1182-1197, July.
    163. Zhang, Jun & Zhou, Yan & Lin, Bingqing & Yu, Yao, 2017. "Estimation and hypothesis test on partial linear models with additive distortion measurement errors," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 114-128.

  181. Härdle, Wolfgang & Kim, Woocheol & Tripathi, Gautam, 2000. "Nonparametric estimation of additive models with homogeneous components," SFB 373 Discussion Papers 2000,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," CeMMAP working papers CWP14/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Boston College Working Papers in Economics 585, Boston College Department of Economics, revised 04 Sep 2006.

  182. Härdle, Wolfgang & Schmidt, Peter, 2000. "Common factors governing VDAX movements and the maximum loss," SFB 373 Discussion Papers 2000,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  183. Härdle, Wolfgang & Tschernig, Rolf, 2000. "Flexible time series analysis," SFB 373 Discussion Papers 2000,51, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Härdle, Wolfgang Karl & Chen, Ying & Schulz, Rainer, 2004. "Prognose mit nichtparametrischen Verfahren," Papers 2004,07, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

  184. Härdle, Wolfgang & Mammen, Enno & Proença, Isabel, 2000. "A bootstrap test for single index models," SFB 373 Discussion Papers 2000,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    2. Alan Ker & A. Tolga Ergun, 2007. "On the Revelation of Private Information in the U.S. Crop Insurance Program," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 74(4), pages 761-776, December.

  185. Wolfgang Haerdle & Helmut Herwartz & Volodia Spokoiny, 2000. "Time Inhomogeneous Multiple Volatility Modelling," Econometric Society World Congress 2000 Contributed Papers 1429, Econometric Society.

    Cited by:

    1. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research.

  186. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Dette, Holger & Pardo-Fernandez, Juan Carlos & van Keilegom, Ingrid, 2007. "Goodness-of-fit tests for multiplicativemodels with dependent data," Technical Reports 2007,34, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  187. Strohe, Hans Gerhard & Härdle, Wolfgang & Geppert, Frank, 1999. "DPLS in XploRe: A PLS approach to dynamic path models," SFB 373 Discussion Papers 1999,80, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Frick, Joachim R. & Goebel, Jan, 2005. "Regional Income Stratification in Unified Germany Using a Gini Decomposition Approach," IZA Discussion Papers 1891, Institute of Labor Economics (IZA).

  188. Härdle, Wolfgang & Klinke, Sigbert & Marron, J. S., 1999. "Connected teaching of statistics," SFB 373 Discussion Papers 1999,24, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Derby, Nathaniel & Härdle, Wolfgang & Rönz, Bernd, 1999. "The three dimensions of multimedia teaching of statistics," SFB 373 Discussion Papers 1999,76, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  189. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Jorge Barrientos Marin, 2006. "Estimation And Testing An Additive Partially Linear Model In A System Of Engel Curves," Working Papers. Serie AD 2006-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  190. Liang, Hua & Härdle, Wolfgang, 1997. "Asymptotic normality of parametric part in partial linear heteroscedastic regression models," SFB 373 Discussion Papers 1997,33, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Liang, Hua, 1997. "Asymptotic normality of parametric part in partially linear models with measurement error in the nonparametric part," SFB 373 Discussion Papers 1997,46, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Liang, Hua & Härdle, Wolfgang & Carroll, Raymond J., 1997. "Large sample theory in a semiparametric partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  191. Härdle, Wolfgang & Liang, Hua & Sommerfeld, Volker, 1997. "Bootstrap approximations in a partially linear regression model," SFB 373 Discussion Papers 1997,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. M. Christopher Auld, 2002. "Disentangling the effects of morbidity and life expectancy on labor market outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 11(6), pages 471-483, September.

  192. Burda, Michael C. & Härdle, Wolfgang & Müller, Marlene & Werwatz, Axel, 1997. "Semiparametric analysis of German East-West migration intentions: Facts and theory," SFB 373 Discussion Papers 1998,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Stephen Drinkwater, 2003. "Go West? Assessing the willingness to move from Central and Eastern European Countries," School of Economics Discussion Papers 0503, School of Economics, University of Surrey.
    2. Christian Dustmann & Anna Okatenko, 2013. "Out-migration, Wealth Constraints, and the Quality of Local Amenities," RF Berlin - CReAM Discussion Paper Series 1313, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).
    3. Christian Bayer & Falko Juessen, 2012. "On the Dynamics of Interstate Migration: Migration Costs and Self-Selection," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(3), pages 377-401, July.
    4. Stephen Drinkwater & Michał Garapich, 2013. "Migration Plans and Strategies of Recent Polish Migrants to England and Wales: Do They Have Any and How Do They Change?," Norface Discussion Paper Series 2013023, Norface Research Programme on Migration, Department of Economics, University College London.
    5. Mitze, Timo & Reinkowski, Janina, 2011. "Testing the neoclassical migration model: overall and age-group specific results for German regions," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 43(4), pages 277-297.
    6. Isabelle Chort, 2012. "New insights into the selection process of Mexican migrants.What can we learn from discrepancies between intentions to migrate and actual moves to the U.S.?," PSE Working Papers halshs-00689467, HAL.
    7. Lilo Locher, 2010. "Testing for the Option Value of Migration," Working Papers id:2763, eSocialSciences.
    8. Jennifer Hunt, 2000. "Why Do People Still Live in East Germany?," Discussion Papers of DIW Berlin 201, DIW Berlin, German Institute for Economic Research.
    9. Locher, Lilo, 2001. "Testing for the Option Value of Migration," IZA Discussion Papers 405, Institute of Labor Economics (IZA).
    10. Helmut Rainer & Thomas Siedler, 2009. "The role of social networks in determining migration and labour market outcomes," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 17(4), pages 739-767, October.
    11. Anzelika Zaiceva, 2006. "Self-Selection and the Returns to Geographic Mobility: What Can Be Learned from the German Reunification "Experiment"," Discussion Papers of DIW Berlin 580, DIW Berlin, German Institute for Economic Research.
    12. Roberto Basile & Jaewon Lim, 2017. "Nonlinearities in Interregional Migration Behavior," International Regional Science Review, , vol. 40(6), pages 563-589, November.
    13. Locher, Lilo, 2001. "The Determination of a Migration Wave Using Ethnicity and Community Ties," IZA Discussion Papers 346, Institute of Labor Economics (IZA).
    14. Michael C. Burda & Jennifer Hunt, 2001. "From Reunification to Economic Integration: Productivity and the Labor Market in Eastern Germany," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 32(2), pages 1-92.
    15. Eder, Christoph & Halla, Martin, 2018. "On the Origin and Composition of the German East-West Population Gap," IZA Discussion Papers 12031, Institute of Labor Economics (IZA).
    16. Gang, Ira & Epstein, Gil S, 2004. "The Influence of Others on Migration Plans," CEPR Discussion Papers 4617, C.E.P.R. Discussion Papers.
    17. Peter Huber & Herbert Brücker & Janos Köllö & Iulia Traistaru & Tomasz Mickiewicz, 2002. "Regional and Labour Market Development in Candidate Countries. A Literature Survey," WIFO Studies, WIFO, number 23340, April.
    18. Ivlevs, Artjoms, 2015. "Happy Moves? Assessing the Link Between Life Satisfaction and Emigration Intentions," IZA Discussion Papers 9017, Institute of Labor Economics (IZA).
    19. Silke Uebelmesser, 2006. "To Go or Not to Go: Emigration from Germany," German Economic Review, Verein für Socialpolitik, vol. 7(2), pages 211-231, May.
    20. Blackaby, David H. & Drinkwater, Stephen, 2004. "Migration and Labour Market Differences: The Case of Wales," IZA Discussion Papers 1275, Institute of Labor Economics (IZA).
    21. De Coulon, Augustin & Wolff, François-Charles, 2005. "Immigrants at retirement: stay/return or 'va-et-vient'?," LSE Research Online Documents on Economics 19890, London School of Economics and Political Science, LSE Library.
    22. Kubis, Alexander & Schneider, Lutz, 2007. "Determinants of Female Migration – The Case of German NUTS 3 Regions," IWH Discussion Papers 12/2007, Halle Institute for Economic Research (IWH).
    23. Simon Winter, 2020. "“It’s the Economy, Stupid!”: On the Relative Impact of Political and Economic Determinants on Migration," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(2), pages 207-252, April.
    24. Abramitzky, Ran, 2009. "The effect of redistribution on migration: Evidence from the Israeli kibbutz," Journal of Public Economics, Elsevier, vol. 93(3-4), pages 498-511, April.
    25. Christian Merkl & Dennis Snower, 2008. "East German unemployment: the myth of the irrelevant labor market," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 31(1), pages 151-165, September.
    26. Michiel Van Leuvensteijn & Ashok Parikh, 2002. "How different are the determinants of population versus labour migration in Germany?," Applied Economics Letters, Taylor & Francis Journals, vol. 9(11), pages 699-703.
    27. Matthias Huber & Till Nikolka & Panu Poutvaara & Ann-Marie Sommerfeld & Silke Uebelmesser, 2022. "Migration Aspirations and Intentions," CESifo Working Paper Series 9708, CESifo.
    28. de Coulon, Augustin & Radu, Dragos & Steinhardt, Max Friedrich, 2013. "Pane e Cioccolata: The impact of native attitudes on return migration," HWWI Research Papers 146, Hamburg Institute of International Economics (HWWI).
    29. Talat Mahmood & Klaus Schömann, 2003. "On the Migration Decision of IT-Graduates: A Two-Level Nested Logit Model," CIG Working Papers SP II 2003-22, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    30. Jan Fidrmuc & Peter Huber, 2007. "The willingness to migrate in the CEECs evidence from the Czech Republic," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(4), pages 351-369, September.
    31. Bonin, Holger & Eichhorst, Werner & Florman, Christer & Hansen, Mette Okkels & Skiöld, Lena & Stuhler, Jan & Tatsiramos, Konstantinos & Thomasen, Henrik & Zimmermann, Klaus F., 2008. "Geographic Mobility in the European Union: Optimising its Economic and Social Benefits," IZA Research Reports 19, Institute of Labor Economics (IZA).
    32. Artjoms Ivlevs, 2014. "Happy moves? Assessing the impact of subjective well-being on the emigration decision," Working Papers 20141402, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    33. Stephen Drinkwater, 2003. "Estimating the willingness to move within Great Britain: Importance and implications," School of Economics Discussion Papers 1203, School of Economics, University of Surrey.
    34. Torben Kuhlenkasper & Max Friedrich Steinhardt, 2012. "Who Leaves and When? - Selective Outmigration of Immigrants from Germany," Discussion Papers 3, Central European Labour Studies Institute (CELSI).
    35. Oliver Busch, 2007. "When Have All the Graduates Gone?: Internal Cross-State Migration of Graduates in Germany 1984-2004," SOEPpapers on Multidisciplinary Panel Data Research 26, DIW Berlin, The German Socio-Economic Panel (SOEP).
    36. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    37. Snower, Dennis J. & Merkl, Christian, 2006. "The Caring Hand that Cripples: The East German Labor Market After Reunification (Detailed Version)," IZA Discussion Papers 2066, Institute of Labor Economics (IZA).
    38. Artjoms Ivlevs, 2013. "Minorities on the move? Assessing post-enlargement emigration intentions of Latvia’s Russian speaking minority," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(1), pages 33-52, August.
    39. van Dalen, H.P. & Henkens, K., 2008. "Emigration Intentions : Mere Words or True Plans? Explaining International Migration Intentions and Behavior," Other publications TiSEM d78ea768-e1d5-4a80-baff-2, Tilburg University, School of Economics and Management.
    40. de Coulon, Augustin & Wolff, François-Charles, 2006. "The Location of Immigrants at Retirement: Stay/Return or ‘Va-et-Vient’?," IZA Discussion Papers 2224, Institute of Labor Economics (IZA).
    41. Charles Bellemare, 2004. "Identification and Estimation of the Economic Performance of Outmigrants using Panel Attrition," Cahiers de recherche 0429, CIRPEE.
    42. Isilda Mara & Michael Landesmann, 2013. "The steadiness of migration plans and expected length of stay: based on a recent survey of Romanian migrants in Italy," Norface Discussion Paper Series 2013007, Norface Research Programme on Migration, Department of Economics, University College London.
    43. Christoph Kern, 2014. "Regional Structures and Mobility Dispositions: A Multilevel Proportional- & Partial-Proportional Odds Approach," SOEPpapers on Multidisciplinary Panel Data Research 681, DIW Berlin, The German Socio-Economic Panel (SOEP).
    44. Siedler, Thomas & Rainer, Helmut, 2008. "Social networks in determining migration and labour market outcomes: evidence from the German reunification," ISER Working Paper Series 2008-36, Institute for Social and Economic Research.
    45. Guido Friebel & Juan Miguel Gallego & Mariapia Mendola, 2011. "Xenophobic Attacks, Migration Intentions and Networks: Evidence from the South of Africa," Development Working Papers 321, Centro Studi Luca d'Agliano, University of Milano, revised 17 Oct 2011.
    46. Chort, Isabelle, 2014. "Mexican Migrants to the US: What Do Unrealized Migration Intentions Tell Us About Gender Inequalities?," World Development, Elsevier, vol. 59(C), pages 535-552.
    47. Hendrik Dalen & George Groenewold & Jeannette Schoorl, 2005. "Out of Africa: what drives the pressure to emigrate?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 18(4), pages 741-778, November.
    48. Ashok Parikh & Michiel Van Leuvensteijn, 2003. "Interregional labour mobility, inequality and wage convergence," Applied Economics, Taylor & Francis Journals, vol. 35(8), pages 931-941.
    49. Herbert Brücker & Parvati Trübswetter, 2007. "Do the best go west? An analysis of the self-selection of employed East-West migrants in Germany," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(4), pages 371-395, September.
    50. Schneider, Lutz & Kubis, Alexander, 2009. "Are there Gender-specific Preferences for Location Factors? A Grouped Conditional Logit-Model of Interregional Migration Flows in Germany," IWH Discussion Papers 5/2009, Halle Institute for Economic Research (IWH).
    51. Christoph Eder & Martin Halla, 2018. "On the Origin of the German East-West Population Gap," Economics working papers 2018-17, Department of Economics, Johannes Kepler University Linz, Austria.
    52. Marius Braun, 2021. "A Real-Options Analysis of Climate Change and International Migration," MAGKS Papers on Economics 202138, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    53. Haas, Anette, 2000. "Arbeitsmarktausgleich: Regionale Mobilität gestiegen : bei einem Betriebswechsel werden immer öfter größere Entfernungen überwunden - gerade auch von Arbeitslosen," IAB-Kurzbericht 200004, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    54. Timo MITZE & Björn ALECKE & Gerhard UNTIEDT, 2008. "Determinants of Interregional Migration Among German States and its Implications for Reducing East-West Disparities: Results from a Panel VAR Using Efficient GMM Estimation," EcoMod2008 23800089, EcoMod.
    55. Nicola Fuchs‐Schündeln & Matthias Schündeln, 2009. "Who stays, who goes, who returns?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 17(4), pages 703-738, October.
    56. Thomas Liebig & Alfonso Sousa-Poza, 2003. "How does income inequality influence international migration?," ERSA conference papers ersa03p472, European Regional Science Association.
    57. Mahmood, Talat & Schömann, Klaus, 2009. "The decision to migrate: A simultaneous decision making approach," Discussion Papers, Research Unit: Competition and Innovation SP II 2009-17, WZB Berlin Social Science Center.
    58. Rodriguez Poo, Juan M. & Sperlich, Stefan & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
    59. Braun, Marius, 2022. "A Real-Options Analysis of Climate Change and International Migration," VfS Annual Conference 2022 (Basel): Big Data in Economics 264006, Verein für Socialpolitik / German Economic Association.
    60. Mitze, Timo & Reinkowski, Janina, 2010. "Testing the Validity of the Neoclassical Migration Model: Overall and Age-Group Specific Estimation Results for German Spatial Planning Regions," MPRA Paper 23616, University Library of Munich, Germany.
    61. Artjoms Ivlevs & Roswitha King, 2012. "Family Migration Capital and Migration Intentions," Journal of Family and Economic Issues, Springer, vol. 33(1), pages 118-129, March.
    62. Talat Mahmood & Klaus Schömann, 2003. "On the Migration Decision of Indian IT-Graduates: An Empirical Analysis," CIG Working Papers SP II 2003-23, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).

  193. Liang, Hua & Härdle, Wolfgang & Werwatz, Axel, 1997. "Asymptotic properties of the nonparametric part in partial linear heteroscedastic regression models," SFB 373 Discussion Papers 1997,55, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Jiaqi Li & Likai Chen & Kun Ho Kim & Tianwei Zhou, 2022. "Simultaneous Inference of a Partially Linear Model in Time Series," Papers 2212.10359, arXiv.org, revised Sep 2023.

  194. Liang, Hua & Härdle, Wolfgang & Carroll, Raymond J., 1997. "Large sample theory in a semiparametric partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Liang, Hua, 1997. "Asymptotic normality of parametric part in partially linear models with measurement error in the nonparametric part," SFB 373 Discussion Papers 1997,46, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Weiming Yang & Yiping Yang, 2020. "Composite quantile regression estimation of linear error-in-variable models using instrumental variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 1-16, January.
    3. He, Xuming & Liang, Hua, 1997. "Quantile regression estimates for a class of linear and partially linear errors-in-variables models," SFB 373 Discussion Papers 1997,103, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  195. Härdle, Wolfgang & Müller, Marlene, 1997. "Multivariate and semiparametric kernel regression," SFB 373 Discussion Papers 1997,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Tomas Ruzgas & Mantas Lukauskas & Gedmantas Čepkauskas, 2021. "Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model," Mathematics, MDPI, vol. 9(21), pages 1-22, October.
    2. Dursun AYDIN & Ersin YILMAZ, 2017. "Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data," Romanian Statistical Review, Romanian Statistical Review, vol. 65(2), pages 81-104, June.

  196. Sperlich, S. & Linton, O. & Härdle, Wolfgang, 1997. "A Simulation Comparison between Integration and Backfitting Methods of Estimating Separable Nonparametric Regression Models," SFB 373 Discussion Papers 1997,66, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    2. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.

  197. Klinke, Sigbert & Golubev, Yuri & Härdle, Wolfgang & Neumann, Michael H., 1997. "Teaching wavelets in XploRe," SFB 373 Discussion Papers 1997,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  198. Härdle, Wolfgang & Sperlich, Stefan & Spokoiny, Vladimir G., 1997. "Component analysis for additive models," SFB 373 Discussion Papers 1997,52, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Horowitz, Joel L. & Spokoiny, Vladimir G., 1999. "An adaptive, rate-optimal test of a parametric model against a nonparametric alternative," SFB 373 Discussion Papers 1999,10, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Hardle W. & Sperlich S. & Spokoiny V., 2001. "Structural Tests in Additive Regression," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1333-1347, December.
    3. Horowitz, Joel L. & Spokoiny, Vladimir G., 1999. "An Adaptive, Rate-Optimal Test of a Parametric Model Against a Nonparametric Alternative," Working Papers 99-02, University of Iowa, Department of Economics.

  199. Fan, J. & Härdle, Wolfgang & Mammen, Enno, 1996. "Direct estimation of low dimensional components in additive models," SFB 373 Discussion Papers 1996,17, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Elena Ketteni & Theofanis P. Mamuneas & Thanasis Stengos, 2007. "Nonlinearities in Economic Growth: A Semiparametric Approach applied to Information Technology data," Working Papers 0701, University of Guelph, Department of Economics and Finance.
    2. Raymond J Carroll & Oliver Linton & Enno Mammen & Zhijie Xiao, 2002. "More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors," STICERD - Econometrics Paper Series 435, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    4. Badi H. Baltagi & Dong Li, 2002. "Series Estimation of Partially Linear Panel Data Models with Fixed Effects," Annals of Economics and Finance, Society for AEF, vol. 3(1), pages 103-116, May.
    5. Sperlich, Stefan & Tjøstheim, Dag & Yang, Lijian, 2002. "Nonparametric Estimation And Testing Of Interaction In Additive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 197-251, April.
    6. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Mammen, Enno & Linton, Oliver & Nielsen, J, 2000. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 2315, London School of Economics and Political Science, LSE Library.
    8. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    9. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Semiparametric spatial regression: theory and practice," MPRA Paper 11991, University Library of Munich, Germany, revised Oct 2006.
    11. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    12. Thanasis Stengos & Andreas Savvides & Theofanis Mamuneas & Elena Ketteni, 2007. "Is the Financial Development and Economic Growth Relationship Nonlinear?," Economics Bulletin, AccessEcon, vol. 15(14), pages 1-12.

  200. Härdle, Wolfgang & Mammen, Enno & Müller, Maike, 1996. "Testing Parametric versus Semiparametric Modelling in Generalized Linear Models," SFB 373 Discussion Papers 1996,28, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.

  201. Härdle, Wolfgang & Yang, L., 1996. "Nonparametric Time Series Model Selection," SFB 373 Discussion Papers 1996,53, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Norberto Rodríguez & Patricia Siado, 2003. "Un Pronóstico No Paramétrico De La Inflación Colombiana," Borradores de Economia 3691, Banco de la Republica.
    2. Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).

  202. Bossaerts, P. & Hafner, C. & Härdle, Wolfgang, 1996. "Foreign Exchange Rates Have Surprising Volatility," SFB 373 Discussion Papers 1996,68, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
    2. Sami MESTIRI, 2022. "Modeling the volatility of Bitcoin returns using Nonparametric GARCH models," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 2-16, June.
    3. GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," LIDAM Discussion Papers CORE 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. HARDLE, Wolfgang & HAFNER, Christian M., 2000. "Discrete time option pricing with flexible volatility estimation," LIDAM Reprints CORE 1439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Bossaerts, Peter & Hillion, Pierre, 2003. "Local parametric analysis of derivatives pricing and hedging," Journal of Financial Markets, Elsevier, vol. 6(4), pages 573-605, August.
    8. GHYSELS, Eric & PATILEA, Valentin & RENAULT, Eric & TORRES, Olivier, 1997. "Nonparametric methods and option pricing," LIDAM Discussion Papers CORE 1997075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. MEDDAHI, Nour & RENAULT, Éric, 1998. "Quadratic M-Estimators for ARCH-Type Processes," Cahiers de recherche 9814, Universite de Montreal, Departement de sciences economiques.
    10. Bossaerts, Peter & Hillion, Pierre, 1997. "Local parametric analysis of hedging in discrete time," Journal of Econometrics, Elsevier, vol. 81(1), pages 243-272, November.

  203. Yang, L. & Härdle, Wolfgang, 1996. "Nonparametric Autoregression with Multiplicative Volatility and Additive Mean," SFB 373 Discussion Papers 1996,62, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Kreiss, Jens-Peter & Neumann, Michael H. & Yao, Qiwei, 2008. "Bootstrap tests for simple structures in nonparametric time series regression," LSE Research Online Documents on Economics 24135, London School of Economics and Political Science, LSE Library.
    2. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    3. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    4. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    5. Miao Yang & Lan Xue & Lijian Yang, 2016. "Variable selection for additive model via cumulative ratios of empirical strengths total," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(3), pages 595-616, September.
    6. Francesco Audrino & Peter Bühlmann, 2007. "Splines for Financial Volatility," University of St. Gallen Department of Economics working paper series 2007 2007-11, Department of Economics, University of St. Gallen.
    7. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Detecting serial dependencies with the reproducibility probability autodependogram," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 35-61, January.
    8. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    9. Francesco Audrino, 2005. "Local Likelihood for non‐parametric ARCH(1) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 251-278, March.
    10. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    11. Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," Finance 9904005, University Library of Munich, Germany.
    12. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    13. Buhlmann, Peter & McNeil, Alexander J., 2002. "An algorithm for nonparametric GARCH modelling," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 665-683, October.
    14. Mammen, Enno & Linton, Oliver & Nielsen, J, 2000. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 2315, London School of Economics and Political Science, LSE Library.
    15. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. HARDLE, Wolfgang & HAFNER, Christian M., 2000. "Discrete time option pricing with flexible volatility estimation," LIDAM Reprints CORE 1439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Maria Mohr & Natalie Neumeyer, 2021. "Nonparametric volatility change detection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 529-548, June.
    18. Fengler, M.R. & Mammen, E. & Vogt, M., 2015. "Specification and structural break tests for additive models with applications to realized variance data," Journal of Econometrics, Elsevier, vol. 188(1), pages 196-218.
    19. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2018. "Testing for Serial Independence: Beyond the Portmanteau Approach," The American Statistician, Taylor & Francis Journals, vol. 72(3), pages 219-238, July.
    20. Tschernig, Rolf & Yang, Lijian, 1997. "Nonparametric lag selection for time series," SFB 373 Discussion Papers 1997,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    21. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.
    22. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    23. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    24. Lu, Zudi & Jiang, Zhenyu, 2001. "L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term," Statistics & Probability Letters, Elsevier, vol. 51(2), pages 121-130, January.
    25. Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    26. Ming Chen & Qiongxia Song, 2016. "Semi-parametric estimation and forecasting for exogenous log-GARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 93-112, March.
    27. Yang, Lijian, 2006. "A semiparametric GARCH model for foreign exchange volatility," Journal of Econometrics, Elsevier, vol. 130(2), pages 365-384, February.
    28. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    29. Neumann, Michael H., 1997. "On robustness of model-based bootstrap schemes in nonparametric time series analysis," SFB 373 Discussion Papers 1997,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    30. Yang, Hu & Wu, Xingcui, 2011. "Semiparametric EGARCH model with the case study of China stock market," Economic Modelling, Elsevier, vol. 28(3), pages 761-766.
    31. Neumeyer, Natalie & Omelka, Marek & Hudecová, Šárka, 2019. "A copula approach for dependence modeling in multivariate nonparametric time series," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 139-162.

  204. Härdle, Wolfgang & Tsybakov, A. & Yang, L., 1996. "Nonparametric Vector Autoregression," SFB 373 Discussion Papers 1996,61, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    2. Tschernig, Rolf & Yang, Lijian, 2000. "Nonparametric estimation of generalized impulse response function," SFB 373 Discussion Papers 2000,89, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    4. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    5. Yuanhua Feng & David Hand & Yuanhua Feng, 2012. "A Multivariate Random Walk Model with Slowly Changing Drift and Cross-correlation Applied to Finance," Working Papers CIE 50, Paderborn University, CIE Center for International Economics.
    6. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    7. Christian Hafner, 2005. "Durations, volume and the prediction of financial returns in transaction time," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 145-152.
    8. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Mario Francisco-Fernandez & Juan Vilar-Fernandez, 2004. "Weighted Local Nonparametric Regression with Dependent Errors: Study of Real Private Residential Fixed Investment in the USA," Statistical Inference for Stochastic Processes, Springer, vol. 7(1), pages 69-93, March.
    10. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Yang, Lijian & Tschernig, Rolf, 1997. "Multivariate plug-in bandwidth for local linear regression," SFB 373 Discussion Papers 1997,99, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    13. Tschernig, Rolf & Yang, Lijian, 1997. "Nonparametric lag selection for time series," SFB 373 Discussion Papers 1997,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    14. Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
    15. Yuanhua Feng, 2013. "Double-conditional smoothing of high-frequency volatility surface in a spatial multiplicative component GARCH with random effects," Working Papers CIE 65, Paderborn University, CIE Center for International Economics.
    16. Yang, Lijian, 2006. "A semiparametric GARCH model for foreign exchange volatility," Journal of Econometrics, Elsevier, vol. 130(2), pages 365-384, February.
    17. Feng, Yuanhua & Yu, Keming, 2006. "Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model," MPRA Paper 1597, University Library of Munich, Germany.
    18. Juan Vilar Fernández & Mario Francisco Fernández, 2002. "Local polynomial regression smoothers with AR-error structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(2), pages 439-464, December.
    19. A. Pérez-González & J. Vilar-Fernández & W. González-Manteiga, 2009. "Asymptotic properties of local polynomial regression with missing data and correlated errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 85-109, March.
    20. Harvill, Jane L. & Ray, Bonnie K., 2006. "Functional coefficient autoregressive models for vector time series," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3547-3566, August.
    21. Hafner, C.M. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2005. "Semi-Parametric Modelling of Correlation Dynamics," Econometric Institute Research Papers EI 2005-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. De Gooijer, Jan G. & Ray, Bonnie K., 2003. "Modeling vector nonlinear time series using POLYMARS," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 73-90, February.

  205. Schmelzer, S. & Kötter, T. & Klinke, S. & Härdle, Wolfgang, 1996. "A New Generation of a Statistical Computing Environment on the Net," SFB 373 Discussion Papers 1996,52, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. A. M. Kitchen & R. Drachenberg & J. Symanzik, 2003. "Assessing the reliability of web-based statistical software," Computational Statistics, Springer, vol. 18(1), pages 107-122, March.

  206. Härdle, Wolfgang & Marron, J. & Yang, L., 1996. "Discussion," SFB 373 Discussion Papers 1996,65, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Farmer, Roger E A, 1997. "Money in a Real Business Cycle Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(4), pages 568-611, November.
    2. Bruckner, Eberhard, 2003. "Überlebenschancen neu gegründeter Firmen: Ein evolutionstheoretischer Zugang," Discussion Papers, Research Unit: Civil Society and Transnational Networks SP IV 2003-105, WZB Berlin Social Science Center.
    3. Svensson, Lars E. O., 1999. "Monetary policy issues for the Eurosystem," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 51(1), pages 79-136, December.
    4. Guillaume Allègre, 2012. "Work, family or state ? from wage inequalitie ans in-work poverty in a european cross-country perspective," Documents de Travail de l'OFCE 2012-12, Observatoire Francais des Conjonctures Economiques (OFCE).
    5. de Rus, Gines & Trujillo, Lourdes & Romero, Manuel, 2000. "Participacion privada en la construccion y explotacion de carreteras de peaje [Private sector funding for the construction and operation of toll roads]," MPRA Paper 12204, University Library of Munich, Germany.
    6. Svensson, Lars E.O., 1998. "Inflation Targeting as a Monetary Policy Rule," Seminar Papers 646, Stockholm University, Institute for International Economic Studies.
    7. Rauch, James E. & Watson, Joel, 2003. "Starting small in an unfamiliar environment," International Journal of Industrial Organization, Elsevier, vol. 21(7), pages 1021-1042, September.
    8. Gersbach, Hans & Schmutzler, Armin, 2006. "Foreign Direct Investment and R&D Offshoring," CEPR Discussion Papers 5766, C.E.P.R. Discussion Papers.
    9. George J. Mailath & Larry Samuelson, "undated". "Your Reputation Is Who You're Not, Not Who You'd Like To Be," Penn CARESS Working Papers bb1b279d6539c9ed3b83a027c, Penn Economics Department.
    10. Van der Heijden, Eline C. M. & Nelissen, Jan H. M. & Potters, Jan J. M. & Verbon, Harrie A. A., 1998. "The poverty game and the pension game: The role of reciprocity," Journal of Economic Psychology, Elsevier, vol. 19(1), pages 5-41, February.
    11. Kraus, Florian & Puhani, Patrick A. & Steiner, Viktor, 1997. "Employment Effects of Publicly Financed Training Programs The East German Experience," ZEW Discussion Papers 97-33, ZEW - Leibniz Centre for European Economic Research.
    12. Stefania Villa, 2005. "Determinants of growth in Italy. A time series analysis," Quaderni DSEMS 24-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    13. Bianco, Madga & Golinelli, Roberto & Parigi, Giuseppe, 2009. "Family firms and investments," MPRA Paper 19247, University Library of Munich, Germany.
    14. Amable, Bruno & Demmou, Lilas & Gatti, Donatella, 2007. "Employment Performance and Institutions: New Answers to an Old Question," IZA Discussion Papers 2731, Institute of Labor Economics (IZA).
    15. Landiyanto, Erlangga Agustino & Wardaya, Wirya, 2005. "Pertumbuhan dan Konvergensi pada Industri Tebu di Asia Tenggara [Growth and Convergence of Sugarcare Industries in Southeast Asia]," MPRA Paper 2723, University Library of Munich, Germany, revised Mar 2007.
    16. Lisandro Abrego & Carlo Perroni, 2002. "Investment subsidies and Time-Consistent Environmental Policy," Oxford Economic Papers, Oxford University Press, vol. 54(4), pages 617-635, October.
    17. E. Galdon-Sanchez, Jose & Guell, Maia, 2003. "Dismissal conflicts and unemployment," European Economic Review, Elsevier, vol. 47(2), pages 323-335, April.
    18. Boiscuvier, Éléonore, 2001. "Innovation, intégration et développement régional," L'Actualité Economique, Société Canadienne de Science Economique, vol. 77(2), pages 255-280, juin.
    19. David E. A. Giles & Chad Stroomer, 2003. "Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence," Econometrics Working Papers 0307, Department of Economics, University of Victoria.
    20. Estache, A. & Gonzalez, M. & Trujillo, L., 2007. "Government expenditure on education, health and infrastructure: a naive look at levels, outcomes and efficiency," Working Papers 07/03, Department of Economics, City University London.
    21. Davide Furceri, 2002. "Risk-sharing e architettura istituzionale delle politiche di stabilizzazione nell'UME: aspetti metodologici e verifica empirica," Rivista di Politica Economica, SIPI Spa, vol. 92(6), pages 175-210, November-.
    22. Amable, Bruno & Gatti, Donatella, 2001. "The Impact of Product Market Competition on Employment and Wages," IZA Discussion Papers 276, Institute of Labor Economics (IZA).
    23. Choi, Jae-Young & Ratti, Ronald A., 2000. "The Predictive Power of Alternative Indicators of Monetary Policy," Journal of Macroeconomics, Elsevier, vol. 22(4), pages 581-610, October.
    24. Stèphane Dees, 1998. "Foreign Direct Investment in China: Determinants and Effects," Economic Change and Restructuring, Springer, vol. 31(2), pages 175-194, May.
    25. Paul Brenton & Francesca Di Mauro & Matthias Lücke, 1999. "Economic Integration and FDI: An Empirical Analysis of Foreign Investment in the EU and in Central and Eastern Europe," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 26(2), pages 95-121, June.
    26. Mr. Tonny Lybek, 1999. "Central Bank Autonomy, and Inflation and Output Performance in the Baltic States, Russia, and Other Countries of the Former Soviet Union, 1995-1997," IMF Working Papers 1999/004, International Monetary Fund.
    27. Weizsäcker, Robert K. von, 1997. "Chancengleichheit, Statusmobilität und öffentliche Bildungsinvestitionen," Discussion Papers 557, Institut fuer Volkswirtschaftslehre und Statistik, Abteilung fuer Volkswirtschaftslehre.
    28. Orphanides, Athanasios & Rasche, Robert H & Lindsey, David E, 2005. "The Reform of October 1979: How it Happened and Why," CEPR Discussion Papers 4866, C.E.P.R. Discussion Papers.
    29. Richter, Marcel K. & Wong, Kam-Chau, 1999. "Computable preference and utility," Journal of Mathematical Economics, Elsevier, vol. 32(3), pages 339-354, November.
    30. Lee, B.C. & Longe-Akindemowo, O., 1998. "Regulatory Issues in Electronic Money: A Legal-Economics Analysis," Economics Working Papers wp98-02, School of Economics, University of Wollongong, NSW, Australia.
    31. Olaf, POSCH & Klaus, WAELDE, 2005. "Natural volatility, welfare and taxation," Discussion Papers (ECON - Département des Sciences Economiques) 2005009, Université catholique de Louvain, Département des Sciences Economiques.
    32. Amendola, M. & Froeschle, C. & Gaffard, J. -L. & Lega, E., 2001. "Round-about production, co-ordination failure, technological change, and the wage-employment dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 46(1), pages 1-22, September.
    33. Zigic, Kresimir, 2000. "Strategic trade policy, intellectual property rights protection, and North-South trade," Journal of Development Economics, Elsevier, vol. 61(1), pages 27-60, February.
    34. Jean-Raphael Chaponniere & Jean-Pierre Cling, 2009. "Vietnam's Export-Led Growth Model and Competition with China," Economie Internationale, CEPII research center, issue 118, pages 101-130.
    35. Lindbeck, Assar, 1998. "How Can Economic Policy Strike a Balance between Economic Efficiency and Income Equality?," Working Paper Series 505, Research Institute of Industrial Economics.
    36. Beyer, Jürgen, 2001. "One best way oder Varietät? Strategischer und organisatorischer Wandel von Großunternehmen im Prozess der Internationalisierung," MPIfG Discussion Paper 01/2, Max Planck Institute for the Study of Societies.
    37. Felipe Balmaceda, 2005. "Cooperation and Network Formation," Documentos de Trabajo 205, Centro de Economía Aplicada, Universidad de Chile.
    38. Stange, Henriette & Lissitsa, Alexej, 2003. "Russischer Agrarsektor im Aufschwung? Eine Analyse der technischen und Skaleneffizienz der Agrarunternehmen," IAMO Discussion Papers 52, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    39. Lukas Lengauer, 2004. "Sozioökonomische Veränderungen in der Vienna Region 1971-2001 - Ausgewählte Ergebnisse," SRE-Disc sre-disc-2004_06, Institute for Multilevel Governance and Development, Department of Socioeconomics, Vienna University of Economics and Business.
    40. Hofer, Helmut & Huber, Peter, 2001. "Wage and Mobility Effects of Trade and Migration on the Austrian Labour Market," Economics Series 97, Institute for Advanced Studies.
    41. Sachin Zodgekar, 1996. "Netting and payments finality: proposed changes to the law," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 59, September.
    42. Davide Furceri, 2004. "Does the EMU Need a Fiscal Transfer Mechanism?," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 73(3), pages 418-428.
    43. Jenny Ploeg & Lori Campbell & Margaret Denton & Anju Joshi & Sharon Davies, 2003. "Helping to Build and Rebuild Secure Lives and Futures: Intergenerational Financial Transfers from Parents to Adult Children and Grandchildren," Social and Economic Dimensions of an Aging Population Research Papers 96, McMaster University.
    44. Camilla Froyn, 2005. "Decision Criteria, Scientific Uncertainty, and the Globalwarming Controversy," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 10(2), pages 183-211, April.
    45. Marika Karanassou & Hector Sala & Dennis J. Snower, 2002. "Unemployment in the European Union: A Dynamic Reappraisal," Working Papers 480, Queen Mary University of London, School of Economics and Finance.
    46. Koen De Backer & Leo Sleuwaegen, 2003. "Does Foreign Direct Investment Crowd Out Domestic Entrepreneurship?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 22(1), pages 67-84, February.
    47. Rosenbrock, Rolf & Schaeffer, Doris & Dubois-Arber, Francoise & Moers, Martin & Pinell, Patrice & Setbon, Michel, 1999. "Die Normalisierung von Aids in Westeuropa: Der Politik-Zyklus am Beispiel einer Infektionskrankheit," Discussion Papers, Research Group Public Health P 99-201, WZB Berlin Social Science Center.
    48. Clark, Andrew E. & Loheac, Youenn, 2007. ""It wasn't me, it was them!" Social influence in risky behavior by adolescents," Journal of Health Economics, Elsevier, vol. 26(4), pages 763-784, July.
    49. Reiter, Sara Ann & Williams, Paul F., 2002. "The structure and progressivity of accounting research: the crisis in the academy revisited," Accounting, Organizations and Society, Elsevier, vol. 27(6), pages 575-607, August.
    50. Graziella Bertocchi, 2003. "Labor Market Institutions, International Capital Mobility, and the Persistence of Underdevelopment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(3), pages 637-650, July.
    51. Koen De Backer & Leo Sleuwaegen, 2005. "A closer look at the productivity advantage of foreign affiliates," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 12(1), pages 17-34.
    52. David Bailey & Helena Lenihan & Ajit Singh, 2009. "Lessons for African Economies from Irish and East Asian Industrial Policy," Journal of Industry, Competition and Trade, Springer, vol. 9(4), pages 357-382, December.
    53. Kurt Geppert & Martin Gornig & Andreas Stephan, 2003. "Regional productivity differences in the European Union - Theoretical predictions and empirical evidence," ERSA conference papers ersa03p171, European Regional Science Association.
    54. Felipe Balmaceda, 2004. "Network Formation and Cooperation," Econometric Society 2004 Latin American Meetings 208, Econometric Society.
    55. Li, Yao, 2007. "Capital liberalization, industrial agglomeration and wage inequality," MPRA Paper 11355, University Library of Munich, Germany, revised May 2008.
    56. Betts, Julian, 2000. "The Impact of School Resources on Women's Earnings and Educational Attainment: Findings from the National Longitudinal Survey of Young Women," University of California at San Diego, Economics Working Paper Series qt6nx050kp, Department of Economics, UC San Diego.
    57. Rita Asplund, 2005. "The Provision and Effects of Company Training: A Brief Review of the Literature," Nordic Journal of Political Economy, Nordic Journal of Political Economy, vol. 31, pages 47-73.

  207. Härdle, Wolfgang & Linton, O., 1995. "Nonparametric Regression," SFB 373 Discussion Papers 1995,29, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Susumu Imai & Neelam Jain, 2005. "Bayesian Estimation of Dynamic Discrete Choice Models," 2005 Meeting Papers 432, Society for Economic Dynamics.
    3. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Sperlich, Stefan & Tjøstheim, Dag & Yang, Lijian, 2002. "Nonparametric Estimation And Testing Of Interaction In Additive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 197-251, April.
    5. Arthur Lewbel & Oliver Linton, 2002. "Nonparametric Censored and Truncated Regression," Econometrica, Econometric Society, vol. 70(2), pages 765-779, March.
    6. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
    8. Christine A. Ribic & Thomas W. Miller, 1998. "Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(5), pages 685-698, June.
    9. Wichert, Laura & Wilke, Ralf A., 2005. "Application of a simple nonparametric conditional quantile function estimator in unemployment duration analysis," ZEW Discussion Papers 05-67, ZEW - Leibniz Centre for European Economic Research.
    10. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.
    11. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  208. Linton, O. B. & Härdle, Wolfgang, 1995. "Estimation of Additive Regression Models with Links," SFB 373 Discussion Papers 1995,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    2. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Kempe, Wolfram, 1997. "Das Arbeitsangebot verheirateter Frauen in den neuen und alten Bundesländern: Eine semiparametrische Regressionsanalyse," SFB 373 Discussion Papers 1997,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    6. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Härdle, Wolfgang & Sperlich, Stefan & Spokoiny, Vladimir G., 1997. "Component analysis for additive models," SFB 373 Discussion Papers 1997,52, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  209. Linton, O. B. & Chen, R. & Härdle, Wolfgang, 1995. "An Analysis of Transformations for Additive Nonparanetric Regression," SFB 373 Discussion Papers 1995,68, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chen, Xiaohong & Linton, Oliver & Van Keilegom, Ingrid, 2003. "Estimation of semiparametric models when the criterion function is not smooth," LSE Research Online Documents on Economics 2167, London School of Economics and Political Science, LSE Library.
    2. Hess, Sebastian & Cramon-Taubadel, Stephan von & Sperlich, 2010. "Numbers for Pascal: Explaining differences in the Estimated Benefited of the Doha Developing Agenda," Department of Agricultural and Rural Development (DARE) Discussion Papers 187311, Georg-August-Universitaet Goettingen, Department of Agricultural Economics and Rural Development (DARE).
    3. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    4. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    5. Politis, Dimitris N, 2010. "Model-free Model-fitting and Predictive Distributions," University of California at San Diego, Economics Working Paper Series qt67j6s174, Department of Economics, UC San Diego.
    6. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    7. Lawrence Dacuycuy, 2006. "Explaining male wage inequality in the Philippines: non-parametric and semiparametric approaches," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2497-2511.
    8. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    9. J. S. Allison & M. Hušková & S. G. Meintanis, 2018. "Testing the adequacy of semiparametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 70-94, March.
    10. Fryzlewicz, Piotr & Delouille, V´eronique & Nason, Guy P., 2007. "GOES-8 X-ray sensor variance stabilization using the multiscale data-driven Haar-Fisz transform," LSE Research Online Documents on Economics 25221, London School of Economics and Political Science, LSE Library.

  210. Bossaerts, P. & Härdle, Wolfgang & Hafner, C., 1995. "A New Method for Volatility Estimation with Applications in Foreign Exchange Rate Series," SFB 373 Discussion Papers 1995,45, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Bossaerts, P.L.M. & Hillion, P., 1995. "Local Parametric Analysis of Hedging in Discrete Time," Discussion Paper 1995-23, Tilburg University, Center for Economic Research.
    2. Bossaerts, P.L.M. & Hillion, P., 1995. "Local Parametric Analysis of Hedging in Discrete Time," Other publications TiSEM 77cdfe27-8732-4f09-bf89-f, Tilburg University, School of Economics and Management.
    3. Lu, Zudi & Jiang, Zhenyu, 2001. "L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term," Statistics & Probability Letters, Elsevier, vol. 51(2), pages 121-130, January.
    4. Bossaerts, Peter & Hillion, Pierre, 1997. "Local parametric analysis of hedging in discrete time," Journal of Econometrics, Elsevier, vol. 81(1), pages 243-272, November.

  211. Härdle, Wolfgang & Tsybakov, A., 1995. "Local Polynomial Estimators of the Volatility Function in Nonparametric Autoregression," SFB 373 Discussion Papers 1995,42, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    2. Ke Yang, 2013. "An Improved Local-linear Estimator For Nonparametric Regression With Autoregressive Errors," Economics Bulletin, AccessEcon, vol. 33(1), pages 19-27.
    3. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2012. "Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory," Working Papers 13-05, Department of Economics, West Virginia University.
    4. Yujiao Yang & Yuhang Xu & Qiongxia Song, 2012. "Spline confidence bands for variance functions in nonparametric time series regressive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 699-714.
    5. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    6. Tschernig, Rolf & Yang, Lijian, 2000. "Nonparametric estimation of generalized impulse response function," SFB 373 Discussion Papers 2000,89, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Wolfgang Hardle & Torsten Kleinow & Alexander Korostelev & Camille Logeay & Eckhard Platen, 2008. "Semiparametric diffusion estimation and application to a stock market index," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 81-92.
    8. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
    9. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    10. Comte, F. & Rozenholc, Y., 2002. "Adaptive estimation of mean and volatility functions in (auto-)regressive models," Stochastic Processes and their Applications, Elsevier, vol. 97(1), pages 111-145, January.
    11. Tierney, Heather L.R., 2009. "Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data," MPRA Paper 17856, University Library of Munich, Germany.
    12. Peter Woehrmann & Willi Semmler & Martin Lettau, "undated". "Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models," IEW - Working Papers 225, Institute for Empirical Research in Economics - University of Zurich.
    13. Nicoleta Serban, 2008. "Estimating and clustering curves in the presence of heteroscedastic errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 553-571.
    14. Franke, Jürgen & Kreiss, Jens-Peter & Mammen, Enno, 1997. "Bootstrap of kernel smoothing in nonlinear time series," SFB 373 Discussion Papers 1997,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    15. Yipeng Yang & Allanus Tsoi, 2016. "A Level Set Analysis and A Nonparametric Regression on S&P 500 Daily Return," IJFS, MDPI, vol. 4(1), pages 1-24, February.
    16. Peter C.B. Phillips & Ke-Li Xu, 2007. "Tilted Nonparametric Estimation of Volatility Functions," Cowles Foundation Discussion Papers 1612, Cowles Foundation for Research in Economics, Yale University, revised Jul 2010.
    17. Pérez-González, A. & Vilar-Fernández, J.M. & González-Manteiga, W., 2010. "Nonparametric variance function estimation with missing data," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1123-1142, May.
    18. Heather L. R. Tierney, 2019. "Forecasting with the Nonparametric Exclusion-from-Core Inflation Persistence Model Using Real-Time Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(1), pages 39-63, February.
    19. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.
    20. Denis Chetverikov, 2012. "Adaptive test of conditional moment inequalities," CeMMAP working papers CWP36/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Francesco Audrino & Peter Bühlmann, 2007. "Splines for Financial Volatility," University of St. Gallen Department of Economics working paper series 2007 2007-11, Department of Economics, University of St. Gallen.
    22. Jianqing Fan, 2004. "A selective overview of nonparametric methods in financial econometrics," Papers math/0411034, arXiv.org.
    23. Tierney, Heather L.R., 2009. "Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation," MPRA Paper 22409, University Library of Munich, Germany, revised Feb 2010.
    24. Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
    25. Spokoiny, Vladimir, 2002. "Variance Estimation for High-Dimensional Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 82(1), pages 111-133, July.
    26. Yu, Zhuoxi & Wang, Dehui & Shi, Ningzhong, 2009. "Semiparametric estimation of regression functions in autoregressive models," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 165-172, January.
    27. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    28. Panagiotis Avramidis, 2016. "Adaptive likelihood estimator of conditional variance function," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 132-151, March.
    29. Feldmann, David & Härdle, Wolfgang Karl & Hafner, Christian M. & Hoffmann, Marc & Lepskii, Oleg V. & Tsybakov, Alexandre B., 1998. "Flexible stochastic volatility structures for high frequency financial data," SFB 373 Discussion Papers 1998,34, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    30. Polonik, Wolfgang & Yao, Qiwei, 2008. "Testing for multivariate volatility functions using minimum volume sets and inverse regression," LSE Research Online Documents on Economics 24132, London School of Economics and Political Science, LSE Library.
    31. P. G. Ferrario & H. Walk, 2012. "Nonparametric partitioning estimation of residual and local variance based on first and second nearest neighbours," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 1019-1039, December.
    32. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.
    33. Biqing Cai & Dag Tjøstheim, 2015. "Nonparametric Regression Estimation for Multivariate Null Recurrent Processes," Econometrics, MDPI, vol. 3(2), pages 1-24, April.
    34. Joseph Ngatchou-Wandji & Echarif Elharfaoui & Michel Harel, 2022. "On change-points tests based on two-samples U-Statistics for weakly dependent observations," Statistical Papers, Springer, vol. 63(1), pages 287-316, February.
    35. Xiangdong Long & Liangjun Su & Aman Ullah, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 109-125, January.
    36. Zhan-Qian Lu, 1999. "Multivariate Local Polynomial Fitting for Martingale Nonlinear Regression Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(4), pages 691-706, December.
    37. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    38. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    39. Paola Gloria Ferrario, 2018. "Partitioning estimation of local variance based on nearest neighbors under censoring," Statistical Papers, Springer, vol. 59(2), pages 423-447, June.
    40. Hoffmann, Marc, 1999. "On nonparametric estimation in nonlinear AR(1)-models," Statistics & Probability Letters, Elsevier, vol. 44(1), pages 29-45, August.
    41. Levine, M., 2006. "Bandwidth selection for a class of difference-based variance estimators in the nonparametric regression: A possible approach," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3405-3431, August.
    42. Jürgen Franke & Jean-Pierre Stockis & Joseph Tadjuidje, 2007. "Quantile Sieve Estimates For Time Series," SFB 649 Discussion Papers SFB649DP2007-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    43. Tierney, Heather L.R., 2009. "A Local Examination for Persistence in Exclusions-from-Core Measures of Inflation Using Real-Time Data," MPRA Paper 13383, University Library of Munich, Germany, revised 03 Feb 2009.
    44. Xu, Ke-Li & Phillips, Peter C. B., 2011. "Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 518-528.
    45. Josephine Njeri Ngure & Anthony Gichuhi Waititu, 2021. "Consistency of an Estimator for Change Point in Volatility of Financial Returns," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 13(1), pages 1-56, February.
    46. Joseph Ngatchou-Wandji & Marwa Ltaifa & Didier Alain Njamen Njomen & Jia Shen, 2022. "Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    47. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    48. Fabienne Comte, 2004. "Kernel deconvolution of stochastic volatility models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 563-582, July.
    49. Franses, Ph.H.B.F. & Neele, J. & van Dijk, D.J.C., 1998. "Modeling asymmetric volatility in weekly Dutch temperature data," Econometric Institute Research Papers EI 9840, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    50. Scholz, Achim & Neumeyer, Natalie & Munk, Axel, 2004. "Nonparametric Analysis of Covariance : the Case of Inhomogeneous and Heteroscedastic Noise," Technical Reports 2004,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    51. Lu, Zudi & Jiang, Zhenyu, 2001. "L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term," Statistics & Probability Letters, Elsevier, vol. 51(2), pages 121-130, January.
    52. Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
    53. Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
    54. Denis Chetverikov, 2012. "Testing regression monotonicity in econometric models," CeMMAP working papers CWP35/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    55. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    56. Denis Chetverikov, 2012. "Adaptive test of conditional moment inequalities," CeMMAP working papers 36/12, Institute for Fiscal Studies.
    57. Chronopoulos, Ilias & Kapetanios, George & Petrova, Katerina, 2021. "Kernel-based Volatility Generalised Least Squares," Econometrics and Statistics, Elsevier, vol. 20(C), pages 2-11.
    58. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2008. "Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility," Journal of Econometrics, Elsevier, vol. 143(2), pages 227-262, April.
    59. Polonik, Wolfgang & Yao, Qiwei, 2008. "Testing for multivariate volatility functions using minimum volume sets and inverse regression," Journal of Econometrics, Elsevier, vol. 147(1), pages 151-162, November.
    60. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.
    61. Michael Wegener & Göran Kauermann, 2008. "Examining heterogeneity in implied equity risk premium using penalized splines," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 35-56, February.
    62. Neumann, Michael H., 1997. "On robustness of model-based bootstrap schemes in nonparametric time series analysis," SFB 373 Discussion Papers 1997,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    63. Li, Degui & Li, Runze, 2016. "Local composite quantile regression smoothing for Harris recurrent Markov processes," Journal of Econometrics, Elsevier, vol. 194(1), pages 44-56.
    64. Véronique Delouille & Rainer Sachs, 2005. "Estimation of nonlinear autoregressive models using design-adapted wavelets," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(2), pages 235-253, June.
    65. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    66. Christophe Chesneau & Salima El Kolei & Junke Kou & Fabien Navarro, 2019. "Nonparametric estimation in a regression model with additive and multiplicative noise," Papers 1906.07695, arXiv.org, revised Jun 2020.
    67. T. Palanisamy & J. Ravichandran, 2015. "A wavelet-based hybrid approach to estimate variance function in heteroscedastic regression models," Statistical Papers, Springer, vol. 56(3), pages 911-932, August.
    68. Mohamed Salah Eddine Arrouch & Echarif Elharfaoui & Joseph Ngatchou-Wandji, 2023. "Change-Point Detection in the Volatility of Conditional Heteroscedastic Autoregressive Nonlinear Models," Mathematics, MDPI, vol. 11(18), pages 1-31, September.
    69. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    70. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    71. A. Pérez-González & J. Vilar-Fernández & W. González-Manteiga, 2009. "Asymptotic properties of local polynomial regression with missing data and correlated errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 85-109, March.
    72. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Feb 2017.
    73. Chaouch, Mohamed, 2019. "Volatility estimation in a nonlinear heteroscedastic functional regression model with martingale difference errors," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 129-148.
    74. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    75. Haag, Berthold R. & Hoderlein, Stefan & Pendakur, Krishna, 2009. "Testing and imposing Slutsky symmetry in nonparametric demand systems," Journal of Econometrics, Elsevier, vol. 153(1), pages 33-50, November.
    76. Yipeng Yang & Allanus Tsoi, 2013. "Prospect Agents and the Feedback Effect on Price Fluctuations," Papers 1308.6759, arXiv.org, revised Jan 2014.
    77. Mukherjee, Kanchan, 2007. "Generalized R-estimators under conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 141(2), pages 383-415, December.
    78. Franke Jürgen & Diagne Mabouba, 2006. "Estimating market risk with neural networks," Statistics & Risk Modeling, De Gruyter, vol. 24(2), pages 1-21, December.

  212. Härdle, Wolfgang & Chen, R., 1995. "Nonparametric Time Series Analysis, a selectiv review with examples," SFB 373 Discussion Papers 1995,14, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    2. Sami MESTIRI, 2022. "Modeling the volatility of Bitcoin returns using Nonparametric GARCH models," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 2-16, June.
    3. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    5. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    7. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.

  213. Chen, R. & Härdle, Wolfgang & Linton, O. B. & Severance-Lossin, E., 1995. "Nonparametric Estimation of Additive Seperable Regression Models," SFB 373 Discussion Papers 1995,50, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    2. Avalos, Marta & Grandvalet, Yves & Ambroise, Christophe, 2007. "Parsimonious additive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2851-2870, March.
    3. Morteza Haghiri & James Nolan & Kien Tran, 2004. "Assessing the impact of economic liberalization across countries: a comparison of dairy industry efficiency in Canada and the USA," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1233-1243.
    4. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    5. Kempe, Wolfram, 1997. "Das Arbeitsangebot verheirateter Frauen in den neuen und alten Bundesländern: Eine semiparametrische Regressionsanalyse," SFB 373 Discussion Papers 1997,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Chèze-Payaud, Nathalie & Poggi, Jean-Michel & Portier, Bruno, 1998. "Estimation and test of linearity for a class of additive nonlinear models," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 189-201, September.
    7. Morteza Haghiri & Alireza Simchi, 2005. "An application of the residual deviance analysis in testing input separability restrictions," Applied Economics Letters, Taylor & Francis Journals, vol. 12(12), pages 755-758.
    8. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  214. Härdle, Wolfgang & Chen, R., 1995. "Estimation and Variable Selection in Additive Nonparametric Regression Models," SFB 373 Discussion Papers 1995,16, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Dette, Holger & von Lieres und Wilkau, Carsten, 2000. "Testing additivity by kernel based methods - what is a reasonable test?," Technical Reports 2000,39, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  215. Härdle, Wolfgang & Spokoiny, V. & Sperlich, S., 1995. "Semiparametric Single Index Versus Fixed Link Function Modelling," SFB 373 Discussion Papers 1995,21, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Jean Pinquet & Montserrat Guillén & Catalina Bolancé, 2008. "On the link between credibility and frequency premium," Post-Print hal-00361645, HAL.
    2. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.

  216. Horowitz, Joel & Hardle, Wolfgang, 1994. "Direct Semiparametric Estimation of Single-Index Models With Discrete Covariates," Working Papers 94-22, University of Iowa, Department of Economics.

    Cited by:

    1. Tue Gorgens & Joel L. Horowitz, 1996. "Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable," Econometrics 9603001, University Library of Munich, Germany.
    2. Joel L. Horowitz & Sokbae (Simon) Lee, 2002. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," CeMMAP working papers CWP21/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Jia Chen & Jiti Gao & Degui Li, 2011. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," Monash Econometrics and Business Statistics Working Papers 12/11, Monash University, Department of Econometrics and Business Statistics.
    4. Tue Gorgens, 2000. "Semiparametric Estimation of Single-Index Transition Intensities," Econometric Society World Congress 2000 Contributed Papers 0596, Econometric Society.
    5. Nese Yildiz, 2012. "Estimation of Binary Choice Models with Linear Index and Dummy Endogenous Variables," Koç University-TUSIAD Economic Research Forum Working Papers 1202, Koc University-TUSIAD Economic Research Forum.
    6. Zhou, Yahong, 2008. "Semiparametric estimation of a nonstationary panel data transformation model under symmetry," Economics Letters, Elsevier, vol. 99(1), pages 107-110, April.
    7. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2010. "Robust Data-Driven Inference for Density-Weighted Average Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1070-1083.
    8. Härdle, Wolfgang & Müller, Marlene, 1997. "Multivariate and semiparametric kernel regression," SFB 373 Discussion Papers 1997,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Chen, Songnian & Zhou, Yahong, 2007. "Estimating a generalized correlation coefficient for a generalized bivariate probit model," Journal of Econometrics, Elsevier, vol. 141(2), pages 1100-1114, December.
    10. Joel L. Horowitz, 1996. "Bootstrap Critical Values for Tests Based on the Smoothed Maximum Score Estimator," Econometrics 9603003, University Library of Munich, Germany.
    11. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    13. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    14. König, Anja, 1997. "Schätzen und Testen in semiparametrischen partiell linearen Modellen für die Paneldatenanalyse," Hannover Economic Papers (HEP) dp-208, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Delecroix, Michel & Härdle, Wolfgang & Hristache, Marian, 1997. "Efficient estimation in single-index regression," SFB 373 Discussion Papers 1997,37, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  217. Härdle, Wolfgang & Tsybakov, A. B., 1994. "Additive Nonparametric Regression on Principal Components," SFB 373 Discussion Papers 1994,39, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  218. Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Herwartz, Helmut & Reimers, Hans-Eggert, 2006. "Modelling the Fisher hypothesis: World wide evidence," Economics Working Papers 2006-04, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Liang, Hua & Härdle, Wolfgang, 1997. "Large sample theory of the estimation of the error distribution for a semiparametric model," SFB 373 Discussion Papers 1997,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Das, J.W.M. & Donkers, A.C.D., 1997. "How Certain are Dutch Households about Future Income? An Empirical Analysis," Other publications TiSEM d8aabd66-ddc7-4834-a157-e, Tilburg University, School of Economics and Management.
    5. Matthew Pritsker, 1997. "Nonparametric density estimation and tests of continuous time interest rate models," Finance and Economics Discussion Series 1997-26, Board of Governors of the Federal Reserve System (U.S.).
    6. Hjalmarsson, Erik, 2003. "Does the Black-Scholes formula work for electricity markets? A nonparametric approach," Working Papers in Economics 101, University of Gothenburg, Department of Economics.
    7. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    8. Martin Evans and David Lyons, 2001. "Time-Varying Liquidity in Foreign Exchange," Working Papers gueconwpa~01-01-11, Georgetown University, Department of Economics.
    9. Geng, Xin & Janssens, Wendy & Kramer, Berber, 2018. "Liquid milk: Cash Constraints and Recurring Savings among Dairy Farmers in Kenya," 2018 Annual Meeting, August 5-7, Washington, D.C. 273823, Agricultural and Applied Economics Association.
    10. Mark Broadie & Jérôme Detemple & Eric Ghysels & Olivier Torrès, 1996. "Nonparametric Estimation of American Options Exercise Boundaries and Call Prices," CIRANO Working Papers 96s-24, CIRANO.
    11. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    12. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    13. BERTINELLI, Luisito & STROBL, Eric, 2003. "Urbanization, urban concentration and economic growth in developing countries," LIDAM Discussion Papers CORE 2003076, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Koo, Bonsoo & Linton, Oliver, 2010. "Semiparametric estimation of locally stationary diffusion models," LSE Research Online Documents on Economics 58186, London School of Economics and Political Science, LSE Library.
    15. Raymond J Carroll & Oliver Linton & Enno Mammen & Zhijie Xiao, 2002. "More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors," STICERD - Econometrics Paper Series 435, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    17. Sabino da Silva Porto Junior & Eduardo Pontual Ribeiro, 2003. "Dinâmica Espacial da Renda Per capita e Crescimento Entre os Municípios da Região Nordeste do Brasil - uma Análise Markoviana," Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31st Brazilian Economics Meeting] e54, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    18. Fousekis, Panos & Lazaridis, Panagiotis, 2001. "Food Expenditure Patterns of the Urban and the Rural Households in Greece. A Kernel Regression Analysis," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 2(1), pages 1-16, January.
    19. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    20. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    21. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    22. Evenett, S. J. & Keller, W., 1994. "On Theories Explaining the Success of the Gravity Equation," Working papers 9713, Wisconsin Madison - Social Systems.
    23. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "A meta-analysis on the price elasticity of energy demand," Energy Policy, Elsevier, vol. 102(C), pages 549-568.
    24. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    25. Oliver Linton, 1996. "An Asymptotic Expansion in the Garch(1,1) Model," Cowles Foundation Discussion Papers 1118, Cowles Foundation for Research in Economics, Yale University.
    26. Emmanuel Saez, 2010. "Do Taxpayers Bunch at Kink Points?," American Economic Journal: Economic Policy, American Economic Association, vol. 2(3), pages 180-212, August.
    27. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 325-353, November.
    28. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.
    29. Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
    30. Gong, X. & van Soest, A.H.O. & Zhang, P., 2000. "Sexual Bias and Household Consumption : A Semiparametic Analysis of Engel curves in Rural China," Discussion Paper 2000-45, Tilburg University, Center for Economic Research.
    31. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada, "undated". "Exchange-rate forecasts with simultaneous nearest-neighbour methods: Evidence from the EMS," Working Papers 98-17, FEDEA.
    32. Ghysels, E. & Ng, S., 1996. "A Semi-Parametric Factor Model for Interest Rates," Cahiers de recherche 9612, Universite de Montreal, Departement de sciences economiques.
    33. Beggs Alan, 2009. "Learning in Bayesian Games with Binary Actions," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 9(1), pages 1-30, September.
    34. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 1999. "Nonparametric Modeling of the Anchoring Effect in an Unfolding Bracket Design," Other publications TiSEM cd55131c-178a-45fd-b101-e, Tilburg University, School of Economics and Management.
    35. Julián Andrada-Félix & Fernando Fernández-Rodríguez & María Dolores García-Artiles & Simón Sosvilla-Rivero, "undated". "An Empirical Evaluation of Non-Linear Trading Rules," Working Papers 2001-16, FEDEA.
    36. Feng Zhu, 2005. "A nonparametric analysis of the shape dynamics of the US personal income distribution: 1962-2000," BIS Working Papers 184, Bank for International Settlements.
    37. Gouriéroux, Christian & Monfort, Alain & Tenreiro, Carlos, 1994. "Kernel m-estimators : non parametric diagnostics for structural models," CEPREMAP Working Papers (Couverture Orange) 9405, CEPREMAP.
    38. Michael LaCour-Little & Michael Marschoun & Clark L. Maxam, 2002. "Improving Parametric Mortgage Prepayment Models with Non-parametric Kernel Regression," Journal of Real Estate Research, American Real Estate Society, vol. 24(3), pages 299-328.
    39. Knoppik, Christoph, 2004. "The Kernel-Location Approach - A New Non-parametric Approach to the Analysis of Download Nominal Rigidity in Micro Data," University of Regensburg Working Papers in Business, Economics and Management Information Systems 392, University of Regensburg, Department of Economics.
    40. Jean Pinquet & Montserrat Guillén & Catalina Bolancé, 2008. "On the link between credibility and frequency premium," Post-Print hal-00361645, HAL.
    41. Susanne M. Schennach, 2015. "A bias bound approach to nonparametric inference," CeMMAP working papers 71/15, Institute for Fiscal Studies.
    42. Reiss, Peter C. & Wolak, Frank A., 2003. "Structural Econometric Modeling: Rationales and Examples from Industrial Organization," Research Papers 1831, Stanford University, Graduate School of Business.
    43. Susanne M. Schennach & Halbert White & Karim Chalak, 2007. "Estimating average marginal effects in nonseparable structural systems," CeMMAP working papers CWP31/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    44. Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," LIDAM Discussion Papers CORE 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    45. McMillen, Daniel P., 2001. "Nonparametric Employment Subcenter Identification," Journal of Urban Economics, Elsevier, vol. 50(3), pages 448-473, November.
    46. Läuter, Henning & Liero, H., 1997. "Ill-posed inverse problems and their optimal regularization," SFB 373 Discussion Papers 1997,57, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    47. Wolfgang Hardle & Torsten Kleinow & Alexander Korostelev & Camille Logeay & Eckhard Platen, 2008. "Semiparametric diffusion estimation and application to a stock market index," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 81-92.
    48. Egger, Peter & Wamser, Georg, 2011. "The Impact of Controlled Foreign Company Legislation on Real Investments Abroad: A Two-dimensional Regression Discontinuity Des," CEPR Discussion Papers 8460, C.E.P.R. Discussion Papers.
    49. Gosoniu, L. & Vounatsou, P. & Sogoba, N. & Maire, N. & Smith, T., 2009. "Mapping malaria risk in West Africa using a Bayesian nonparametric non-stationary model," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3358-3371, July.
    50. Araújo, E., 2004. "Medindo o Impacto Regional da Política Monetária Brasileira: Uma Comparação entre as Regiões Nordeste e Sul," Insper Working Papers wpe_46, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    51. Ansgar Steland, 2002. "Nonparametric monitoring of financial time series by jump-preserving control charts," Statistical Papers, Springer, vol. 43(3), pages 401-422, July.
    52. Creemers, An & Aerts, Marc & Hens, Niel & Molenberghs, Geert, 2012. "A nonparametric approach to weighted estimating equations for regression analysis with missing covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 100-113, January.
    53. Federico M. Bandi & Peter C. B. Phillips, 2003. "Fully Nonparametric Estimation of Scalar Diffusion Models," Econometrica, Econometric Society, vol. 71(1), pages 241-283, January.
    54. Klaassen, F.J.G.M., 1999. "Purchasing Power Parity : Evidence from a New Test," Other publications TiSEM 91e73eb9-a023-4fdb-bd70-b, Tilburg University, School of Economics and Management.
    55. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Technical Working Papers 0337, National Bureau of Economic Research, Inc.
    56. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    57. B.U.PARK & Wolfgang HAERDLE, "undated". "Testing increasing dispersion," Statistic und Oekonometrie 9314, Humboldt Universitaet Berlin.
    58. Fabio Fornari & Antonio Mele, 2001. "Recovering the Probability Density Function of Asset Prices Using GARCH as Diffusion Approximations," Temi di discussione (Economic working papers) 396, Bank of Italy, Economic Research and International Relations Area.
    59. Eric Ghysels & Serena Ng, 1997. "A Semi-Parametric Factor Model of Interest Rates and Tests of the Affine Term Structure," CIRANO Working Papers 97s-33, CIRANO.
    60. Tierney, Heather L.R., 2009. "Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data," MPRA Paper 17856, University Library of Munich, Germany.
    61. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.
    62. Das, J.W.M. & Dominitz, J. & van Soest, A.H.O., 1997. "Comparing Predictions and Outcomes : Theory and Application to Income Changes," Other publications TiSEM 6eef11dd-0ae4-4673-b8c0-2, Tilburg University, School of Economics and Management.
    63. Joel L. Horowitz & Sokbae (Simon) Lee, 2004. "Nonparametric estimation of an additive quantile regression model," CeMMAP working papers CWP07/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    64. Das, J.W.M. & van Soest, A.H.O., 1995. "Expected and Realized Income Changes : Evidence From the Dutch Socio-Economic Panel," Other publications TiSEM cd97154d-b1fd-490e-9e30-7, Tilburg University, School of Economics and Management.
    65. Geweke, John F. & Horowitz, Joel L. & Pesaran, M. Hashem, 2006. "Econometrics: A Bird's Eye View," IZA Discussion Papers 2458, Institute of Labor Economics (IZA).
    66. Broadie, Mark & Detemple, Jerome & Ghysels, Eric & Torres, Olivier, 2000. "American options with stochastic dividends and volatility: A nonparametric investigation," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 53-92.
    67. Justin McCrary, 2007. "Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test," NBER Technical Working Papers 0334, National Bureau of Economic Research, Inc.
    68. Yan, Robert & Nuttall, John & Ling, Charles, 2006. "Application of machine learning to short-term equity return prediction," MPRA Paper 2536, University Library of Munich, Germany.
    69. Luisito Bertinelli & Eric Strobl & Benteng Zou, 2008. "Sustainable Economic Development and the Environment: Theory and Evidence," DEM Discussion Paper Series 08-06, Department of Economics at the University of Luxembourg.
    70. Austan Goolsbee & David B. Gross, 1997. "Estimating Adjustment Costs with Data on Heterogeneous Capital Goods," NBER Working Papers 6342, National Bureau of Economic Research, Inc.
    71. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2001. "Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach," Cahiers de recherche CREFE / CREFE Working Papers 143, CREFE, Université du Québec à Montréal.
    72. Norberto Rodríguez & Patricia Siado, 2003. "Un Pronóstico No Paramétrico De La Inflación Colombiana," Borradores de Economia 3691, Banco de la Republica.
    73. Martin D. D. Evans & Richard K. Lyons, 2001. "Portfolio Balance, Price Impact, and Secret Intervention," NBER Working Papers 8356, National Bureau of Economic Research, Inc.
    74. Boris A. Zürcher, 2004. "Income Inequality and Mobility: A Nonparametric Decomposition Analysis by Age for Switzerland in the 80s and 90s," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 140(II), pages 265-292, June.
    75. Antonio Acconcia & Daniel Montolio & Leone Leonida & Marta Espasa, 2002. "Lock-In Effects Of Eu R&D Spending On Regional Growth. A Non-Parametric And Semi-Parametric Conditional Quantile Regressions Approach," Working Papers. Serie EC 2002-12, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    76. Laurini, Márcio P., 2007. "A note on the use of quantile regression in beta convergence analysis," Insper Working Papers wpe_95, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    77. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical Analysis in Foreign Exchange Markets: Linear Versus Nonlinear Trading Rules," Working Papers on International Economics and Finance 00-02, FEDEA.
    78. Gregory Kordas, 2006. "Smoothed binary regression quantiles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 387-407.
    79. Charlier, E., 1997. "Equivalence Scales for the Former West Germany," Other publications TiSEM eed8f5af-8f69-445e-94df-d, Tilburg University, School of Economics and Management.
    80. Townsend, John P. & Brorsen, B. Wade, 2000. "Cost of Forward Contracting Hard Red Winter Wheat," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 32(1), pages 89-94, April.
    81. Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
    82. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    83. James Stephen MARRON & Wolfgang HAERDLE, "undated". "Fast and simple scatterplot smoothing," Statistic und Oekonometrie 9308, Humboldt Universitaet Berlin.
    84. Peter C.B. Phillips, 2008. "Local Limit Theory and Spurious Nonparametric Regression," Cowles Foundation Discussion Papers 1654, Cowles Foundation for Research in Economics, Yale University.
    85. Alexandra L. Minicozzi, 2003. "Estimation of sons' intergenerational earnings mobility in the presence of censoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 291-314.
    86. Juan Rodríguez-Poo & Oliver Linton, 2001. "Nonparametric factor analysis of residual time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(1), pages 161-182, June.
    87. A. de Palma & C. Fontan & O. Mekkaoui, 2000. "Trip Timing for Public Transportation : An Empirical Application," THEMA Working Papers 2000-19, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    88. Loader, Catherine, 2004. "Smoothing: Local Regression Techniques," Papers 2004,12, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    89. Susumu Imai & Neelam Jain, 2005. "Bayesian Estimation of Dynamic Discrete Choice Models," 2005 Meeting Papers 432, Society for Economic Dynamics.
    90. Jean-Yves Duclos & Joan Esteban & Debraj Ray, 2004. "Polarization: Concepts, Measurement, Estimation," Econometrica, Econometric Society, vol. 72(6), pages 1737-1772, November.
    91. Emili Tortosa Ausina & Diego Prior & María Teresa Balaguer-Coll, 2004. "On The Determinants Of Local Government Performance: A Two-Stage Nonparametric Approach," Working Papers. Serie EC 2004-04, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    92. Politis, Dimitris N, 2010. "Model-free Model-fitting and Predictive Distributions," University of California at San Diego, Economics Working Paper Series qt67j6s174, Department of Economics, UC San Diego.
    93. Steland, Ansgar, 2003. "Optimal sequential kernel detection for dependent processes," Technical Reports 2003,27, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    94. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    95. Cristian Aedo, "undated". "The Impact of Training Policies in Latin America and the Caribbean: The Case of "Programa Joven"," ILADES-UAH Working Papers inv131, Universidad Alberto Hurtado/School of Economics and Business.
    96. Azomahou, Théophile & Laisney, François & van Phu, Nguyen, 2005. "Economic Development and CO2 Emissions: A Nonparametric Panel Approach," ZEW Discussion Papers 05-56, ZEW - Leibniz Centre for European Economic Research.
    97. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    98. Foltz, Jeremy D. & Chang, Hsiu-Hui, 2001. "The Adoption and Profitability of rbST on Connecticut Dairy Farms," Research Reports 25168, University of Connecticut, Food Marketing Policy Center.
    99. Schennach, Susanne & White, Halbert & Chalak, Karim, 2012. "Local indirect least squares and average marginal effects in nonseparable structural systems," Journal of Econometrics, Elsevier, vol. 166(2), pages 282-302.
    100. Tierney, Heather L.R., 2009. "Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation," MPRA Paper 22409, University Library of Munich, Germany, revised Feb 2010.
    101. Stehle, Richard & Bunke, Olaf & Sommerfeld, Volker, 1997. "Semiparametric modelling of the cross-section of expected returns in the German stock market," SFB 373 Discussion Papers 1997,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    102. Gozalo, Pedro & Linton, Oliver, 2000. "Local nonlinear least squares: Using parametric information in nonparametric regression," Journal of Econometrics, Elsevier, vol. 99(1), pages 63-106, November.
    103. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
    104. J. B. Engberg & T. Kim, "undated". "Person or Place? Parametric and semiparametric estimates of intrametropolitan earnings variation," Institute for Research on Poverty Discussion Papers 1089-96, University of Wisconsin Institute for Research on Poverty.
    105. BARRIOS, Salvador & GOERG, Holger & STROBL, Eric, 2004. "Foreign direct investment, competition and industrial development in the host country," LIDAM Discussion Papers CORE 2004011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    106. Yacine Ait-Sahalia & Jialin Yu, 2009. "High frequency market microstructure noise estimates and liquidity measures," Papers 0906.1444, arXiv.org.
    107. Linton, Oliver, 2002. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," Journal of Econometrics, Elsevier, vol. 106(2), pages 325-368, February.
    108. Blow, Laura & Crawford, Ian, 2002. "A nonparametric method for valuing new goods," Working Paper Series 143, European Central Bank.
    109. Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    110. Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
    111. Martin D. D. Evans & Richard K. Lyons, 2000. "Are Different-Currency Assets Imperfect Substitutes?," Working Papers gueconwpa~00-00-05, Georgetown University, Department of Economics.
    112. Michael Falkenheim & George Pennacchi, 2003. "The Cost of Deposit Insurance for Privately Held Banks: A Market Comparable Approach," Journal of Financial Services Research, Springer;Western Finance Association, vol. 24(2), pages 121-148, October.
    113. Currie, Janet & Thomas, Duncan, 1995. "Does Head Start Make a Difference?," American Economic Review, American Economic Association, vol. 85(3), pages 341-364, June.
    114. Knoppik, Christoph, 2004. "Downward Nominal Rigidity in US Wage Data from the PSID - An Application of the Kernel-Location Approach," University of Regensburg Working Papers in Business, Economics and Management Information Systems 393, University of Regensburg, Department of Economics.
    115. Jean-Yves Duclos & Paul Makdissi & Abdelkrim Araar, 2010. "Pro-Poor Tax Reforms, with an Application to Mexico," Cahiers de recherche 1001, CIRPEE.
    116. Ph. Nguyen Van & Th. Azomahou, 2005. "Nonlinearties and heterogeneity in environmental quality : an empirical analysis of deforestation," THEMA Working Papers 2005-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    117. Sanghamitra Das & Ramprasad Sengupta, 2004. "Projection pursuit regression and disaggregate productivity effects: the case of the Indian blast furnaces," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(3), pages 397-418.
    118. André Luis Squarize Chagas & Rudinei Toneto & Carlos Roberto Azzoni, 2012. "A Spatial Propensity Score Matching Evaluation of the Social Impacts of Sugarcane Growing on Municipalities in Brazil," International Regional Science Review, , vol. 35(1), pages 48-69, January.
    119. Juan M. Vilar Fernández & Alejandro Quintela del Río, 1993. "Técnicas no paramétricas de estimación funcional, con observaciones dependientes," Investigaciones Economicas, Fundación SEPI, vol. 17(1), pages 143-163, January.
    120. Gorton, Gary & Schmid, Frank A., 2000. "Universal banking and the performance of German firms," Journal of Financial Economics, Elsevier, vol. 58(1-2), pages 29-80.
    121. Bunke, Olaf & Castell, Ernestina, 1998. "Regression and contrast estimated based on adaptive regressograms depending on qualitative explanatory variables," SFB 373 Discussion Papers 1998,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    122. Steland, Ansgar, 2003. "Jump-preserving monitoring of dependent time series using pilot estimators," Technical Reports 2004,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    123. Dette, Holger & Birke, Melanie, 2005. "Estimating a convex function in nonparametric regression," Technical Reports 2005,21, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    124. Néstor Duch-Brown & José García-Quevedo & Daniel Montolio, 2011. "The link between public support and private r&d effort: what is the optimal subsidy?," Working Papers 2011/12, Institut d'Economia de Barcelona (IEB).
    125. Théophile T. Azomahou & Bity Diene & Mbaye Diene, 2009. "Technology frontier, labor productivity and economic growth: Evidence from OECD countries," DEM Discussion Paper Series 09-19, Department of Economics at the University of Luxembourg.
    126. Datt, Gaurav & Jolliffe, Dean, 1999. "Determinants of Poverty in Egypt," FCND briefs 2, International Food Policy Research Institute (IFPRI).
    127. Joseph Cooper & Carl Zulauf & Michael Langemeier & Gary Schnitkey, 2012. "Implications of within county yield heterogeneity for modeling crop insurance premiums," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(1), pages 134-155, May.
    128. Bocart, Fabian & Hafner, Christian, 2012. "Econometric analysis of volatile art markets," LIDAM Reprints ISBA 2012020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    129. Arribas Fernández Iván & Pérez García Francisco & Tortosa-Ausina Emili, 2008. "On the Dynamics of Globalization," Working Papers 201088, Fundacion BBVA / BBVA Foundation.
    130. Yun, Myeong-Su, 1999. "Generalized Selection Bias and The Decomposition of Wage Differentials," IZA Discussion Papers 69, Institute of Labor Economics (IZA).
    131. Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation for Research in Economics, Yale University.
    132. Richard Blundell & Frank Windmeijer, 2000. "Identifying demand for health resources using waiting times information," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 465-474, September.
    133. R M Rejesus, 2003. "Ex post Moral Hazard in Crop Insurance: Costly State Verification or Falsification?," Economic Issues Journal Articles, Economic Issues, vol. 8(2), pages 29-46, September.
    134. Datt, Gaurav & Jolliffe, Dean & Sharma, Manohar, 1998. "A profile of poverty in Egypt: 1997," FCND discussion papers 49, International Food Policy Research Institute (IFPRI).
    135. Indrani Chakraborty, 2010. "Living Standard and Economic Growth: A Fresh Look at the Relationship Through The Nonparametric Approach," Working Papers id:3161, eSocialSciences.
    136. Kempe, Wolfram, 1997. "Das Arbeitsangebot verheirateter Frauen in den neuen und alten Bundesländern: Eine semiparametrische Regressionsanalyse," SFB 373 Discussion Papers 1997,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    137. Hansen,B.E., 1999. "Testing for linearity," Working papers 7, Wisconsin Madison - Social Systems.
    138. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
    139. Heinz König & Michael Lechner, 1994. "Some Recent Developments in Microeconometrics - A Survey," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(III), pages 299-331, September.
    140. Mammen, Enno & Linton, Oliver & Nielsen, J, 2000. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 2315, London School of Economics and Political Science, LSE Library.
    141. Michael Jacobs, Jr, 2011. "An option theoretic model for ultimate loss-given-default with systematic recovery risk and stochastic returns on defaulted debt," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 257-285, Bank for International Settlements.
    142. Fengxia Dong & Allen Featherstone, 2004. "Technical and Scale Efficiencies for Chinese Rural Credit Cooperatives: A Bootstrapping Approach in Data Envelopment Analysis," Center for Agricultural and Rural Development (CARD) Publications 04-wp366, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    143. Hübler Olaf, 2005. "Sind betriebliche Bündnisse für Arbeit erfolgreich? / Are ln-plant Alliances for Job Security Successful?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(6), pages 630-652, December.
    144. Ciriaci, Daria & Palma, Daniela, 2010. "Geography, environmental efficiency and Italian economic growth: a spatially-adapted Environmental Kuznets Curve," MPRA Paper 22899, University Library of Munich, Germany.
    145. Scheder, Regine & Dette, Holger, 2005. "Strictly monotone and smooth nonparametric regression for two or more variables," Technical Reports 2005,17, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    146. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    147. Connor, Gregory & Korajczyk, Robert A. & Linton, Oliver, 2006. "The common and specific components of dynamic volatility," Journal of Econometrics, Elsevier, vol. 132(1), pages 231-255, May.
    148. David E. A. Giles & Betty J. Johnson, 2000. "Taxes, Risk-Aversion, and the Size of the Underground Economy: A Nonparametric Analysis With New Zealand Data," Econometrics Working Papers 0006, Department of Economics, University of Victoria.
    149. Bart Capéau & Philip Verwimp, 2012. "Dictatorship in a single export crop economy," Journal of Theoretical Politics, , vol. 24(2), pages 210-234, April.
    150. Stoker, Thomas M., 1987. "Equivalence of direct and indirect estimators of average derivatives," Working papers 1961-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    151. Chen, Songnian, 2000. "Rank estimation of a location parameter in the binary choice model," Journal of Econometrics, Elsevier, vol. 98(2), pages 317-334, October.
    152. Carlos Lamarche & Alberto Porto & Walter Sosa Escudero, 1998. "Aspectos Regionales del Desempleo en la Argentina," IIE, Working Papers 008, IIE, Universidad Nacional de La Plata.
    153. Laurini, Márcio P. & Moura, Marcelo, 2007. "Constrained Smoothing Splines for the Term Structure of Interest Rates," Insper Working Papers wpe_100, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    154. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    155. Hidalgo, Javier & Lee, Jungyoon & Seo, Myung Hwan, 2019. "Robust inference for threshold regression models," Journal of Econometrics, Elsevier, vol. 210(2), pages 291-309.
    156. Livanis, Grigorios T. & Salois, Matthew J. & Moss, Charles B., 2009. "A Nonparametric Kernel Representation of the Agricultural Production Function: Implications for Economic Measures of Technology," 83rd Annual Conference, March 30 - April 1, 2009, Dublin, Ireland 51063, Agricultural Economics Society.
    157. Viviana Fernández, 1999. "Estructura de Tasas de Interés en Chile: La Vía No Paramétrica," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 36(109), pages 1005-1034.
    158. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    159. Linton, Oliver, 1996. "Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 12(1), pages 30-60, March.
    160. Galina Besstremyannaya & Jaak Simm, 2014. "Multi-payer health insurance systems in Central and Eastern Europe: lessons from the Czech Republic, Slovakia, and Russia," Working Papers w0203, Center for Economic and Financial Research (CEFIR).
    161. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    162. M. M. Salinas-Jimenez, 2003. "Technological change, efficiency gains and capital accumulation in labour productivity growth and convergence: an application to the Spanish regions," Applied Economics, Taylor & Francis Journals, vol. 35(17), pages 1839-1851.
    163. Cristian Aedo & Sergio Nuñez, 2004. "Efectos de las políticas de capacitación en América Latina y el Caribe: el caso del Programa Joven," Research Department Publications 3176, Inter-American Development Bank, Research Department.
    164. Abadir, Karim M. & Lawford, Steve, 2004. "Optimal asymmetric kernels," Economics Letters, Elsevier, vol. 83(1), pages 61-68, April.
    165. Michael B. Gordy, "undated". "Multiple Bids in a Multiple-Unit Common Value Auction," Computing in Economics and Finance 1996 _021, Society for Computational Economics.
    166. Chung-Ming Kuan & Christos Michalopoulos & Zhijie Xiao, 2017. "Quantile Regression on Quantile Ranges – A Threshold Approach," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 99-119, January.
    167. Yuichi Kitamura & Louise Laage, 2018. "Nonparametric Analysis of Finite Mixtures," Papers 1811.02727, arXiv.org.
    168. Dora L. Costa, 1999. "American Living Standards: Evidence from Recreational Expenditures," NBER Working Papers 7148, National Bureau of Economic Research, Inc.
    169. Chris Downing & Steven A. Sharpe, 2003. "Getting bad news out early: does it really help stock prices?," Finance and Economics Discussion Series 2003-58, Board of Governors of the Federal Reserve System (U.S.).
    170. John W. Galbraith, 1999. "Content Horizons For Forecasts Of Economic Time Series," Departmental Working Papers 1999-01, McGill University, Department of Economics.
    171. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 1999. "Nonparametric Bounds on the Income Distribution in the Presence of Item Nonresponse," Discussion Paper 1999-33, Tilburg University, Center for Economic Research.
    172. Denis Fougère & Bruno Crépon & Thomas Brodaty, 2007. "Les méthodes micro-économétriques d'évaluation et leurs applications aux politiques actives de l'emploi," Économie et Prévision, Programme National Persée, vol. 177(1), pages 93-118.
    173. Galina Besstremyannaya & Jaak Simm, 2012. "The impact of private health insurers on the quality of Russian regional health systems," Working Papers w0177, Center for Economic and Financial Research (CEFIR).
    174. Schady, Norbert R., 1999. "Seeking votes - the political economy of expenditures by the Peruvian Social Fund (FONCODES), 1991-95," Policy Research Working Paper Series 2166, The World Bank.
    175. Márcio Laurini & Eduardo Andrade, 2004. "Income Convergence Clubs for Brazilian Municipalities: a Non-Parametric Analysis," Econometric Society 2004 Latin American Meetings 51, Econometric Society.
    176. David C. Wheelock & Paul W. Wilson, 1997. "New evidence on returns to scale and product mix among U.S. commercial banks," Working Papers 1997-003, Federal Reserve Bank of St. Louis.
    177. Janet Currie & Duncan Thomas, 1995. "Race, Children's Cognitive Achievement and The Bell Curve," NBER Working Papers 5240, National Bureau of Economic Research, Inc.
    178. Pedro Delicado & Ana Justel, 1997. "Forecasting with missing data: Application to a real case," Economics Working Papers 213, Department of Economics and Business, Universitat Pompeu Fabra.
    179. GHYSELS, Eric & PATILEA, Valentin & RENAULT, Eric & TORRES, Olivier, 1997. "Nonparametric methods and option pricing," LIDAM Discussion Papers CORE 1997075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    180. Jinyong Hahn & Petra Todd & Wilbert Van der Klaauw, 1999. "Evaluating the Effect of an Antidiscrimination Law Using a Regression-Discontinuity Design," NBER Working Papers 7131, National Bureau of Economic Research, Inc.
    181. Pedro Gozalo & Oliver Linton, 1994. "Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically," Cowles Foundation Discussion Papers 1075, Cowles Foundation for Research in Economics, Yale University.
    182. Burkhauser, Richard V. & Amy Crews Cutts & Mary C. Daly & Stephen P. Jenkins, 1999. "Testing the Significance of Income Distribution Changes over the 1980s Business Cycle: A Cross-National Comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 253-272, May-June.
    183. Breunig, Robert & Dasgupta, Indraneel & Gundersen, Craig & Pattanaik, Prasanta, 2001. "Explaining The Food Stamp Cash-Out Puzzle," Food Assistance and Nutrition Research Reports 33869, United States Department of Agriculture, Economic Research Service.
    184. Tierney, Heather L.R., 2009. "A Local Examination for Persistence in Exclusions-from-Core Measures of Inflation Using Real-Time Data," MPRA Paper 13383, University Library of Munich, Germany, revised 03 Feb 2009.
    185. Andrew Jeffrey & Linton, Oliver Linton & Thong Nguyen & Peter C.B. Phillips, 2001. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Cowles Foundation Discussion Papers 1311, Cowles Foundation for Research in Economics, Yale University.
    186. Meise, Monika & Davies, Paul Lyndon, 2005. "Approximating data with weighted smoothing splines," Technical Reports 2005,48, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    187. Maria Fraga O. Martins, 2001. "Parametric and semiparametric estimation of sample selection models: an empirical application to the female labour force in Portugal," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(1), pages 23-39.
    188. Livio Di Matteo, 2016. "Wealth Distribution and the Canadian Middle Class: Historical Evidence and Policy Implications," Canadian Public Policy, University of Toronto Press, vol. 42(2), pages 132-151, June.
    189. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Testing Chaotic Dynamics via Lyapunov Exponents," Working Papers 2000-07, FEDEA.
    190. Petra E. Todd & Kenneth I. Wolpin, 2008. "Ex Ante Evaluation of Social Programs," Annals of Economics and Statistics, GENES, issue 91-92, pages 263-291.
    191. Peter C.B. Phillips, 1999. "Descriptive Econometrics for Nonstationary Time Series with Empirical Illustrations," Cowles Foundation Discussion Papers 1219, Cowles Foundation for Research in Economics, Yale University.
    192. Nicholas Z. Muller, 2007. "Using Hedonic Property Models to Value Public Water Bodies: A Note Regarding Specification Issues," Middlebury College Working Paper Series 0721, Middlebury College, Department of Economics.
    193. Paudel, Krishna P. & Zapata, Hector O., 2004. "Two Methods Of Estimating Semiparametric Component In The Environmental Kuznet'S Curve (Ekc)," 2004 Annual Meeting, February 14-18, 2004, Tulsa, Oklahoma 34598, Southern Agricultural Economics Association.
    194. Melser, Daniel & Syed, Iqbal, 2007. "Life Cycle Pricing and the Measurement of Inflation," MPRA Paper 16722, University Library of Munich, Germany, revised 07 Jul 2008.
    195. Bunke, Olaf, 1998. "Semiparametric estimation and prediction for time series cross sectional data," SFB 373 Discussion Papers 1998,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    196. Matthias R. Fengler, 2005. "Arbitrage-Free Smoothing of the Implied Volatility Surface," SFB 649 Discussion Papers SFB649DP2005-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    197. Barrios, Erniel B. & Sobrevinas, Alellie B., 2012. "Impact of the Rice Trade Policy Reforms on Household Welfare in the Philippines," Philippine Journal of Development PJD 2010 Vol. 37 No. 1b, Philippine Institute for Development Studies.
    198. Olivier RENAULT & Olivier SCAILLET, 2003. "On the Way to Recovery: A Nonparametric Bias Free Estimation of Recovery Rate Densities," FAME Research Paper Series rp83, International Center for Financial Asset Management and Engineering.
    199. VAN KERM Philippe, 2006. "Comparisons of income mobility profiles," IRISS Working Paper Series 2006-03, IRISS at CEPS/INSTEAD.
    200. Philip Burns & Ian Crawford & Andrew Dilnot, 1995. "Regulation and redistribution in utilities," Fiscal Studies, Institute for Fiscal Studies, vol. 16(4), pages 1-22, January.
    201. Härdle, Wolfgang & Müller, Marlene, 1997. "Multivariate and semiparametric kernel regression," SFB 373 Discussion Papers 1997,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    202. Nowman, K. Ben & Saltoglu, Burak, 2003. "Continuous time and nonparametric modelling of U.S. interest rate models," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 25-34.
    203. Palmquist, Raymond B., 2006. "Property Value Models," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 16, pages 763-819, Elsevier.
    204. Tang Qingguo, 2009. "Asymptotic normality of M-estimators in a semiparametric model with longitudinal data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 69(1), pages 55-67, January.
    205. Richard, Jean-François, 2000. "Conférence François-Albert Angers (1999). Enchères : théorie économique et réalité," L'Actualité Economique, Société Canadienne de Science Economique, vol. 76(2), pages 173-198, juin.
    206. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    207. Bertschek, Irene & Lechner, Michael, 1998. "Convenient estimators for the panel probit model," Journal of Econometrics, Elsevier, vol. 87(2), pages 329-371, September.
    208. Nicholas Z. Muller & Peter C. B. Phillips, 2006. "Sinusoidal Modeling Applied to Spatially Variant Tropospheric Ozone Air Pollution," Cowles Foundation Discussion Papers 1548, Cowles Foundation for Research in Economics, Yale University.
    209. Bertinelli, Luisito & Strobl, Eric & Zou, Benteng, 2011. "Sustainable economic development and the environment," Center for Mathematical Economics Working Papers 369, Center for Mathematical Economics, Bielefeld University.
    210. Hidehiko Ichimura, "undated". "Asymptotic Distribution of Non-Parametric and Semi-Parametric Estimators with Data Dependent Smoothing Parameters," Working Papers _001, University of California at Berkeley, Econometrics Laboratory Software Archive.
    211. Mahmood, Ishtiaq P. & Zheng, Weiting, 2009. "Whether and how: Effects of international joint ventures on local innovation in an emerging economy," Research Policy, Elsevier, vol. 38(9), pages 1489-1503, November.
    212. Steve Gibbons & Stephen Machin, 2001. "Valuing Primary Schools," CEE Discussion Papers 0015, Centre for the Economics of Education, LSE.
    213. Dette, Holger & Ziggel, Daniel, 2006. "Discount curve estimation by monotonizing McCulloch Splines," Technical Reports 2006,27, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    214. David J. Vanness, 2003. "A structural econometric model of family valuation and choice of employer‐sponsored health insurance in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 12(9), pages 771-790, September.
    215. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    216. Mahmood, Ishtiaq P. & Mitchell, Will, 2002. "Two Faces: Effects of Business Groups on Innovation in Emerging Economies," CEI Working Paper Series 2002-14, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    217. Yannis M. Ioannides & Henry G. Overman, 2000. "Zipf's Law for Cities: An Explanation," Discussion Papers Series, Department of Economics, Tufts University 0006, Department of Economics, Tufts University.
    218. Opoku-Agyemang, Kweku A., 2017. "Priming human-computer interactions: Experimental evidence from economic development mobile surveys," SocArXiv 6bwxv, Center for Open Science.
    219. Marcel Fafchamps & Chris Udry & Katherine Czukas, "undated". "Drought and Saving in West Africa: Are Livestock a Buffer Stock?," Working Papers 97013, Stanford University, Department of Economics.
    220. Elena Krasnokutskaya, 2004. "Identification and Estimation in Highway Procurement Auctions under Unobserved Auction Heterogeneity," PIER Working Paper Archive 05-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    221. Rama CONT, 1998. "Beyond implied volatility: extracting information from option prices," Finance 9804002, University Library of Munich, Germany.
    222. Easterly, William, 1999. "Life during growth : international evidence on quality of life and per capita income," Policy Research Working Paper Series 2110, The World Bank.
    223. Cristian Aedo & Sergio Nuñez, 2004. "The Impact of Training Policies in Latin America and the Caribbean: The Case of Programa Joven," Research Department Publications 3175, Inter-American Development Bank, Research Department.
    224. Galina Besstremyannaya, 2014. "Urban inequity in the performance of social health insurance system: evidence from Russian regions," Working Papers w0204, Center for Economic and Financial Research (CEFIR).
    225. Jürgen Maurer, 2007. "Modelling socioeconomic and health determinants of health‐care use: a semiparametric approach," Health Economics, John Wiley & Sons, Ltd., vol. 16(9), pages 967-979, September.
    226. J. S. Marron & Frederic Udina, 1995. "Interactive local bandwidth choice," Economics Working Papers 109, Department of Economics and Business, Universitat Pompeu Fabra.
    227. Steve Gibbons, 2001. "Paying for good neighbours? Neighbourhood deprivation and the communiy benefits of education," CEE Discussion Papers 0017, Centre for the Economics of Education, LSE.
    228. Salvador Barrios & Holger Görg & Eric Strobl, 2004. "Foreign Direct Investment, Competition and Industrial Development in the Host Country: An Analysis for the Case of "White" Certificates," Discussion Papers of DIW Berlin 426, DIW Berlin, German Institute for Economic Research.
    229. Temel, Tugrul, 2011. "New facts for old debates: Farm size and productivity in US agriculture," MPRA Paper 31920, University Library of Munich, Germany.
    230. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    231. Mason, Patrick L., 1994. "An empirical derivation of the industry wage equation," MPRA Paper 11325, University Library of Munich, Germany.
    232. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    233. Peter C.B. Phillips & Joon Y. Park, 1998. "Nonstationary Density Estimation and Kernel Autoregression," Cowles Foundation Discussion Papers 1181, Cowles Foundation for Research in Economics, Yale University.
    234. Peter C.B. Phillips, 2003. "Laws and Limits of Econometrics," Cowles Foundation Discussion Papers 1397, Cowles Foundation for Research in Economics, Yale University.
    235. Gottschalk Sandra, 2005. "Microdata Disclosure Control by Resampling - Effects on Regression Results," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(5), pages 567-583, October.
    236. Oliver Linton, 1997. "Second Order Approximation in a Linear Regression with Heteroskedasticity for Unknown Form," Cowles Foundation Discussion Papers 1151, Cowles Foundation for Research in Economics, Yale University.
    237. Nakar Djindil Syntiche & Tabo Symphorien Ndang & Toinar Mogota Anatole, 2007. "A qui profitent les dépenses sociales au Tchad? Une analyse d'incidence à partir des données d'enquête," Working Papers PMMA 2007-11, PEP-PMMA.
    238. König, Anja, 1997. "Schätzen und Testen in semiparametrischen partiell linearen Modellen für die Paneldatenanalyse," Hannover Economic Papers (HEP) dp-208, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    239. Eric Ghysels & Christian Gouriéroux & Joann Jasiak, 1996. "Kernel Autocorrelogram for Time Deformed Processes," CIRANO Working Papers 96s-19, CIRANO.
    240. DiNardo, John & Tobias, Justin, 2001. "Nonparametric Density and Regression Estimation," Staff General Research Papers Archive 12020, Iowa State University, Department of Economics.
    241. Rand Wilcox, 2006. "Confidence intervals for prediction intervals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 317-326.
    242. Egger, Peter H. & Wamser, Georg, 2015. "The impact of controlled foreign company legislation on real investments abroad. A multi-dimensional regression discontinuity design," Journal of Public Economics, Elsevier, vol. 129(C), pages 77-91.
    243. D. K. Ginther, "undated". "A nonparametric analysis of the U.S. earnings distribution," Institute for Research on Poverty Discussion Papers 1067-95, University of Wisconsin Institute for Research on Poverty.
    244. Christopher T. Downing, 1999. "Nonparametric Estimation of Multifactor Continuous Time Interest-Rate Models," Computing in Economics and Finance 1999 111, Society for Computational Economics.
    245. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    246. Adonis Yatchew & Len Bos, 1997. "Nonparametric Least Squares Regression and Testing in Economic Models," Working Papers yatchew-99-01, University of Toronto, Department of Economics.
    247. Datt, Gaurav & Payongayong, Ellen & Garrett, James L. & Ruel, Marie T., 1997. "The GAPVU cash transfer program in Mozambique," FCND discussion papers 36, International Food Policy Research Institute (IFPRI).
    248. Jens Hainmueller & Holger Lutz Kern, 2005. "Incumbency Effects in German and British Elections: A Quasi- Experimental Approach," Public Economics 0505009, University Library of Munich, Germany.
    249. Dursun AYDIN & Ersin YILMAZ, 2017. "Bandwidth Selection Problem for Nonparametric Regression Model with Right-Censored Data," Romanian Statistical Review, Romanian Statistical Review, vol. 65(2), pages 81-104, June.
    250. Giorgio Fagiolo, 2001. "Engel Curves Specification in an Artificial Model of Consumption Dynamics with Socially Evolving Preferences," LEM Papers Series 2001/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    251. Čížek, Pavel, 2004. "(Non) Linear Regression Modeling," Papers 2004,11, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    252. Sturdivant, Rodney X. & Hosmer Jr., David W., 2007. "A smoothed residual based goodness-of-fit statistic for logistic hierarchical regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3898-3912, May.
    253. Robert Breunig, 2001. "Density Estimation For Clustered Data," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 353-367.
    254. Joel L. Horowitz & N. E. Savin, 2001. "Binary Response Models: Logits, Probits and Semiparametrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 43-56, Fall.
    255. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "A New Test for Chaotic Dynamics Using Lyapunov Exponents," Working Papers 2003-09, FEDEA.

  219. Härdle, Wolfgang & Korostelev, A., 1994. "Search of Significant Variables in Nonparametric Additive Regression," SFB 373 Discussion Papers 1994,42, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  220. HÄRDLE, Wolfgang & VIEU, Philippe, 1992. "Kernel regression smoothing of time series," LIDAM Reprints CORE 981, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Ayse Yilmaz & Ufuk Yolcu, 2022. "Dendritic neuron model neural network trained by modified particle swarm optimization for time‐series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 793-809, July.
    2. Federico M Bandi & Valentina Corradi & Daniel Wilhelm, 2016. "Possibly Nonstationary Cross-Validation," CeMMAP working papers 11/16, Institute for Fiscal Studies.
    3. Francesco Audrino, 2005. "Local Likelihood for non‐parametric ARCH(1) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 251-278, March.
    4. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.
    5. Kim, Namhyun & W. Saart, Patrick, 2021. "Estimation in partially linear semiparametric models with parametric and/or nonparametric endogeneity," Cardiff Economics Working Papers E2021/9, Cardiff University, Cardiff Business School, Economics Section.
    6. Jozef Barunik & Lukas Vacha, 2023. "The Dynamic Persistence of Economic Shocks," Papers 2306.01511, arXiv.org.

  221. HÄRDLE, Wolfgang & HART, Jeffrey D., 1992. "A bootstrap test for positive definiteness of income effect matrices," LIDAM Reprints CORE 999, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Manisha Chakrabarty & Anke Schmalenbach & Jeffrey Racine, 2006. "On the distributional effects of income in an aggregate consumption relation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(4), pages 1221-1243, November.
    2. Joachim Freyberger & Joel L. Horowitz, 2013. "Identification and shape restrictions in nonparametric instrumental variables estimation," CeMMAP working papers 31/13, Institute for Fiscal Studies.

  222. Härdle, W.K. & Scott, D.W., 1992. "Smoothing by weighted averaging of rounded points," LIDAM Reprints CORE 996, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

  223. HÄRDLE, Wolfgang & HART, Jeffrey & MARRON, Steve & TSYBAKOV, Alexander, 1992. "Bandwith choice for average derivative estimation," LIDAM Reprints CORE 977, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.
    2. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.
    3. Matsushita, Yukitoshi & Otsu, Taisuke, 2018. "Likelihood inference on semiparametric models: average derivative and treatment effect," LSE Research Online Documents on Economics 85870, London School of Economics and Political Science, LSE Library.
    4. Nishiyama, Yoshihiko & Robinson, Peter M., 2005. "The bootstrap and the Edgeworth correction for semiparametric averaged derivatives," LSE Research Online Documents on Economics 2297, London School of Economics and Political Science, LSE Library.
    5. Yukitoshi Matsushita & Taisuke Otsu, 2018. "Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect," The Japanese Economic Review, Springer, vol. 69(2), pages 133-155, June.
    6. Marian Hristache, 2002. "Are Efficient Estimators in Single-Index Models Really Efficient? A Computational Discussion," Computational Statistics, Springer, vol. 17(4), pages 453-464, December.
    7. Thomas Knox & James H. Stock & Mark W. Watson, 2004. "Empirical Bayes Regression With Many Regressors," Working Papers 2004-1, Princeton University. Economics Department..
    8. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.

  224. Hardle, W. & Tsybakov, A.B., 1992. "How Sensitive are Average Derivatives?," Papers 9208, Tilburg - Center for Economic Research.

    Cited by:

    1. Hiroaki Kaido, 2014. "Asymptotically efficient estimation of weighted average derivatives with an interval censored variable," CeMMAP working papers 03/14, Institute for Fiscal Studies.
    2. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    3. Yingcun Xia & Wolfgang Härdle & Oliver Linton, 2009. "Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator," SFB 649 Discussion Papers SFB649DP2009-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Girard, Séphane & Jacob, Pierre, 2009. "Frontier estimation with local polynomials and high power-transformed data," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1691-1705, September.
    5. Huybrechts F. Bindele & Ash Abebe & Karlene N. Meyer, 2018. "General rank-based estimation for regression single index models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1115-1146, October.
    6. Goldenshluger, Alexander, 2002. "Density Deconvolution in the Circular Structural Model," Journal of Multivariate Analysis, Elsevier, vol. 81(2), pages 360-375, May.
    7. Bontemps, Christophe & Simioni, Michel & Surry, Yves R., 2005. "Hedonic Housing Prices and Agricultural Pollution: An Empirical Investigation on Semiparametric Models," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24709, European Association of Agricultural Economists.
    8. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series 451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    9. Kyungchul Song, 2009. "Bootstrapping Semiparametric Models with Single-Index Nuisance Parameters, Second Version," PIER Working Paper Archive 10-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2010.
    10. Tue Gorgens, 2000. "Semiparametric Estimation of Single-Index Transition Intensities," Econometric Society World Congress 2000 Contributed Papers 0596, Econometric Society.
    11. Hall, Peter & Park, Byeong U. & Stern, Steven E., 1998. "On Polynomial Estimators of Frontiers and Boundaries," Journal of Multivariate Analysis, Elsevier, vol. 66(1), pages 71-98, July.
    12. Flambard, Véronique & Lasserre, Pierre & Mohnen, Pierre, 2004. "Snow Removal Auctions in Montreal: Costs, Informational Rents, and Procurement Management," Research Memorandum 023, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    13. Linton, Oliver, 2002. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," Journal of Econometrics, Elsevier, vol. 106(2), pages 325-368, February.
    14. Marian Hristache, 2002. "Are Efficient Estimators in Single-Index Models Really Efficient? A Computational Discussion," Computational Statistics, Springer, vol. 17(4), pages 453-464, December.
    15. Almekinders, G.J. & Eijffinger, S.C.W., 1994. "Daily Bundesbank and federal reserve interventions : Are they a reaction to changes in the level and volatility of the DM/$-rate?," Other publications TiSEM 3e0ae3fa-af29-4757-aecb-a, Tilburg University, School of Economics and Management.
    16. Yiping Yang & Tiejun Tong & Gaorong Li, 2019. "SIMEX estimation for single-index model with covariate measurement error," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 137-161, March.
    17. Powell, James L. & Stoker, Thomas M., 1992. "Optimal bandwidth choice for density-weighted averages," Working papers 3424-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    18. Song, Kyungchul, 2014. "Semiparametric models with single-index nuisance parameters," Journal of Econometrics, Elsevier, vol. 178(P3), pages 471-483.
    19. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2010. "Robust Data-Driven Inference for Density-Weighted Average Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1070-1083.
    20. Erik Bergkvist & Per Johansson, 2000. "Weighted Derivative Estimation of Quantal Response Models: Simulations and Applications to Choice of Truck Freight Carrier," Computational Statistics, Springer, vol. 15(4), pages 485-510, December.
    21. Feng, Sanying & Kong, Kaidi & Kong, Yinfei & Li, Gaorong & Wang, Zhaoliang, 2022. "Statistical inference of heterogeneous treatment effect based on single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 175(C).
    22. Girard, Stéphane & Guillou, Armelle & Stupfler, Gilles, 2013. "Frontier estimation with kernel regression on high order moments," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 172-189.
    23. Biau, Gérard & Cadre, Benoît & Pelletier, Bruno, 2008. "Exact rates in density support estimation," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2185-2207, November.
    24. Qihua Wang & Tao Zhang & Wolfgang Karl Härdle, 2014. "An Extended Single Index Model with Missing Response at Random," SFB 649 Discussion Papers SFB649DP2014-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Girard, Stéphane & Jacob, Pierre, 2008. "Frontier estimation via kernel regression on high power-transformed data," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 403-420, March.
    26. Cardot, Hervé & Johannes, Jan, 2010. "Thresholding projection estimators in functional linear models," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 395-408, February.
    27. Kim, Peter T. & Koo, Ja-Yong & Park, Heon Jin, 2004. "Sharp minimaxity and spherical deconvolution for super-smooth error distributions," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 384-392, August.
    28. Hotz, Thomas & Marnitz, Philipp & Stichtenoth, Rahel & Davies, Laurie & Kabluchko, Zakhar & Munk, Axel, 2012. "Locally adaptive image denoising by a statistical multiresolution criterion," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 543-558.
    29. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    30. Zhang, Riquan & Huang, Zhensheng & Lv, Yazhao, 2010. "Statistical inference for the index parameter in single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 1026-1041, April.
    31. Kyungchul Song, 2009. "Two-Step Extremum Estimation with Estimated Single-Indices," PIER Working Paper Archive 09-012, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    32. Nishiyama, Y., 2004. "Minimum normal approximation error bandwidth selection for averaged derivatives," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(1), pages 53-61.
    33. Cuevas, Antonio & Febrero, Manuel & Fraiman, Ricardo, 2001. "Cluster analysis: a further approach based on density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 441-459, June.
    34. Xue, Liu-Gen & Zhu, Lixing, 2006. "Empirical likelihood for single-index models," Journal of Multivariate Analysis, Elsevier, vol. 97(6), pages 1295-1312, July.
    35. Guerre, Emmanuel, 2000. "Design Adaptive Nearest Neighbor Regression Estimation," Journal of Multivariate Analysis, Elsevier, vol. 75(2), pages 219-244, November.

  225. HÄRDLE, Wolfgang & HALL, Peter & MARRON, Steve, 1992. "Regression smoothing parameters that are not far from their optimum," LIDAM Reprints CORE 978, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Feng, Yuanhua & Beran, Jan, 2007. "Optimal convergence rates in nonparametric regression with fractional time series errors," CoFE Discussion Papers 07/15, University of Konstanz, Center of Finance and Econometrics (CoFE).
    2. Beran, Jan & Feng, Yuanhua, 2000. "Data-driven estimation of semiparametric fractional autoregressive models," CoFE Discussion Papers 00/16, University of Konstanz, Center of Finance and Econometrics (CoFE).
    3. Beran, Jan & Feng, Yuanhua, 2002. "Recent Developments in Non- and Semiparametric Regression with Fractional Time Series Errors," CoFE Discussion Papers 02/13, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Beran, Jan & Feng, Yuanhua & Heiler, Siegfried, 2000. "Modifying the double smoothing bandwidth selector in nonparametric regression," CoFE Discussion Papers 00/37, University of Konstanz, Center of Finance and Econometrics (CoFE).
    5. K. De Brabanter & Y. Liu & C. Hua, 2016. "Convergence rates for uniform confidence intervals based on local polynomial regression estimators," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 31-48, March.
    6. Beran, Jan & Feng, Yuanhua, 2001. "Iterative plug-in algorithms for SEMIFAR models - definition, convergence and asymptotic properties," CoFE Discussion Papers 01/11, University of Konstanz, Center of Finance and Econometrics (CoFE).
    7. Heiler, Siegfried & Feng, Yuanhua, 1997. "A bootstrap bandwidth selector for local polynomial fitting," Discussion Papers, Series II 344, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    8. Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).

  226. HÄRDLE, Wolfgang & TURLACH, Berwin, 1992. "Nonparametric approaches to generalized linear models," LIDAM Discussion Papers CORE 1992037, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Müller, Marlene, 1997. "Computer-assisted generalized partial linear models," SFB 373 Discussion Papers 1997,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  227. Hardle, W. & Hall, P. & Ichimura, H., 1991. "Optimal smoothing in single index models," LIDAM Discussion Papers CORE 1991007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
    2. Yingcun Xia & Wolfgang Härdle & Oliver Linton, 2009. "Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator," SFB 649 Discussion Papers SFB649DP2009-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Rolf Aaberge & Steinar Bjerve & Kjell Doksum, 2005. "Decomposition of Rank-Dependent Measures of Inequality by Subgroups," Discussion Papers 437, Statistics Norway, Research Department.
    4. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.
    5. Jean Pinquet & Montserrat Guillén & Catalina Bolancé, 2008. "On the link between credibility and frequency premium," Post-Print hal-00361645, HAL.
    6. Climov, Daniela & Delecroix, Michel & Simar, Léopold, 2001. "Semiparametric estimation in single index poisson regression: A practical approach," SFB 373 Discussion Papers 2001,51, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Jia Chen & Jiti Gao & Degui Li, 2011. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," Monash Econometrics and Business Statistics Working Papers 12/11, Monash University, Department of Econometrics and Business Statistics.
    8. Juan Carlos Escanciano & Kyungchul Song, 2007. "Asymptotically Optimal Tests for Single-Index Restrictions with a Focus on Average Partial Effects," PIER Working Paper Archive 07-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    9. Grant, Charles & Padula, Mario, 2013. "Using bounds to investigate household debt repayment behaviour," Research in Economics, Elsevier, vol. 67(4), pages 336-354.
    10. Qiang Chen & Lu Lin & Lixing Zhu, 2010. "Bias-corrected smoothed score function for single-index models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(1), pages 45-58, January.
    11. Jiti Gao & Hua Liang, 1997. "Statistical Inference in Single-Index and Partially Nonlinear Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(3), pages 493-517, September.
    12. Gutierrez, Roberto G. & Carroll, Raymond J., 1995. "Plug-in semiparametric estimating equations," SFB 373 Discussion Papers 1997,13, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    13. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    14. Li, Lexin & Dennis Cook, R. & Nachtsheim, Christopher J., 2004. "Cluster-based estimation for sufficient dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 175-193, August.
    15. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.

  228. Hall, P. & Hardle, W. & Simar, L., 1991. "On teh inconsistency of bootstrap distribution estimators," LIDAM Discussion Papers CORE 1991020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Hall, P. & Hardle, W. & Simar, L., 1991. "Iterated bootstrap with applications to frontier models," LIDAM Discussion Papers CORE 1991021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    3. B.U.PARK & Wolfgang HAERDLE, "undated". "Testing increasing dispersion," Statistic und Oekonometrie 9314, Humboldt Universitaet Berlin.
    4. Feng, Qu & Horrace, William C., 2012. "Estimating technical efficiency in micro panels," Economics Letters, Elsevier, vol. 117(3), pages 730-733.
    5. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    6. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2007. "On the Accuracy of Bootstrap Confidence Intervals for Efficiency Levels in Stochastic Frontier Models with Panel Data," Working Papers 0704, University of Crete, Department of Economics.
    7. Qu Feng & William C. Horrace, 2010. "Alternative Technical Efficiency Measures: Skew, Bias, and Scale," Center for Policy Research Working Papers 121, Center for Policy Research, Maxwell School, Syracuse University.
    8. Hardle, W. & Park, B. U., 1995. "Testing increasing dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 19(6), pages 641-653, June.
    9. Zhexiao Lin & Fang Han, 2023. "On the failure of the bootstrap for Chatterjee's rank correlation," Papers 2303.14088, arXiv.org, revised Apr 2023.

  229. Wolfgang HÄRDLE & Michael JERISON, 1991. "Cross section Engel Curves over Time," Discussion Papers (REL - Recherches Economiques de Louvain) 1991045, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).

    Cited by:

    1. Gong, X. & van Soest, A.H.O. & Zhang, P., 2000. "Sexual Bias and Household Consumption : A Semiparametic Analysis of Engel curves in Rural China," Discussion Paper 2000-45, Tilburg University, Center for Economic Research.
    2. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2023. "Nonparametric Models in Consumer Behaviour," Working Papers ECARES 2023-04, ULB -- Universite Libre de Bruxelles.
    3. Arthur Lewbel, 2000. "A Rational Rank Four Demand System," Boston College Working Papers in Economics 463, Boston College Department of Economics, revised 04 Apr 2003.
    4. Chakrabarty, Manisha & Hildenbrand, Werner, 2011. "Engel's Law Reconsidered," Journal of Mathematical Economics, Elsevier, vol. 47(3), pages 289-299.
    5. Gozalo, Pedro L., 1997. "Nonparametric bootstrap analysis with applications to demographic effects in demand functions," Journal of Econometrics, Elsevier, vol. 81(2), pages 357-393, December.
    6. Menggen Chen, 2022. "Engel’s law in China: Some new evidence," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1640-1662, August.
    7. Song, Ze & Li, Lianyou & Ma, Chao, 2013. "The EASI Demand System : Evidence from China Household," MPRA Paper 48435, University Library of Munich, Germany.
    8. Chai Andreas & Moneta Alessio, 2014. "Escaping Satiation Dynamics: Some Evidence from British Household Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(2-3), pages 299-327, April.
    9. Cordes, Christian, 2009. "Changing your role models: Social learning and the Engel curve," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(6), pages 957-965, December.
    10. Gaurav Nayyar, 2009. "The Demand for Services in India. A Mirror Image of Engel's Law for Food?," Economics Series Working Papers 451, University of Oxford, Department of Economics.
    11. Mette Christensen, 2007. "Integrability of Demand Accounting for Unobservable Heterogeneity: A Test on Panel Data," Economics Discussion Paper Series 0713, Economics, The University of Manchester.
    12. Richard Blundell & Xiaohong Chen & Dennis Kristensen, 2003. "Nonparametric IV estimation of shape-invariant Engel curves," CeMMAP working papers CWP15/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Giorgio Fagiolo, 2001. "Engel Curves Specification in an Artificial Model of Consumption Dynamics with Socially Evolving Preferences," LEM Papers Series 2001/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Stephan B. Bruns & Alessio Moneta, 2017. "Intertemporal propensity to consume," Journal of Evolutionary Economics, Springer, vol. 27(2), pages 295-314, April.

  230. Hardle, W. & Huet, S. & Jolivet, E., 1991. "Better Bootstrap Confidence Intervals for Regression Curve Estimation," LIDAM Discussion Papers CORE 1991056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Peter Hall & Joel L. Horowitz, 2012. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers CWP14/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Sommerfeld, Volker, 1997. "Wild bootstrap versus moment-oriented bootstrap," SFB 373 Discussion Papers 1997,76, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  231. Franke, J. & Hardle, W., 1990. "On bootstrapping kernel spectralestimates," LIDAM Discussion Papers CORE 1990058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Luca Benati & Paolo Surico, 2006. "The Great Moderation and the ‘Bernanke Conjecture’," Computing in Economics and Finance 2006 158, Society for Computational Economics.
    2. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1995. "Dynamic Equilibrium Economies: A Framework for Comparing Models and Data," NBER Technical Working Papers 0174, National Bureau of Economic Research, Inc.
    3. Luca Benati, 2004. "Evolving post-World War II UK economic performance," Bank of England working papers 232, Bank of England.
    4. Dette, Holger & Paparoditis, Efstathios, 2008. "Bootstrapping frequency domain tests in multivariate time series with an application to comparing spectral densities," Technical Reports 2008,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Carlos Velasco & Ignacio N. Lobato, 2004. "A simple and general test for white noise," Econometric Society 2004 Latin American Meetings 112, Econometric Society.
    6. Dette, Holger & Paroditis, Efstathios, 2007. "Testing equality of spectral densities," Technical Reports 2007,29, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    7. Fortin, Ines & Kuzmics, Christoph, 1999. "Optimal Bandwidth Selection in Non-Parametric Spectral Density Estimation," Economics Series 62, Institute for Advanced Studies.

  232. Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," LIDAM Discussion Papers CORE 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc.
    2. Chen, Rong, 1998. "Functional coefficient autoregressive models: Estimation and tests of hypotheses," SFB 373 Discussion Papers 1998,10, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Dabo-Niang, Sophie & Francq, Christian & Zakoian, Jean-Michel, 2009. "Combining parametric and nonparametric approaches for more efficient time series prediction," MPRA Paper 16893, University Library of Munich, Germany.
    4. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761R2, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    5. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    6. Juan Carlos Escanciano & Carlos Velasco, 2006. "Testing the Martingale Difference Hypothesis Using Integrated Regression Functions," Faculty Working Papers 06/06, School of Economics and Business Administration, University of Navarra.
    7. John Galbraith & Simon van Norden, 2008. "The Calibration Of Probabilistic Economic Forecasts," Departmental Working Papers 2008-05, McGill University, Department of Economics.
    8. Gerhard Weihrather, 1993. "Testing a linear regression model against nonparametric alternatives," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 40(1), pages 367-379, December.
    9. Bissantz, Nicolai & Holzmann, Hajo, 2007. "Statistical inference for inverse problems," Technical Reports 2007,40, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    10. Neumann, Michael H., 1997. "Strong approximation of density estimators from weakly dependent observations by density estimators from independent observations," SFB 373 Discussion Papers 1997,86, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    11. David C. Wheelock & Paul W. Wilson, 2011. "Are Credit Unions Too Small?," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1343-1359, November.
    12. José Eduardo Gómez-González & Elioth Mirsha Sanabria-Buenaventura, 2012. "Non-Parametric and Semi-Parametric Asset Pricing: An Application to the Colombian Stock Exchange," Borradores de Economia 9384, Banco de la Republica.
    13. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2009. "An Improved Bootstrap Test of Stochastic Dominance," Cowles Foundation Discussion Papers 1713, Cowles Foundation for Research in Economics, Yale University.
    14. Bontemps, Christophe & Simioni, Michel & Surry, Yves R., 2005. "Hedonic Housing Prices and Agricultural Pollution: An Empirical Investigation on Semiparametric Models," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24709, European Association of Agricultural Economists.
    15. Lopez, O. & Patilea, V., 2009. "Nonparametric lack-of-fit tests for parametric mean-regression models with censored data," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 210-230, January.
    16. Escanciano, Juan Carlos & Jacho-Chávez, David T., 2010. "Approximating the critical values of Cramér-von Mises tests in general parametric conditional specifications," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 625-636, March.
    17. Li-Ping Zhu & Lin-Yi Qian & Jin-Guan Lin, 2011. "Variable selection in a class of single-index models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(6), pages 1277-1293, December.
    18. Lei Gao & Li Wang, 2011. "Security price responses to unexpected earnings: a nonparametric investigation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 241-258, June.
    19. Franke, Jürgen & Kreiss, Jens-Peter & Mammen, Enno, 1997. "Bootstrap of kernel smoothing in nonlinear time series," SFB 373 Discussion Papers 1997,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    20. Paulo Parente & Richard Smith, 2012. "Exogeneity in semiparametric moment condition models," CeMMAP working papers CWP30/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. W. González-Manteiga & R. Cao, 1993. "Testing the hypothesis of a general linear model using nonparametric regression estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(1), pages 161-188, December.
    22. Bartels, Knut, 1998. "A model specification test," SFB 373 Discussion Papers 1998,109, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    23. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
    24. Härdle, Wolfgang & Liang, Hua & Sommerfeld, Volker, 1997. "Bootstrap approximations in a partially linear regression model," SFB 373 Discussion Papers 1997,102, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    25. Nicolas Debarsy & Vincenzo Verardi, 2010. "Estimating Nonlinearities in Spatial Autoregressive Models," Working Papers 1016, University of Namur, Department of Economics.
    26. Juei-Chao Chen, 1994. "Testing for no effect in nonparametric regression via spline smoothing techniques," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(2), pages 251-265, June.
    27. Thomas Triebs & Subal C. Kumbhakar, 2012. "Management Practice in Production," ifo Working Paper Series 129, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    28. Christoph Rothe & Dominik Wied, 2013. "Misspecification Testing in a Class of Conditional Distributional Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(501), pages 314-324, March.
    29. Kyle Handley & Nuno Limão, 2013. "Policy Uncertainty, Trade and Welfare: Theory and Evidence for China and the U.S," NBER Working Papers 19376, National Bureau of Economic Research, Inc.
    30. Poulin, Jennifer & Duchesne, Pierre, 2008. "On the power transformation of kernel-based tests for serial correlation in vector time series: Some finite sample results and a comparison with the bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4432-4457, May.
    31. Bartels, Knut & Boztuæg, Yasemin & Müller, Marlene, 1999. "Testing the multinomial logit model," SFB 373 Discussion Papers 1999,19, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    32. Eckhard Liebscher, 2012. "Model checks for parametric regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 132-155, March.
    33. Mark Fiecas & Hernando Ombao, 2016. "Modeling the Evolution of Dynamic Brain Processes During an Associative Learning Experiment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1440-1453, October.
    34. Simar, Leopold & Wilson, Paul W., 2011. "Inference by the m out of n bootstrap in nonparametric frontier models," LIDAM Reprints ISBA 2011027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    35. Läuter, Henning & Nikulin, Michail, 1999. "Parametric versus nonparametric goodness of fit: Another view," SFB 373 Discussion Papers 1999,14, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    36. Zheng, Xu, 2008. "Testing for discrete choice models," Economics Letters, Elsevier, vol. 98(2), pages 176-184, February.
    37. He X. & Zhu L-X., 2003. "A Lack-of-Fit Test for Quantile Regression," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 1013-1022, January.
    38. Estela Bee Dagum & Alessandra Luati, 2002. "Global and local statistical properties of fixed-length nonparametric smoothers," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 313-333, October.
    39. Juan Carlos Escanciano, 2004. "Model Checks Using Residual Marked Empirical Processes," Faculty Working Papers 13/04, School of Economics and Business Administration, University of Navarra.
    40. Diack, C.A.T. & Thomas-Agnan, C., 1996. "A Nonparametric Test of The Non-Convexity of Regression," Papers 976.427, Toulouse - GREMAQ.
    41. Zhang, Chunming & Dette, Holger, 2003. "A power comparison between nonparametric regression tests," Technical Reports 2003,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    42. Pascal Lavergne & Valentin Patilea, 2008. "One for All and All for One:Regression Checks With Many Regressors," Discussion Papers dp08-06, Department of Economics, Simon Fraser University.
    43. Neumeyer, Natalie & Dette, Holger & Nagel, Eva-Renate, 2003. "A note on testing symmetry of the error distribution in linear regression models," Technical Reports 2003,25, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    44. Denis Chetverikov, 2012. "Testing regression monotonicity in econometric models," CeMMAP working papers CWP35/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Zhang, Chun-Xia & Mei, Chang-Lin & Zhang, Jiang-She, 2007. "An empirical study of a test for polynomial relationships in randomly right censored regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6543-6556, August.
    46. Heuchenne, Cédric & Van Keilegom, Ingrid, 2010. "Goodness-of-fit tests for the error distribution in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1942-1951, August.
    47. Neumann, Michael H. & Paparoditis, Efstathios, 1998. "A nonparametric test for the stationary density," SFB 373 Discussion Papers 1998,58, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    48. Enno Mammen, 2007. "Comments on: Nonparametric inference with generalized likelihood ratio tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(3), pages 462-464, December.
    49. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2008. "Bootstrap Tests of Stochastic Dominance with AsymptoticSimilarity on the Boundary," STICERD - Econometrics Paper Series 527, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    50. Anatolyev Stanislav, 2019. "Testing for a Functional Form of Mean Regression in a Fully Parametric Environment," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
    51. Duchesne, Pierre & Li, Linyuan & Vandermeerschen, Jill, 2010. "On testing for serial correlation of unknown form using wavelet thresholding," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2512-2531, November.
    52. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    53. Sommerfeld, Volker, 1997. "Wild bootstrap versus moment-oriented bootstrap," SFB 373 Discussion Papers 1997,76, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    54. Dette, Holger & Hetzler, Benjamin, 2004. "Specification tests indexed by bandwidths," Technical Reports 2004,48, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    55. Bissantz, Nicolai & Holzmann, Hajo & Pawlak, Mirosław, 2008. "Testing for image symmetries: with application to confocal microscopy," Technical Reports 2008,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    56. Härdle, Wolfgang & Sperlich, Stefan & Spokoiny, Vladimir G., 1997. "Component analysis for additive models," SFB 373 Discussion Papers 1997,52, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  233. Härdle, W. & Marron, S.J., 1990. "Semiparametric comparison of regression curves," LIDAM Reprints CORE 890, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc.
    2. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    3. Hira L. Koul & Fang Li, 2020. "Comparing two nonparametric regression curves in the presence of long memory in covariates and errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(4), pages 499-517, May.
    4. Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," LIDAM Discussion Papers CORE 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
    6. Li, S. & Linton, O., 2020. "When will the Covid-19 pandemic peak?," Cambridge Working Papers in Economics 2025, Faculty of Economics, University of Cambridge.
    7. Blow, Laura & Crawford, Ian, 2002. "A nonparametric method for valuing new goods," Working Paper Series 143, European Central Bank.
    8. Zhao, Shi & Bakoyannis, Giorgos & Lourens, Spencer & Tu, Wanzhu, 2020. "Comparison of nonlinear curves and surfaces," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    9. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
    10. Läuter, Henning & Nikulin, Michail, 1999. "Parametric versus nonparametric goodness of fit: Another view," SFB 373 Discussion Papers 1999,14, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    11. Brachmann, Klaus, 1995. "Nichtparametrische Analyse parametrischer Wachstumsfunktionen: Eine Anwendung auf das Wachstum des globalen Netzwerks Internet," Discussion Papers in Econometrics and Statistics 5/95, University of Cologne, Institute of Econometrics and Statistics.
    12. Zapata, Hector O. & Sulgham, Anil K., 2006. "A Semiparametric Approach to Estimate Engel curves using the US Micro Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21092, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    14. Cody Carroll & Hans‐Georg Müller & Alois Kneip, 2021. "Cross‐component registration for multivariate functional data, with application to growth curves," Biometrics, The International Biometric Society, vol. 77(3), pages 839-851, September.
    15. Holger Dette & Subhra Sankar Dhar & Weichi Wu, 2021. "Identifying shifts between two regression curves," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(5), pages 855-889, October.
    16. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    17. Ying Qing Chen, 2010. "Semiparametric Regression in Size-Biased Sampling," Biometrics, The International Biometric Society, vol. 66(1), pages 149-158, March.
    18. Luca Bagnato & Lucio De Capitani & Antonio Punzo, 2014. "Testing Serial Independence via Density-Based Measures of Divergence," Methodology and Computing in Applied Probability, Springer, vol. 16(3), pages 627-641, September.
    19. Eleftherios Giovanis & Martina Menon & Federico Perali, 2023. "Disability specific equivalence scales: a case–control approach applied to the cost of acquired brain injuries," International Journal of Health Economics and Management, Springer, vol. 23(4), pages 643-672, December.
    20. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  234. Hardle, W. & Mammen, E., 1990. "Bootstarp Methods in Nonparametric Regression," LIDAM Discussion Papers CORE 1990049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Soo-Bin Jeong & Bong-Hwan Kim & Tae-Hwan Kim & Hyung-Ho Moon, 2017. "Unit Root Tests In The Presence Of Multiple Breaks In Variance," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(02), pages 345-361, June.
    2. Estela Bee Dagum & Alessandra Luati, 2002. "Global and local statistical properties of fixed-length nonparametric smoothers," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 313-333, October.

  235. Hardle, W. & Marron, J.S. & Wand, Mp., 1990. "Bandwith choice for density derivatives," LIDAM Reprints CORE 945, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Salim Bouzebda & Mohamed Chaouch & Sultana Didi Biha, 2022. "Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(4), pages 737-771, August.
    2. Pei Geng & Hira L. Koul, 2019. "Minimum distance model checking in Berkson measurement error models with validation data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 879-899, September.
    3. Martins-Filho, Carlos & Xie, Sihong & Yao, Feng, 2022. "A new estimator of a jump discontinuity in regression," Economics Letters, Elsevier, vol. 218(C).
    4. Berwin A. TURLACH, "undated". "Bandwidth selection in kernel density estimation: a rewiew," Statistic und Oekonometrie 9307, Humboldt Universitaet Berlin.
    5. Matthew D. Baird, 2014. "Cross Validation Bandwidth Selection for Derivatives of Multidimensional Densities," Working Papers WR-1060, RAND Corporation.

  236. Hardle, W. & Tsybakov, A., 1990. "Robust locally adaptive nonparametric regression," LIDAM Discussion Papers CORE 1990028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Estela Bee Dagum & Alessandra Luati, 2002. "Global and local statistical properties of fixed-length nonparametric smoothers," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 313-333, October.

  237. Hardle, W. & Marron, J., 1989. "Bootstrap Simultaneous Error Bars For Nonparametric Regression," LIDAM Discussion Papers CORE 1989023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Peter Hall & Joel L. Horowitz, 2012. "A simple bootstrap method for constructing nonparametric confidence bands for functions," CeMMAP working papers CWP14/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Kauermann, Göran & Müller, Marlene & Carroll, Raymond J., 1998. "The efficiency of bias-corrected estimators for nonparametric kernel estimation based on local estimating equations," Statistics & Probability Letters, Elsevier, vol. 37(1), pages 41-47, January.
    4. Politis, Dimitris N, 2010. "Model-free Model-fitting and Predictive Distributions," University of California at San Diego, Economics Working Paper Series qt67j6s174, Department of Economics, UC San Diego.
    5. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Qian, Junhui & Wang, Le, 2009. "Estimating Semiparametric Panel Data Models by Marginal Integration," MPRA Paper 18850, University Library of Munich, Germany.
    7. Lawrence Brown & Xin Fu & Linda Zhao, 2011. "Confidence intervals for nonparametric regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(1), pages 149-163.
    8. Bissantz, Nicolai & Dümbgen, Lutz & Munk, Axel & Stratmann, Bernd, 2008. "Convergence analysis of generalized iteratively reweighted least squares algorithms on convex function spaces," Technical Reports 2008,25, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    9. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.
    10. Sommerfeld, Volker, 1997. "Construction of automatic confidence intervals in nonparametric heteroscedastic regression by a moment-oriented bootstrap," SFB 373 Discussion Papers 1997,22, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    11. R. Fraiman & G. Pérez-Iribarren, 1996. "Nonparametric conservative bands for the trend of Gaussian AR(p) models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 125-144, June.

  238. Wolfgang HAERDLE & Marlene MUELLER, "undated". "Applied nonparametric smoothing techniques," Statistic und Oekonometrie 9303, Humboldt Universitaet Berlin.

    Cited by:

    1. Michael Gerfin, 1994. "Income Distribution, Income Inequality and Life Cycle Effects - A Nonparametric Analysis for Switzerland," Diskussionsschriften dp9405, Universitaet Bern, Departement Volkswirtschaft.

  239. Wolfgang HAERDLE & Marlene MUELLER, "undated". "Nichtparametrische Glaettungsmethoden in der alltaeglichen statistischen Praxis," Statistic und Oekonometrie 9208, Humboldt Universitaet Berlin.

    Cited by:

    1. Steiner, Viktor & Puhani, Patrick A., 1996. "Die Entwicklung der Lohnstruktur im ostdeutschen Transformationsprozeß," ZEW Discussion Papers 96-03, ZEW - Leibniz Centre for European Economic Research.

  240. Leopold SIMAR & Wolfgang HAERDLE, "undated". "Iterated bootstrap with applications to frontier models," Statistic und Oekonometrie 9302, Humboldt Universitaet Berlin.

    Cited by:

    1. Hall, Peter & Nussbaum, Michael & Stern, Steven E., 1997. "On the Estimation of a Support Curve of Indeterminate Sharpness," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 204-232, August.
    2. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    3. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2007. "On the Accuracy of Bootstrap Confidence Intervals for Efficiency Levels in Stochastic Frontier Models with Panel Data," Working Papers 0704, University of Crete, Department of Economics.
    4. Grosskopf, S. & Margaritis, D. & Valdmanis, V., 1995. "Estimating output substitutability of hospital services: A distance function approach," European Journal of Operational Research, Elsevier, vol. 80(3), pages 575-587, February.
    5. Cherchye, L. & Post, G.T., 2001. "Nonparametric Efficiency Estimation in Stochastic Environments (II)," ERIM Report Series Research in Management ERS-2001-26-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Daniel Wikström, 2015. "A finite sample improvement of the fixed effects estimator applied to technical inefficiency," Journal of Productivity Analysis, Springer, vol. 43(1), pages 29-46, February.
    7. Panutat Satchachai & Peter Schmidt, 2010. "Estimates of technical inefficiency in stochastic frontier models with panel data: generalized panel jackknife estimation," Journal of Productivity Analysis, Springer, vol. 34(2), pages 83-97, October.
    8. Simar, Leopold & Wilson, Paul, 2015. "Statistical Approaches for Nonparametric Frontier Models: A Guided Tour," LIDAM Reprints ISBA 2015022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  241. Xiu Xu & Andrija Mihoci & Wolfgang Karl Härdle, "undated". "lCARE – localizing Conditional AutoRegressive Expectiles," SFB 649 Discussion Papers SFB649DP2015-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).

Articles

  1. Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter FRM based on Expectiles," Journal of Multivariate Analysis, Elsevier, vol. 189(C).

    Cited by:

    1. Daniel Traian PELE & Alexandra Ioana CONDA & Raul Cristian BAG & Miruna MAZURENCU-MARINESCU-PELE & Vasile Alecsandru STRAT, 2023. "Financial Risk Meter for The Romanian Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-24, March.
    2. Wang, Ruting & Althof, Michael & Härdle, Wolfgang Karl, 2023. "A financial risk meter for China," Emerging Markets Review, Elsevier, vol. 56(C).
    3. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).

  2. Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter for emerging markets," Research in International Business and Finance, Elsevier, vol. 60(C).

    Cited by:

    1. Ahmad, Wasim & Tiwari, Shiv Ratan & Wadhwani, Akshay & Khan, Mohammad Azeem & Bekiros, Stelios, 2023. "Financial networks and systemic risk vulnerabilities: A tale of Indian banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    2. Daniel Traian PELE & Alexandra Ioana CONDA & Raul Cristian BAG & Miruna MAZURENCU-MARINESCU-PELE & Vasile Alecsandru STRAT, 2023. "Financial Risk Meter for The Romanian Stock Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-24, March.
    3. Nazlioglu, Saban & Kucukkaplan, Ilhan & Kilic, Emre & Altuntas, Mehmet, 2022. "Financial market integration of emerging markets: Heavy tails, structural shifts, nonlinearity, and asymmetric persistence," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Feng, Haoyuan & Liu, Yue & Wu, Jie & Guo, Kun, 2023. "Financial market spillovers and macroeconomic shocks: Evidence from China," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).

  3. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    See citations under working paper version above.
  4. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "K-expectiles clustering," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    See citations under working paper version above.
  5. Andrija Mihoci & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2021. "TERES: Tail Event Risk Expectile Shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 21(3), pages 449-460, March.

    Cited by:

    1. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).

  6. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    See citations under working paper version above.
  7. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    See citations under working paper version above.
  8. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.

    Cited by:

    1. Thomaidis, Nikolaos S. & Christodoulou, Theodoros & Santos-Alamillos, Francisco J., 2023. "Handling the risk dimensions of wind energy generation," Applied Energy, Elsevier, vol. 339(C).
    2. Mosquera-López, Stephania & Uribe, Jorge M., 2022. "Pricing the risk due to weather conditions in small variable renewable energy projects," Applied Energy, Elsevier, vol. 322(C).

  9. Alla Petukhina & Simon Trimborn & Wolfgang Karl Härdle & Hermann Elendner, 2021. "Investing with cryptocurrencies – evaluating their potential for portfolio allocation strategies," Quantitative Finance, Taylor & Francis Journals, vol. 21(11), pages 1825-1853, November.

    Cited by:

    1. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
    2. Martin Waltz & Abhay Kumar Singh & Ostap Okhrin, 2022. "Vulnerability-CoVaR: Investigating the Crypto-market," Papers 2203.10777, arXiv.org.
    3. Čuljak, Maria & Tomić, Bojan & Žiković, Saša, 2022. "Benefits of sectoral cryptocurrency portfolio optimization," Research in International Business and Finance, Elsevier, vol. 60(C).
    4. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    5. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Ren, Rui & Althof, Michael & Härdle, Wolfgang Karl, 2020. "Tail Risk Network Effects in the Cryptocurrency Market during the COVID-19 Crisis," IRTG 1792 Discussion Papers 2020-028, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.
    8. Aljinović Zdravka & Marasović Branka & Milićević Tea Kalinić, 2022. "The Risk and Return of Traditional and Alternative Investments Under the Impact of COVID-19," Business Systems Research, Sciendo, vol. 13(3), pages 8-22, October.
    9. Konstantin Gorgen & Jonas Meirer & Melanie Schienle, 2022. "Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests," Papers 2203.08224, arXiv.org, revised Jun 2022.
    10. Ingo Weber & Mark Staples, 2022. "Programmable money: next-generation blockchain-based conditional payments," Digital Finance, Springer, vol. 4(2), pages 109-125, September.
    11. Chen, Hao & Xu, Chao, 2022. "The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    12. Wolfgang Karl Hardle & Yegor Klochkov & Alla Petukhina & Nikita Zhivotovskiy, 2022. "Robustifying Markowitz," Papers 2212.13996, arXiv.org.
    13. Bruno Spilak & Wolfgang Karl Hardle, 2022. "Risk budget portfolios with convex Non-negative Matrix Factorization," Papers 2204.02757, arXiv.org, revised Jun 2023.
    14. Rudkin, Simon & Rudkin, Wanling & Dłotko, Paweł, 2023. "On the topology of cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 89(C).
    15. Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    16. Patel, Ritesh & Migliavacca, Milena & Oriani, Marco E., 2022. "Blockchain in banking and finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 62(C).
    17. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    18. Gerritsen, Dirk F. & Lugtigheid, Rick A.C. & Walther, Thomas, 2022. "Can Bitcoin Investors Profit from Predictions by Crypto Experts?," Finance Research Letters, Elsevier, vol. 46(PA).
    19. Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024. "Quantifying neural network uncertainty under volatility clustering," Papers 2402.14476, arXiv.org.

  10. Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021. "Factorisable Multitask Quantile Regression," Econometric Theory, Cambridge University Press, vol. 37(4), pages 794-816, August.
    See citations under working paper version above.
  11. Wang, Ben Zhe & Sheen, Jeffrey & Trück, Stefan & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "A Note On The Impact Of News On Us Household Inflation Expectations," Macroeconomic Dynamics, Cambridge University Press, vol. 24(4), pages 995-1015, June.

    Cited by:

    1. Sheen, Jeffrey & Wang, Ben Zhe, 2023. "Do monetary condition news at the zero lower bound influence households’ expectations and readiness to spend?," European Economic Review, Elsevier, vol. 152(C).
    2. Nicolas Reigl, 2023. "Noise shocks and business cycle fluctuations in three major European Economies," Empirical Economics, Springer, vol. 64(2), pages 603-657, February.

  12. Shiyi Chen & Wolfgang K. Härdle & Li Wang, 2020. "Estimation and determinants of Chinese banks’ total factor efficiency: a new vision based on unbalanced development of Chinese banks and their overall risk," Computational Statistics, Springer, vol. 35(2), pages 427-468, June.
    See citations under working paper version above.
  13. Wolfgang Karl Härdle & Campbell R Harvey & Raphael C G Reule, 2020. "Understanding Cryptocurrencies," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 181-208.
    See citations under working paper version above.
  14. Simon Trimborn & Mingyang Li & Wolfgang Karl Härdle, 2020. "Investing with Cryptocurrencies—a Liquidity Constrained Investment Approach," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 280-306.
    See citations under working paper version above.
  15. Marius Lux & Wolfgang Karl Härdle & Stefan Lessmann, 2020. "Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid," Computational Statistics, Springer, vol. 35(3), pages 947-981, September.
    See citations under working paper version above.
  16. Ai Jun Hou & Weining Wang & Cathy Y H Chen & Wolfgang Karl Härdle, 2020. "Pricing Cryptocurrency Options," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 250-279.

    Cited by:

    1. Lian, Yu-Min & Chen, Jun-Home, 2021. "Pricing virtual currency-linked derivatives with time-inhomogeneity," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 424-439.
    2. Matic, Jovanka Lili & Packham, Natalie & Härdle, Wolfgang Karl, 2021. "Hedging Cryptocurrency Options," MPRA Paper 110774, University Library of Munich, Germany.
    3. Jovanka Lili Matic & Natalie Packham & Wolfgang Karl Härdle, 2023. "Hedging cryptocurrency options," Review of Derivatives Research, Springer, vol. 26(1), pages 91-133, April.
    4. Zhang, Chuanhai & Ma, Huan & Liao, Xiaosai, 2023. "Futures trading activity and the jump risk of spot market: Evidence from the bitcoin market," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    5. Min-Bin Lin & Kainat Khowaja & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Blockchain mechanism and distributional characteristics of cryptos," Papers 2011.13240, arXiv.org, revised Aug 2021.
    6. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
    7. Xia, Lan & Roggeveen, Anne L., 2022. "How collective stress affects price fairness perceptions: The role of nostalgia," Journal of Business Research, Elsevier, vol. 152(C), pages 361-371.
    8. Huang, Jing-Zhi & Ni, Jun & Xu, Li, 2022. "Leverage effect in cryptocurrency markets," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    9. Melanie Cao & Batur Celik, 2021. "Valuation of bitcoin options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1007-1026, July.
    10. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    11. Carol Alexander & Ding Chen & Arben Imeraj, 2021. "Inverse and Quanto Inverse Options in a Black-Scholes World," Papers 2107.12041, arXiv.org, revised Oct 2022.
    12. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    13. Wujun Lv & Tao Pang & Xiaobao Xia & Jingzhou Yan, 2023. "Dynamic portfolio choice with uncertain rare-events risk in stock and cryptocurrency markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    14. José Almeida & Tiago Cruz Gonçalves, 2022. "A Systematic Literature Review of Volatility and Risk Management on Cryptocurrency Investment: A Methodological Point of View," Risks, MDPI, vol. 10(5), pages 1-18, May.
    15. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    16. Bandi, Federico M. & Renò, Roberto, 2022. "β in the tails," Journal of Econometrics, Elsevier, vol. 227(1), pages 134-150.
    17. Burda, Michael C., 2021. "Valuing cryptocurrencies: Three easy pieces," IRTG 1792 Discussion Papers 2021-011, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    19. Elisa Al`os & Eulalia Nualart & Makar Pravosud, 2023. "On the implied volatility of Inverse and Quanto Inverse options under stochastic volatility models," Papers 2401.00539, arXiv.org.
    20. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    21. Danial Saef & Yuanrong Wang & Tomaso Aste, 2022. "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing," Papers 2208.12614, arXiv.org, revised Sep 2022.
    22. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  17. Alexander Jakob Dautel & Wolfgang Karl Härdle & Stefan Lessmann & Hsin-Vonn Seow, 2020. "Forex exchange rate forecasting using deep recurrent neural networks," Digital Finance, Springer, vol. 2(1), pages 69-96, September.
    See citations under working paper version above.
  18. Ya Qian & Wolfgang Härdle & Cathy Yi-Hsuan Chen, 2019. "Modelling industry interdependency dynamics in a network context," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(1), pages 50-70, December.

    Cited by:

    1. Huynh, Toan Luu Duc & Foglia, Matteo & Doukas, John A., 2022. "COVID-19 and Tail-event Driven Network Risk in the Eurozone," Finance Research Letters, Elsevier, vol. 44(C).
    2. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).

  19. Chen, Shi & Karl Härdle, Wolfgang & López Cabrera, Brenda, 2019. "Regularization approach for network modeling of German power derivative market," Energy Economics, Elsevier, vol. 83(C), pages 180-196.

    Cited by:

    1. Yasir Alsaedi & Gurudeo Anand Tularam & Victor Wong, 2020. "Impact of Solar and Wind Prices on the Integrated Global Electricity Spot and Options Markets: A Time Series Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 337-353.
    2. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    3. He Jiang, 2023. "Forecasting global solar radiation using a robust regularization approach with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1989-2010, December.
    4. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.

  20. S. Nasekin & W. K. Härdle, 2019. "Model-driven statistical arbitrage on LETF option markets," Quantitative Finance, Taylor & Francis Journals, vol. 19(11), pages 1817-1837, November.

    Cited by:

    1. Erdinc Akyildirim & Ahmet Goncu & Alper Hekimoglu & Duc Khuong Nguyen & Ahmet Sensoy, 2023. "Statistical arbitrage: factor investing approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(4), pages 1295-1331, December.
    2. Lucas Schneider & Johannes Stübinger, 2020. "Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns," Mathematics, MDPI, vol. 8(9), pages 1-22, September.

  21. Michael Kostmann & Wolfgang K. Härdle, 2019. "Forecasting in Blockchain-Based Local Energy Markets," Energies, MDPI, vol. 12(14), pages 1-27, July.
    See citations under working paper version above.
  22. Xiu Xu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2019. "Dynamic credit default swap curves in a network topology," Quantitative Finance, Taylor & Francis Journals, vol. 19(10), pages 1705-1726, October.
    See citations under working paper version above.
  23. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    See citations under working paper version above.
  24. Yan Fan & Wolfgang Karl Härdle & Weining Wang & Lixing Zhu, 2018. "Single-Index-Based CoVaR With Very High-Dimensional Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 212-226, April.

    Cited by:

    1. Jun Jin & Tiefeng Ma & Jiajia Dai & Shuangzhe Liu, 2021. "Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates," Computational Statistics, Springer, vol. 36(1), pages 541-575, March.
    2. Xu, Qifa & Li, Mengting & Jiang, Cuixia & He, Yaoyao, 2019. "Interconnectedness and systemic risk network of Chinese financial institutions: A LASSO-CoVaR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    3. Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    4. Bonaccolto, Giovanni & Borri, Nicola & Consiglio, Andrea, 2023. "Breakup and default risks in the great lockdown," Journal of Banking & Finance, Elsevier, vol. 147(C).
    5. Eliana Christou & Michael Grabchak, 2022. "Estimation of Expected Shortfall Using Quantile Regression: A Comparison Study," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 725-753, August.
    6. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    7. Kangning Wang & Wen Shan, 2021. "Copula and composite quantile regression-based estimating equations for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 441-455, June.
    8. Anna Denkowska & Stanisław Wanat, 2020. "A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector," Risks, MDPI, vol. 8(2), pages 1-22, April.
    9. Kangning Wang & Mengjie Hao & Xiaofei Sun, 2021. "Robust and efficient estimating equations for longitudinal data partial linear models and its applications," Statistical Papers, Springer, vol. 62(5), pages 2147-2168, October.
    10. Wang, Kangning & Li, Shaomin & Zhang, Benle, 2021. "Robust communication-efficient distributed composite quantile regression and variable selection for massive data," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    11. Rong Jiang & Mengxian Sun, 2022. "Single-index composite quantile regression for ultra-high-dimensional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 443-460, June.
    12. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

  25. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.

    Cited by:

    1. Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Christis Katsouris, 2023. "Statistical Estimation for Covariance Structures with Tail Estimates using Nodewise Quantile Predictive Regression Models," Papers 2305.11282, arXiv.org, revised Jul 2023.

  26. Wolfgang Karl Härdle & David Kuo Chuen Lee & Sergey Nasekin & Alla Petukhina, 2018. "Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets," Journal of Asset Management, Palgrave Macmillan, vol. 19(1), pages 49-63, January.

    Cited by:

    1. Philipp Gschöpf & Wolfgang Karl Härdle & Andrija Mihoci, 2015. "TERES - Tail Event Risk Expectile based Shortfall," SFB 649 Discussion Papers SFB649DP2015-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Tim Schmitz & Ingo Hoffmann, 2020. "Re-evaluating cryptocurrencies' contribution to portfolio diversification -- A portfolio analysis with special focus on German investors," Papers 2006.06237, arXiv.org, revised Aug 2020.

  27. Chen Ying & Härdle Wolfgang K. & He Qiang & Majer Piotr, 2018. "Risk related brain regions detection and individual risk classification with 3D image FPCA," Statistics & Risk Modeling, De Gruyter, vol. 35(3-4), pages 89-110, July.

    Cited by:

    1. Khowaja, Kainat & Shcherbatyy, Mykhaylo & Härdle, Wolfgang Karl, 2021. "Surrogate Models for Optimization of Dynamical Systems," IRTG 1792 Discussion Papers 2021-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

  28. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.

    Cited by:

    1. Chiang, Thomas C., 2021. "Spillovers of U.S. market volatility and monetary policy uncertainty to global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2018-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    4. Long, Huaigang & Zhu, Yanjian & Chen, Lifang & Jiang, Yuexiang, 2019. "Tail risk and expected stock returns around the world," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 162-178.
    5. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    6. Chiang, Thomas C., 2023. "Real stock market returns and inflation: Evidence from uncertainty hypotheses," Finance Research Letters, Elsevier, vol. 53(C).
    7. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "Modelling systems with a mixture of I(d) and I(0) variables using the fractionally co-integrated VAR model," Economics Letters, Elsevier, vol. 181(C), pages 160-163.
    8. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    9. Ding, Yuanyi, 2023. "Does natural resources cause sustainable financial development or resources curse? Evidence from group of seven economies," Resources Policy, Elsevier, vol. 81(C).
    10. Salisu, Afees A. & Adediran, Idris & Omoke, Philip C. & Tchankam, Jean Paul, 2023. "Gold and tail risks," Resources Policy, Elsevier, vol. 80(C).
    11. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    12. Hadhri, Sinda, 2023. "News-based economic policy uncertainty and financial contagion: An international evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 63-76.
    13. Chen, Xiaoyu & Chiang, Thomas C., 2020. "Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market," Research in International Business and Finance, Elsevier, vol. 53(C).
    14. Chiang, Thomas C., 2019. "Economic policy uncertainty, risk and stock returns: Evidence from G7 stock markets," Finance Research Letters, Elsevier, vol. 29(C), pages 41-49.
    15. Klaus Grobys & Sami Vähämaa, 2020. "Another look at value and momentum: volatility spillovers," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1459-1479, November.
    16. Thomas C. Chiang, 2019. "Market Efficiency and News Dynamics: Evidence from International Equity Markets," Economies, MDPI, vol. 7(1), pages 1-17, February.
    17. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  29. Moro Russ A. & Härdle Wolfgang K. & Schäfer Dorothea, 2017. "Company rating with support vector machines," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 55-67, June.

    Cited by:

    1. Wosnitza, Jan Henrik, 2022. "Calibration alternatives to logistic regression and their potential for transferring the dispersion of discriminatory power into uncertainties of probabilities of default," Discussion Papers 04/2022, Deutsche Bundesbank.

  30. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Karl Härdle, 2017. "Confidence Corridors for Multivariate Generalized Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 70-85, January.

    Cited by:

    1. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
    4. Dette, Holger & Melas, Viatcheslav B. & Shpilev, Petr, 2017. "T-optimal discriminating designs for Fourier regression models," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 196-206.
    5. Kun Ho Kim & Wolfgang K. Härdle & Shih-Kang Chao, 2016. "Simultaneous Inference for the Partially Linear Model with a Multivariate Unknown Function when the Covariates are Measured with Errors," SFB 649 Discussion Papers SFB649DP2016-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  31. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.

    Cited by:

    1. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.

  32. Maria Grith & Wolfgang K. Härdle & Volker Krätschmer, 2017. "Reference-Dependent Preferences and the Empirical Pricing Kernel Puzzle," Review of Finance, European Finance Association, vol. 21(1), pages 269-298.

    Cited by:

    1. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    2. Ricardo Crisóstomo, 2021. "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    3. Chen Tong & Peter Reinhard Hansen & Zhuo Huang, 2021. "Option Pricing with State-dependent Pricing Kernel," Papers 2112.05308, arXiv.org, revised Apr 2022.
    4. Jiao, Yuhan & Liu, Qiang & Guo, Shuxin, 2021. "Pricing kernel monotonicity and term structure: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 123(C).
    5. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Oct 2022.

  33. Denis Belomestny & Wolfgang Karl Härdle & Ekaterina Krymova, 2017. "Sieve Estimation Of The Minimal Entropy Martingale Marginal Density With Application To Pricing Kernel Estimation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-21, September.

    Cited by:

    1. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.

  34. Wolfgang Karl Härdle & Brenda López Cabrera & Ostap Okhrin & Weining Wang, 2016. "Localizing Temperature Risk," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1491-1508, October.
    See citations under working paper version above.
  35. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.

    Cited by:

    1. Li Cai & Lisha Li & Simin Huang & Liang Ma & Lijian Yang, 2020. "Oracally efficient estimation for dense functional data with holiday effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 282-306, March.
    2. Gu, Lijie & Wang, Suojin & Yang, Lijian, 2021. "Smooth simultaneous confidence band for the error distribution function in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    3. Li Cai & Lijie Gu & Qihua Wang & Suojin Wang, 2021. "Simultaneous confidence bands for nonparametric regression with missing covariate data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1249-1279, December.
    4. Li, Xinyi & Wang, Li & Nettleton, Dan, 2019. "Sparse model identification and learning for ultra-high-dimensional additive partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 204-228.
    5. Yuanyuan Zhang & Lijian Yang, 2018. "A smooth simultaneous confidence band for correlation curve," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 247-269, June.
    6. Rong Liu & Yichuan Zhao, 2021. "Empirical likelihood inference for generalized additive partially linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 569-585, September.
    7. Jie Li & Jiangyan Wang & Lijian Yang, 2022. "Kolmogorov–Smirnov simultaneous confidence bands for time series distribution function," Computational Statistics, Springer, vol. 37(3), pages 1015-1039, July.
    8. Wang, Jiangyan & Gu, Lijie & Yang, Lijian, 2022. "Oracle-efficient estimation for functional data error distribution with simultaneous confidence band," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    9. Chen Zhong & Lijian Yang, 2021. "Simultaneous confidence bands for comparing variance functions of two samples based on deterministic designs," Computational Statistics, Springer, vol. 36(2), pages 1197-1218, June.

  36. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  37. Qihua Wang & Tao Zhang & Wolfgang Karl Härdle, 2016. "An Extended Single-index Model with Missing Response at Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1140-1152, December.

    Cited by:

    1. Ash Abebe & Huybrechts F. Bindele & Masego Otlaadisa & Boikanyo Makubate, 2021. "Robust estimation of single index models with responses missing at random," Statistical Papers, Springer, vol. 62(5), pages 2195-2225, October.
    2. M. Hristache & V. Patilea, 2017. "Conditional moment models with data missing at random," Biometrika, Biometrika Trust, vol. 104(3), pages 735-742.
    3. Wei Luo, 2022. "On efficient dimension reduction with respect to the interaction between two response variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 269-294, April.

  38. Härdle, Wolfgang Karl & Okhrin, Ostap & Wang, Weining, 2015. "Hidden Markov Structures For Dynamic Copulae," Econometric Theory, Cambridge University Press, vol. 31(5), pages 981-1015, October.

    Cited by:

    1. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    2. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    3. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    4. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    5. Marius Ötting & Roland Langrock & Antonello Maruotti, 2023. "A copula-based multivariate hidden Markov model for modelling momentum in football," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 9-27, March.
    6. Naumzik, Christof & Feuerriegel, Stefan & Nielsen, Anne Molgaard, 2023. "Data-driven dynamic treatment planning for chronic diseases," European Journal of Operational Research, Elsevier, vol. 305(2), pages 853-867.
    7. Shih-Feng Huang & Hsin-Han Chiang & Yu-Jun Lin, 2021. "A network autoregressive model with GARCH effects and its applications," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-18, July.
    8. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    9. Marius Ötting & Dimitris Karlis, 2023. "Football tracking data: a copula-based hidden Markov model for classification of tactics in football," Annals of Operations Research, Springer, vol. 325(1), pages 167-183, June.

  39. Cathy Chen & Wolfgang Härdle, 2015. "Common factors in credit defaults swap markets," Computational Statistics, Springer, vol. 30(3), pages 845-863, September.

    Cited by:

    1. Álvaro Chamizo & Alfonso Novales, 2019. "Looking through systemic credit risk: determinants, stress testing and market value," Documentos de Trabajo del ICAE 2019-27, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Alfonso Novales & Alvaro Chamizo, 2019. "Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components," JRFM, MDPI, vol. 12(3), pages 1-33, August.
    3. Xiu Xu & Wolfgang K. Härdle & Cathy Yi-Hsuan Chen, 2016. "Dynamic credit default swaps curves in a network topology," SFB 649 Discussion Papers SFB649DP2016-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Lidija Lovreta & Joaquín López Pascual, 2020. "Structural breaks in the interaction between bank and sovereign default risk," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(4), pages 531-559, December.
    5. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  40. Wolfgang Karl Härdle & Annette B. Vogt, 2015. "Ladislaus von Bortkiewicz—Statistician, Economist and a European Intellectual," International Statistical Review, International Statistical Institute, vol. 83(1), pages 17-35, April.

    Cited by:

    1. Ulrich Rendtel & Ulrike C. Wasmuht & Peter-Theodor Wilrich, 2021. "Emil Julius Gumbel," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 15(3), pages 273-291, December.

  41. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.

    Cited by:

    1. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    2. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. Taboga, Marco, 2016. "Option-implied probability distributions: How reliable? How jagged?," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 453-469.
    4. Brenda López Cabrera & Martin Odening & Matthias Ritter, 2013. "Pricing Rainfall Derivatives at the CME," SFB 649 Discussion Papers SFB649DP2013-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Xixuan Han & Boyu Wei & Hailiang Yang, 2018. "Index Options And Volatility Derivatives In A Gaussian Random Field Risk-Neutral Density Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-41, June.

  42. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.

    Cited by:

    1. Junni L. Zhang & Wolfgang K. Härdle & Cathy Y. Chen & Elisabeth Bommes, 2015. "Distillation of News Flow into Analysis of Stock Reactions," SFB 649 Discussion Papers SFB649DP2015-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.

  43. Wolfgang Karl Härdle & Yarema Okhrin & Weining Wang, 2015. "Uniform Confidence Bands for Pricing Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 376-413.

    Cited by:

    1. Denis Belomestny & Wolfgang Karl Härdle & Ekaterina Krymova, 2017. "Sieve Estimation Of The Minimal Entropy Martingale Marginal Density With Application To Pricing Kernel Estimation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-21, September.
    2. Christian Basteck & Tijmen R. Daniëls, 2010. "Every Symmetric 3 x 3 Global Game of Strategic Complementarities Is Noise Independent," SFB 649 Discussion Papers SFB649DP2010-061, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Alexander L. Baranovski, 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers SFB649DP2010-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Krzysztof Burnecki & Joanna Janczura & Rafał Weron, 2010. "Building Loss Models," SFB 649 Discussion Papers SFB649DP2010-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    6. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    8. Ulrich Horst & Santiago Moreno-Bromberg, 2011. "Efficiency and Equilibria in Games of Optimal Derivative Design," Papers 1107.0839, arXiv.org.
    9. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    10. Denis Belomestny & Shujie Ma & Wolfgang Karl Härdle, 2015. "Pricing Kernel Modeling," SFB 649 Discussion Papers SFB649DP2015-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Carolin Hecht & Katja Hanewald, 2010. "Sociodemographic, Economic, and Psychological Drivers of the Demand for Life Insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers SFB649DP2010-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
    16. Yuri Golubev & Wolfgang Härdle & Roman Timofeev, 2014. "Testing monotonicity of pricing kernels," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(4), pages 305-326, October.
    17. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    18. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Wolfgang Karl Härdle & Rouslan Moro & Linda Hoffmann, 2010. "Learning Machines Supporting Bankruptcy Prediction," SFB 649 Discussion Papers SFB649DP2010-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Ralf Sabiwalsky, 2010. "Executive Compensation Regulation and the Dynamics of the Pay-Performance Sensitivity," SFB 649 Discussion Papers SFB649DP2010-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.
    23. Vladimir Panov, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers SFB649DP2010-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  44. Shuzhuan Zheng & Lijian Yang & Wolfgang K. Härdle, 2014. "A Smooth Simultaneous Confidence Corridor for the Mean of Sparse Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 661-673, June.

    Cited by:

    1. Li Cai & Lisha Li & Simin Huang & Liang Ma & Lijian Yang, 2020. "Oracally efficient estimation for dense functional data with holiday effects," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 282-306, March.
    2. Gu, Lijie & Wang, Suojin & Yang, Lijian, 2021. "Smooth simultaneous confidence band for the error distribution function in nonparametric regression," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    3. Li Cai & Lijie Gu & Qihua Wang & Suojin Wang, 2021. "Simultaneous confidence bands for nonparametric regression with missing covariate data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1249-1279, December.
    4. Jiang, Jiakun & Lin, Huazhen & Zhong, Qingzhi & Li, Yi, 2022. "Analysis of multivariate non-gaussian functional data: A semiparametric latent process approach," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    5. Yuanyuan Zhang & Lijian Yang, 2018. "A smooth simultaneous confidence band for correlation curve," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 247-269, June.
    6. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.
    7. Hassan Sharghi Ghale-Joogh & S. Mohammad E. Hosseini-Nasab, 2021. "On mean derivative estimation of longitudinal and functional data: from sparse to dense," Statistical Papers, Springer, vol. 62(4), pages 2047-2066, August.
    8. Li Cai & Lijian Yang, 2015. "A smooth simultaneous confidence band for conditional variance function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 632-655, September.
    9. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2022. "Universal Local Linear Kernel Estimators in Nonparametric Regression," Mathematics, MDPI, vol. 10(15), pages 1-28, July.
    10. Jie Li & Jiangyan Wang & Lijian Yang, 2022. "Kolmogorov–Smirnov simultaneous confidence bands for time series distribution function," Computational Statistics, Springer, vol. 37(3), pages 1015-1039, July.
    11. Wang, Jiangyan & Gu, Lijie & Yang, Lijian, 2022. "Oracle-efficient estimation for functional data error distribution with simultaneous confidence band," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
    12. Kun Huang & Sijie Zheng & Lijian Yang, 2022. "Inference for dependent error functional data with application to event-related potentials," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1100-1120, December.
    13. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    14. Jiangyan Wang & Suojin Wang & Lijian Yang, 2016. "Simultaneous confidence bands for the distribution function of a finite population and of its superpopulation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 692-709, December.
    15. Chen Zhong & Lijian Yang, 2021. "Simultaneous confidence bands for comparing variance functions of two samples based on deterministic designs," Computational Statistics, Springer, vol. 36(2), pages 1197-1218, June.
    16. Jialiang Li & Yaguang Li & Tailen Hsing, 2022. "On functional processes with multiple discontinuities," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 933-972, July.
    17. Lijie Gu & Suojin Wang & Lijian Yang, 2019. "Simultaneous confidence bands for the distribution function of a finite population in stratified sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 983-1005, August.
    18. Yueying Wang & Guannan Wang & Li Wang & R. Todd Ogden, 2020. "Simultaneous confidence corridors for mean functions in functional data analysis of imaging data," Biometrics, The International Biometric Society, vol. 76(2), pages 427-437, June.

  45. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2014. "Generalized dynamic semi‐parametric factor models for high‐dimensional non‐stationary time series," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 101-131, June.

    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers SFB649DP2017-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    3. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.

  46. Alena Bömmel & Song Song & Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Härdle, 2014. "Risk Patterns and Correlated Brain Activities. Multidimensional Statistical Analysis of fMRI Data in Economic Decision Making Study," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 489-514, July.

    Cited by:

    1. Ying Chen & Wolfgang K. Härdle & Qiang He & Piotr Majer, 2015. "Risk Related Brain Regions Detected with 3D Image FPCA," SFB 649 Discussion Papers SFB649DP2015-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Chen Ying & Härdle Wolfgang K. & He Qiang & Majer Piotr, 2018. "Risk related brain regions detection and individual risk classification with 3D image FPCA," Statistics & Risk Modeling, De Gruyter, vol. 35(3-4), pages 89-110, July.
    4. Shih-Kang Chao & Wolfgang K. Härdle & Chen Huang, 2016. "Multivariate Factorisable Sparse Asymmetric Least Squares Regression," SFB 649 Discussion Papers SFB649DP2016-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    6. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Piotr Majer & Peter Mohr & Hauke Heekeren & Wolfgang Karl Härdle, 2014. "Portfolio Decisions and Brain Reactions via the CEAD method," SFB 649 Discussion Papers SFB649DP2014-036, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Yingxing Li & Chen Huang & Wolfgang Karl Härdle, 2017. "Spatial Functional Principal Component Analysis with Applications to Brain Image Data," SFB 649 Discussion Papers SFB649DP2017-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Casado-Aranda, Luis-Alberto & Liébana-Cabanillas, Francisco & Sánchez-Fernández, Juan, 2018. "A Neuropsychological Study on How Consumers Process Risky and Secure E-payments," Journal of Interactive Marketing, Elsevier, vol. 43(C), pages 151-164.
    10. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
    11. Li, Yingxing & Huang, Chen & Härdle, Wolfgang K., 2019. "Spatial functional principal component analysis with applications to brain image data," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 263-274.
    12. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  47. Barbara Choroś-Tomczyk & Wolfgang Karl H�rdle & Ludger Overbeck, 2014. "Copula dynamics in CDOs," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1573-1585, September.

    Cited by:

    1. Sara Cecchetti & Giovanna Nappo, 2012. "A dynamic default dependence model," Temi di discussione (Economic working papers) 892, Bank of Italy, Economic Research and International Relations Area.
    2. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    3. Koziol, Philipp & Schell, Carmen & Eckhardt, Meik, 2015. "Credit risk stress testing and copulas: Is the Gaussian copula better than its reputation?," Discussion Papers 46/2015, Deutsche Bundesbank.
    4. Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Hyun Jin Jang & Kiseop Lee & Kyungsub Lee, 2020. "Systemic Risk in Market Microstructure of Crude Oil and Gasoline Futures Prices: A Hawkes Flocking Model Approach," Papers 2012.04181, arXiv.org.
    6. Stefan Hochrainer-Stigler & Juraj Balkovič & Kadri Silm & Anna Timonina-Farkas, 2019. "Large scale extreme risk assessment using copulas: an application to drought events under climate change for Austria," Computational Management Science, Springer, vol. 16(4), pages 651-669, October.
    7. Lu, Meng-Jou & Chen, Cathy Yi-Hsuan & Härdle, Karl Wolfgang & Härdle, 2015. "Copula-Based Factor Model for Credit Risk Analysis," SFB 649 Discussion Papers SFB649DP2015-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Copula-Based Factor Model for Credit Risk Analysis," Papers 2009.12092, arXiv.org, revised Oct 2020.

  48. Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2013. "Oracally Efficient Two-Step Estimation of Generalized Additive Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 619-631, June.
    See citations under working paper version above.
  49. Maria Grith & Wolfgang Härdle & Juhyun Park, 2013. "Shape Invariant Modeling of Pricing Kernels and Risk Aversion," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 370-399, March.

    Cited by:

    1. Jonathan Dark, 2021. "The lead of oil price rises on US equity market beliefs and preferences," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1861-1887, November.
    2. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    3. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
    4. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).
    5. Hayette Gatfaoui, 2015. "Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas," Post-Print hal-01563015, HAL.
    6. Maria Grith & Wolfgang K. Härdle & Alois Kneip & Heiko Wagner, 2016. "Functional Principal Component Analysis for Derivatives of Multivariate Curves," SFB 649 Discussion Papers SFB649DP2016-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Denis Belomestny & Shujie Ma & Wolfgang Karl Härdle, 2015. "Pricing Kernel Modeling," SFB 649 Discussion Papers SFB649DP2015-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Kiesel, Rüdiger & Rahe, Florentin, 2017. "Option pricing under time-varying risk-aversion with applications to risk forecasting," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 120-138.
    9. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
    11. Salim Morched & Ben Mohamed Ezzeddine & Anis Jarboui, 2023. "The impact of innovation type on the performance and social responsibility of French manufacturing companies," Environment Systems and Decisions, Springer, vol. 43(3), pages 433-452, September.
    12. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    13. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    14. Liao, Wen Ju & Sung, Hao-Chang, 2020. "Implied risk aversion and pricing kernel in the FTSE 100 index," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    15. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.

  50. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "Valuation of collateralized debt obligations with hierarchical Archimedean copulae," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 42-62.

    Cited by:

    1. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2016. "Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(4), pages 989-1007, December.
    2. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    3. Zhu, Wenjun & Wang, Chou-Wen & Tan, Ken Seng, 2016. "Structure and estimation of Lévy subordinated hierarchical Archimedean copulas (LSHAC): Theory and empirical tests," Journal of Banking & Finance, Elsevier, vol. 69(C), pages 20-36.
    4. Fang, Jun & Jiang, Fan & Liu, Yong & Yang, Jingping, 2020. "Copula-based Markov process," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 166-187.
    5. Bernardi Enrico & Romagnoli Silvia, 2015. "A copula-based hierarchical hybrid loss distribution," Statistics & Risk Modeling, De Gruyter, vol. 32(1), pages 73-87, April.
    6. Stefan Hochrainer-Stigler & Juraj Balkovič & Kadri Silm & Anna Timonina-Farkas, 2019. "Large scale extreme risk assessment using copulas: an application to drought events under climate change for Austria," Computational Management Science, Springer, vol. 16(4), pages 651-669, October.
    7. D. V. Boreiko & Y. M. Kaniovski & G. Ch. Pflug, 2017. "Numerical Modeling of Dependent Credit Rating Transitions with Asynchronously Moving Industries," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 499-516, March.
    8. Enrico Bernardi & Silvia Romagnoli, 2016. "Distorted Copula-Based Probability Distribution of a Counting Hierarchical Variable: A Credit Risk Application," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 285-310, March.
    9. Anna Timonina & Stefan Hochrainer‐Stigler & Georg Pflug & Brenden Jongman & Rodrigo Rojas, 2015. "Structured Coupling of Probability Loss Distributions: Assessing Joint Flood Risk in Multiple River Basins," Risk Analysis, John Wiley & Sons, vol. 35(11), pages 2102-2119, November.
    10. Lu, Meng-Jou & Chen, Cathy Yi-Hsuan & Härdle, Karl Wolfgang & Härdle, 2015. "Copula-Based Factor Model for Credit Risk Analysis," SFB 649 Discussion Papers SFB649DP2015-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Copula-Based Factor Model for Credit Risk Analysis," Papers 2009.12092, arXiv.org, revised Oct 2020.
    12. Okhrin, Ostap & Xu, Ya Fei, 2017. "A comparison study of pricing credit default swap index tranches with convex combination of copulae," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 193-217.

  51. Stephan Stahlschmidt & Helmut Tausendteufel & Wolfgang K. Härdle, 2013. "Bayesian networks for sex-related homicides: structure learning and prediction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(6), pages 1155-1171, June.

    Cited by:

    1. E. Cene & F. Karaman, 2015. "Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1572-1590, July.

  52. Härdle Wolfgang Karl & Okhrin Ostap & Okhrin Yarema, 2013. "Dynamic structured copula models," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 361-388, December.

    Cited by:

    1. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.

  53. Wolfgang Karl Härdle & Brenda López Cabrera, 2012. "The Implied Market Price of Weather Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(1), pages 59-95, February.
    See citations under working paper version above.
  54. Mengmeng Guo & Wolfgang Härdle, 2012. "Simultaneous confidence bands for expectile functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(4), pages 517-541, October.

    Cited by:

    1. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Xianhua Dai & Wolfgang Karl Härdle & Keming Yu, 2014. "Do Maternal Health Problems Influence Child's Worrying Status? Evidence from British Cohort Study," SFB 649 Discussion Papers SFB649DP2014-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. P. Burdejova & W.K. Härdle & Kokoszka & Q.Xiong, 2015. "Change point and trend analyses of annual expectile curves of tropical storms," SFB 649 Discussion Papers SFB649DP2015-029, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Stéphane Girard & Gilles Stupfler & Antoine Usseglio‐Carleve, 2022. "Nonparametric extreme conditional expectile estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 78-115, March.
    5. Xianhua Dai & Wolfgang Karl Härdle & Keming Yu, 2016. "Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2941-2955, December.
    6. Mengmeng Guo & Lhan Zhou & Jianhua Z. Huang & Wolfgang Karl Härdle, 2013. "Functional Data Analysis of Generalized Quantile Regressions," SFB 649 Discussion Papers SFB649DP2013-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Stephan Stahlschmidt & Matthias Eckardt & Wolfgang K. Härdle, 2014. "Expectile Treatment Effects: An efficient alternative to compute the distribution of treatment effects," SFB 649 Discussion Papers SFB649DP2014-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Härdle, 2014. "Confidence Corridors for Multivariate Generalized Quantile Regression," SFB 649 Discussion Papers SFB649DP2014-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    10. Mustapha Rachdi & Ali Laksaci & Noriah M. Al-Kandari, 2022. "Expectile regression for spatial functional data analysis (sFDA)," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(5), pages 627-655, July.

  55. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.

    Cited by:

    1. Shih-Kang Chao & Wolfgang Karl Härdle & Hien Pham-Thu, 2014. "Credit Risk Calibration based on CDS Spreads," SFB 649 Discussion Papers SFB649DP2014-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    3. Xiaofeng Lv & Rui Li, 2013. "Smoothed empirical likelihood analysis of partially linear quantile regression models with missing response variables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 317-347, October.
    4. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    5. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    6. Majid Mojirsheibani, 2022. "On the maximal deviation of kernel regression estimators with NMAR response variables," Statistical Papers, Springer, vol. 63(5), pages 1677-1705, October.
    7. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.
    8. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Härdle, 2014. "Confidence Corridors for Multivariate Generalized Quantile Regression," SFB 649 Discussion Papers SFB649DP2014-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Ali Al-Sharadqah & Majid Mojirsheibani, 2020. "A simple approach to construct confidence bands for a regression function with incomplete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 81-99, March.
    10. Wu, Chaojiang & Yu, Yan, 2014. "Partially linear modeling of conditional quantiles using penalized splines," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 170-187.

  56. Härdle, Wolfgang K. & Song, Song, 2010. "Confidence Bands In Quantile Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1180-1200, August.

    Cited by:

    1. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    2. Alona Zharova & Andrija Mihoci & Wolfgang Karl Härdle, 2016. "Academic Ranking Scales in Economics: Prediction and Imputation," SFB 649 Discussion Papers SFB649DP2016-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Kim, Kun Ho & Chao, Shih-Kang & Härdle, Wolfgang Karl, 2020. "Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function," IRTG 1792 Discussion Papers 2020-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Katharina Proksch, 2016. "On confidence bands for multivariate nonparametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(1), pages 209-236, February.
    5. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    6. Weining Wang & Ihtiyor Bobojonov & Wolfgang Karl Härdle & Martin Odening, 2011. "Increasing Weather Risk: Fact or Fiction?," SFB 649 Discussion Papers SFB649DP2011-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Duygun, Meryem & Tunaru, Radu & Vioto, Davide, 2021. "Herding by corporates in the US and the Eurozone through different market conditions," Journal of International Money and Finance, Elsevier, vol. 110(C).
    8. Toshio Honda, 2013. "Nonparametric quantile regression with heavy-tailed and strongly dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 23-47, February.
    9. Mengmeng Guo & Lhan Zhou & Jianhua Z. Huang & Wolfgang Karl Härdle, 2013. "Functional Data Analysis of Generalized Quantile Regressions," SFB 649 Discussion Papers SFB649DP2013-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Marc Hallin & Zudi Lu & Davy Paindaveine & Miroslav Siman, 2012. "Local Constant and Local Bilinear Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2012-003, ULB -- Universite Libre de Bruxelles.
    11. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.
    12. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Härdle, 2014. "Confidence Corridors for Multivariate Generalized Quantile Regression," SFB 649 Discussion Papers SFB649DP2014-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Ali Al-Sharadqah & Majid Mojirsheibani, 2020. "A simple approach to construct confidence bands for a regression function with incomplete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 81-99, March.
    14. Hasan, Iftekhar & Tunaru, Radu & Vioto, Davide, 2023. "Herding behavior and systemic risk in global stock markets," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 107-133.

  57. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.

    Cited by:

    1. Jun Lu & Shao Yi, 2022. "Reducing Overestimating and Underestimating Volatility via the Augmented Blending-ARCH Model," Applied Economics and Finance, Redfame publishing, vol. 9(2), pages 48-59, May.
    2. Marcin Fałdziński & Piotr Fiszeder & Witold Orzeszko, 2020. "Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression," Energies, MDPI, vol. 14(1), pages 1-18, December.
    3. Pedro Correia S. Bezerra & Pedro Henrique M. Albuquerque, 2017. "Volatility forecasting via SVR–GARCH with mixture of Gaussian kernels," Computational Management Science, Springer, vol. 14(2), pages 179-196, April.
    4. Hao Sun & Bo Yu, 2020. "Forecasting Financial Returns Volatility: A GARCH-SVR Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 451-471, February.
    5. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2022. "Corporate Bankruptcy Prediction Using Machine Learning Methodologies with a Focus on Sequential Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1231-1249, March.
    6. Lux, Marius & Härdle, Wolfgang Karl & Lessmann, Stefan, 2018. "Data Driven Value-at-Risk Forecasting using a SVR-GARCH-KDE Hybrid," IRTG 1792 Discussion Papers 2018-001, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Yushu Li & Hyunjoo Kim Karlsson, 2023. "Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1765-1790, April.
    8. Gaoxiu Qiao & Gongyue Jiang, 2023. "VIX futures pricing based on high‐frequency VIX: A hybrid approach combining SVR with parametric models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1238-1260, September.
    9. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis, 2012. "Directional forecasting in financial time series using support vector machines: The USD/Euro exchange rate," DUTH Research Papers in Economics 5-2012, Democritus University of Thrace, Department of Economics.
    10. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "An information diffusion-based model of oil futures price," Energy Economics, Elsevier, vol. 36(C), pages 518-525.
    11. Yao, Yuan & Zhao, Yang & Li, Yan, 2022. "A volatility model based on adaptive expectations: An improvement on the rational expectations model," International Review of Financial Analysis, Elsevier, vol. 82(C).
    12. Chen, Shiyi, 2013. "What is the potential impact of a taxation system reform on carbon abatement and industrial growth in China?," Economic Systems, Elsevier, vol. 37(3), pages 369-386.
    13. Wang, Xinyu & Qi, Zikang & Huang, Jianglu, 2023. "How do monetary shock, financial crisis, and quotation reform affect the long memory of exchange rate volatility? Evidence from major currencies," Economic Modelling, Elsevier, vol. 120(C).
    14. Yaxiong Zeng & Diego Klabjan, 2017. "Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling," Papers 1706.01833, arXiv.org, revised Jun 2018.
    15. Jun Lu & Shao Yi, 2022. "Reducing overestimating and underestimating volatility via the augmented blending-ARCH model," Papers 2203.12456, arXiv.org.
    16. Nawaf Almaskati, 2022. "Machine learning in finance: Major applications, issues, metrics, and future trends," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-32, September.
    17. Maciej Zieba & Wolfgang K. Härdle, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers SFB649DP2016-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.
    19. Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023. "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 285-305, June.

  58. Chen, Ying & Härdle, Wolfgang Karl & Pigorsch, Uta, 2010. "Localized Realized Volatility Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1376-1393.

    Cited by:

    1. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    2. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    4. Ruprecht Puchstein & Philip Preuß, 2016. "Testing for Stationarity in Multivariate Locally Stationary Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 3-29, January.
    5. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    6. Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
    7. Francesco Audrino & Simon D. Knaus, 2016. "Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1485-1521, December.
    8. Lutz, Benjamin Johannes & Pigorsch, Uta & Rotfuß, Waldemar, 2013. "Nonlinearity in cap-and-trade systems: The EUA price and its fundamentals," ZEW Discussion Papers 13-001, ZEW - Leibniz Centre for European Economic Research.
    9. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    10. Wolfgang Karl Härdle & Andrija Mihoci & Christopher Hian-Ann Ting, 2014. "Adaptive Order Flow Forecasting with Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2014-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Philip Preuss & Ruprecht Puchstein & Holger Dette, 2015. "Detection of Multiple Structural Breaks in Multivariate Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 654-668, June.
    13. Li, Xinjue & Zboňáková, Lenka & Wang, Weining & Härdle, Wolfgang Karl, 2019. "Combining Penalization and Adaption in High Dimension with Application in Bond Risk Premia Forecasting," IRTG 1792 Discussion Papers 2019-030, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    14. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
    15. Ying Chen & Bo Li, 2017. "An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 371-388, July.
    16. Golosnoy, Vasyl & Ragulin, Sergiy & Schmid, Wolfgang, 2011. "CUSUM control charts for monitoring optimal portfolio weights," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2991-3009, November.
    17. Hong Li & Johnny Siu-Hang Li, 2017. "Optimizing the Lee-Carter Approach in the Presence of Structural Changes in Time and Age Patterns of Mortality Improvements," Demography, Springer;Population Association of America (PAA), vol. 54(3), pages 1073-1095, June.
    18. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    19. Buncic, Daniel & Gisler, Katja I. M., 2015. "Global Equity Market Volatility Spillovers: A Broader Role for the United States," Economics Working Paper Series 1508, University of St. Gallen, School of Economics and Political Science.
    20. Kley, Tobias & Preuss, Philip & Fryzlewicz, Piotr, 2019. "Predictive, finite-sample model choice for time series under stationarity and non-stationarity," LSE Research Online Documents on Economics 101748, London School of Economics and Political Science, LSE Library.
    21. Lim, Kian Guan & Chen, Ying & Yap, Nelson K.L., 2019. "Intraday information from S&P 500 Index futures options," Journal of Financial Markets, Elsevier, vol. 42(C), pages 29-55.
    22. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    23. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    24. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    25. Ming-Hsien Chen & Vivian Tai, 2014. "The price discovery of day trading activities in futures market," Review of Derivatives Research, Springer, vol. 17(2), pages 217-239, July.
    26. Ying Chen & Bo Li & Linlin Niu, 2013. "A Local Vector Autoregressive Framework and its Applications to Multivariate Time Series Monitoring and Forecasting," Working Papers 2013-12-05, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    27. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    28. Won-Tak Hong & Jiwon Lee & Eunju Hwang, 2020. "A Note on the Asymptotic Normality Theory of the Least Squares Estimates in Multivariate HAR-RV Models," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    29. Chen, Ying & Niu, Linlin, 2014. "Adaptive dynamic Nelson–Siegel term structure model with applications," Journal of Econometrics, Elsevier, vol. 180(1), pages 98-115.
    30. Dedy Dwi Prastyo & Wolfgang Karl Härdle, 2014. "Localising Forward Intensities for Multiperiod Corporate Default," SFB 649 Discussion Papers SFB649DP2014-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    31. Chao Zhang & Piotr Kokoszka & Alexander Petersen, 2022. "Wasserstein autoregressive models for density time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 30-52, January.
    32. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.

  59. Wolfgang Karl Härdle & Brenda López Cabrera, 2010. "Calibrating CAT Bonds for Mexican Earthquakes," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(3), pages 625-650, September.

    Cited by:

    1. Giuricich, Mario Nicoló & Burnecki, Krzysztof, 2019. "Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 498-513.
    2. Harsh K. Mistry & Domenico Lombardi, 2023. "A stochastic exposure model for seismic risk assessment and pricing of catastrophe bonds," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(1), pages 803-829, May.
    3. Ma, Zong-Gang & Ma, Chao-Qun, 2013. "Pricing catastrophe risk bonds: A mixed approximation method," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 243-254.
    4. Carolyn W. Chang & Jack S. K. Chang & Min‐Teh Yu & Yang Zhao, 2020. "Portfolio optimization in the catastrophe space," European Financial Management, European Financial Management Association, vol. 26(5), pages 1414-1448, November.
    5. Chang Carolyn W. & Feng Yalan, 2021. "Hurricane Bond Price Dependency on Underlying Hurricane Parameters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 15(1), pages 1-21, January.
    6. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Zied Chaieb & Djibril Gueye, 2022. "Pricing zero-coupon CAT bonds using the enlargement of ltration theory: a general framework," Papers 2208.02609, arXiv.org.
    8. Denis-Alexandre Trottier & Van Son Lai, 2017. "Reinsurance or CAT Bond? How to Optimally Combine Both," Working Papers 2017-003, Department of Research, Ipag Business School.
    9. Martin Eling, 2013. "Recent Research Developments Affecting Nonlife Insurance—The CAS Risk Premium Project 2011 Update," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 16(1), pages 35-46, March.
    10. Nowak, Piotr & Romaniuk, Maciej, 2013. "Pricing and simulations of catastrophe bonds," Insurance: Mathematics and Economics, Elsevier, vol. 52(1), pages 18-28.
    11. Shao, Jia & Papaioannou, Apostolos D. & Pantelous, Athanasios A., 2017. "Pricing and simulating catastrophe risk bonds in a Markov-dependent environment," Applied Mathematics and Computation, Elsevier, vol. 309(C), pages 68-84.
    12. Y. Esmaeelzade Aghdam & A. Neisy & A. Adl, 2024. "Simulating and Pricing CAT Bonds Using the Spectral Method Based on Chebyshev Basis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 423-435, January.
    13. Joanne Ho & Martin Odening, 2009. "Weather-based estimation of wildfire risk," SFB 649 Discussion Papers SFB649DP2009-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Sukono & Hafizan Juahir & Riza Andrian Ibrahim & Moch Panji Agung Saputra & Yuyun Hidayat & Igif Gimin Prihanto, 2022. "Application of Compound Poisson Process in Pricing Catastrophe Bonds: A Systematic Literature Review," Mathematics, MDPI, vol. 10(15), pages 1-19, July.
    15. Han-Bin KANG & Hsuling CHANG & Tsangyao CHANG, 2022. "Catastrophe Reinsurance Pricing -Modification of Dynamic Asset-Liability Management," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-20, December.
    16. Têtu Alexandre & Lai Van Son & Soumaré Issouf & Gendron Michel, 2015. "Hedging Flood Losses Using Cat Bonds," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 149-184, July.
    17. Loretta Mastroeni & Alessandro Mazzoccoli & Maurizio Naldi, 2022. "Pricing Cat Bonds for Cloud Service Failures," JRFM, MDPI, vol. 15(10), pages 1-18, October.
    18. Ben Ammar, Semir & Braun, Alexander & Eling, Martin, 2015. "Alternative Risk Transfer and Insurance-Linked Securities: Trends, Challenges and New Market Opportunities," I.VW HSG Schriftenreihe, University of St.Gallen, Institute of Insurance Economics (I.VW-HSG), volume 56, number 56.
    19. Jeanne, Olivier & Borensztein, Eduardo & Cavallo, Eduardo, 2015. "The Welfare Gains from Macro-Insurance Against Natural Disasters," CEPR Discussion Papers 10915, C.E.P.R. Discussion Papers.
    20. Alexis Louaas & Pierre Picard, 2017. "Optimal insurance for catastrophic risk: theory and application to nuclear corporate liability," Working Papers hal-01527478, HAL.
    21. Braun, Alexander, 2011. "Pricing catastrophe swaps: A contingent claims approach," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 520-536.
    22. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    23. Zied Chaieb & Djibril Gueye, 2022. "Pricing zero-coupon CAT bonds using the enlargement of ltration theory: a general framework ," Post-Print hal-03745077, HAL.
    24. Krzysztof Burnecki & Mario Nicoló Giuricich, 2017. "Stable Weak Approximation at Work in Index-Linked Catastrophe Bond Pricing," Risks, MDPI, vol. 5(4), pages 1-19, December.
    25. Lo, Chien-Ling & Lee, Jin-Ping & Yu, Min-Teh, 2013. "Valuation of insurers’ contingent capital with counterparty risk and price endogeneity," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5025-5035.

  60. Wolfgang Härdle & Yuh-Jye Lee & Dorothea Schäfer & Yi-Ren Yeh, 2009. "Variable selection and oversampling in the use of smooth support vector machines for predicting the default risk of companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 512-534.

    Cited by:

    1. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    2. Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2017. "Forecasting the U.S. Real House Price Index," Papers 1707.04868, arXiv.org.
    3. Wolfgang Karl Härdle & Dedy Dwi Prastyo & Christian Hafner, 2012. "Support Vector Machines with Evolutionary Feature Selection for Default Prediction," SFB 649 Discussion Papers SFB649DP2012-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Giacomo Caterini, 2018. "Classifying Firms with Text Mining," DEM Working Papers 2018/09, Department of Economics and Management.
    5. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    6. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
    7. Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    8. Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras, 2016. "Testing Exchange Rate Models in a Small Open Economy: an SVR Approach," Bulletin of Applied Economics, Risk Market Journals, vol. 3(2), pages 9-29.
    9. He Jiang, 2022. "A novel robust structural quadratic forecasting model and applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1156-1180, September.
    10. Natalia Nehrebecka, 2021. "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 719-736.
    11. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis, 2019. "Forecasting transportation demand for the U.S. market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 195-214.
    12. Wolfgang Karl Härdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Vasilios Plakandaras & Elie Bouri & Rangan Gupta, 2019. "Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?," Working Papers 201980, University of Pretoria, Department of Economics.
    14. Li, Hui & Sun, Jie, 2012. "Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples – Evidence from the Chinese hotel industry," Tourism Management, Elsevier, vol. 33(3), pages 622-634.
    15. Theodore Syriopoulos & Michael Tsatsaronis & Ioannis Karamanos, 2021. "Support Vector Machine Algorithms: An Application to Ship Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 55-87, January.
    16. Bai, Qing & Tian, Shaonan, 2020. "Innovate or die: Corporate innovation and bankruptcy forecasts," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 88-108.
    17. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2022. "Corporate Bankruptcy Prediction Using Machine Learning Methodologies with a Focus on Sequential Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1231-1249, March.
    18. Tian, Shaonan & Yu, Yan & Guo, Hui, 2015. "Variable selection and corporate bankruptcy forecasts," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 89-100.
    19. Nehrebecka Natalia, 2018. "Predicting the Default Risk of Companies. Comparison of Credit Scoring Models: Logit Vs Support Vector Machines," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(2), pages 54-73, June.
    20. Ligang Zhou & Kin Keung Lai, 2017. "AdaBoost Models for Corporate Bankruptcy Prediction with Missing Data," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 69-94, June.
    21. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    22. Li, Hui & Hong, Lu-Yao & He, Jia-Xun & Xu, Xuan-Guo & Sun, Jie, 2013. "Small sample-oriented case-based kernel predictive modeling and its economic forecasting applications under n-splits-k-times hold-out assessment," Economic Modelling, Elsevier, vol. 33(C), pages 747-761.
    23. Kea BARET & Theophilos PAPADIMITRIOU, 2019. "On the Stability and Growth Pact compliance: what is predictable with machine learning?," Working Papers of BETA 2019-48, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    24. Bommes, Elisabeth & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2018. "Textual Sentiment and Sector specific reaction," IRTG 1792 Discussion Papers 2018-043, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    25. Jie Sun, 2012. "Integration Of Random Sample Selection, Support Vector Machines And Ensembles For Financial Risk Forecasting With An Empirical Analysis On The Necessity Of Feature Selection," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(4), pages 229-246, October.
    26. Alessandra Amendola & Francesco Giordano & Maria Lucia Parrella & Marialuisa Restaino, 2017. "Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 355-368, August.
    27. Alessandra Amendola & Marialuisa Restaino & Luca Sensini, 2010. "Variabile Selection in Forecasting Models for Corporate Bankruptcy," Working Papers 3_216, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    28. Tian, Shaonan & Yu, Yan, 2017. "Financial ratios and bankruptcy predictions: An international evidence," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 510-526.
    29. Maciej Zieba & Wolfgang K. Härdle, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers SFB649DP2016-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.

  61. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2009. "Dynamic semiparametric factor models in risk neutral density estimation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 93(4), pages 387-402, December.
    See citations under working paper version above.
  62. P. Čížek & W. Härdle & V. Spokoiny, 2009. "Adaptive pointwise estimation in time-inhomogeneous conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 248-271, July.

    Cited by:

    1. Schröder, Anna Louise & Fryzlewicz, Piotr, 2013. "Adaptive trend estimation in financial time series via multiscale change-point-induced basis recovery," MPRA Paper 52379, University Library of Munich, Germany.
    2. Xiu Xu & Andrija Mihoci & Wolfgang Karl Hardle, 2020. "lCARE -- localizing Conditional AutoRegressive Expectiles," Papers 2009.13215, arXiv.org.
    3. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2022. "SONIC: SOcial Network analysis with Influencers and Communities," Journal of Econometrics, Elsevier, vol. 228(2), pages 177-220.
    4. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    5. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
    6. Wolfgang Karl Härdle & Andrija Mihoci & Christopher Hian-Ann Ting, 2014. "Adaptive Order Flow Forecasting with Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2014-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    9. Cizek, P., 2010. "Modelling Conditional Heteroscedasticity in Nonstationary Series," Other publications TiSEM a5a7b05f-5f1f-46ed-8ce8-5, Tilburg University, School of Economics and Management.
    10. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    11. Härdle Wolfgang Karl & Okhrin Ostap & Okhrin Yarema, 2013. "Dynamic structured copula models," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 361-388, December.
    12. Meister, Alexander & Kreiß, Jens-Peter, 2016. "Statistical inference for nonparametric GARCH models," Stochastic Processes and their Applications, Elsevier, vol. 126(10), pages 3009-3040.
    13. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    14. Chen, C. Y-H. & Härdle, W. K. & Klochkov, Y., 2019. "Influencers and Communities in Social Networks," Cambridge Working Papers in Economics 1998, Faculty of Economics, University of Cambridge.
    15. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
    16. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.
    17. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2019. "SONIC: SOcial Network with Influencers and Communities," IRTG 1792 Discussion Papers 2019-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    18. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
    19. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Dedy Dwi Prastyo & Wolfgang Karl Härdle, 2014. "Localising Forward Intensities for Multiperiod Corporate Default," SFB 649 Discussion Papers SFB649DP2014-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  63. Ralf Brüggemann & Wolfgang Härdle & Julius Mungo & Carsten Trenkler, 2008. "VAR Modeling for Dynamic Loadings Driving Volatility Strings," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 361-381, Summer.

    Cited by:

    1. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2014. "Inference in VARs with Conditional Heteroskedasticity of Unknown Form," Working Papers 14-21, University of Mannheim, Department of Economics.
    2. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Eduardo Roca & Gurudeo Anand Tularam, 2012. "Which way does water flow? An econometric analysis of the global price integration of water stocks," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 2935-2944, August.
    4. Eduardo Roca & Victor S.H. Wong & Gurudeo Anand Tularam, 2010. "Are socially responsible investment markets worldwide integrated?," Accounting Research Journal, Emerald Group Publishing Limited, vol. 23(3), pages 281-301, November.
    5. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  64. Chen, Ying & Härdle, Wolfgang & Jeong, Seok-Oh, 2008. "Nonparametric Risk Management With Generalized Hyperbolic Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 910-923.

    Cited by:

    1. Michal Skorepa, 2014. "Concurrent Capital Buffers in a Banking Group," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2013/2014, chapter 0, pages 128-136, Czech National Bank.
    2. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    3. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Hambuckers, Julien & Heuchenne, Cedric, 2017. "A robust statistical approach to select adequate error distributions for financial returns," LIDAM Reprints ISBA 2017031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
    6. Härdle Wolfgang Karl & Okhrin Ostap & Okhrin Yarema, 2013. "Dynamic structured copula models," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 361-388, December.
    7. Chen, Ying & Härdle, Wolfgang & Spokoiny, Vladimir, 2010. "GHICA -- Risk analysis with GH distributions and independent components," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 255-269, March.
    8. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    9. Adam Misiorek & Rafal Weron, 2010. "Heavy-tailed distributions in VaR calculations," HSC Research Reports HSC/10/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    10. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    11. Seok-Oh Jeong & Kee-Hoon Kang, 2009. "Nonparametric estimation of value-at-risk," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1225-1238.
    12. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
    13. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    14. Willmot, Gordon E. & Woo, Jae-Kyung, 2022. "Remarks on a generalized inverse Gaussian type integral with applications," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    15. Saralees Nadarajah & Bo Zhang & Stephen Chan, 2014. "Estimation methods for expected shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 271-291, February.
    16. Julien Chevallier & Stéphane Goutte, 2017. "Estimation of Lévy-driven Ornstein–Uhlenbeck processes: application to modeling of $$\hbox {CO}_2$$ CO 2 and fuel-switching," Annals of Operations Research, Springer, vol. 255(1), pages 169-197, August.
    17. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.

  65. M. Benko & M. Fengler & W. Härdle & M. Kopa, 2007. "On extracting information implied in options," Computational Statistics, Springer, vol. 22(4), pages 543-553, December.

    Cited by:

    1. Matthias Fengler, 2010. "Option data and modeling BSM implied volatility," University of St. Gallen Department of Economics working paper series 2010 2010-32, Department of Economics, University of St. Gallen.
    2. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    3. Cristian Homescu, 2011. "Implied Volatility Surface: Construction Methodologies and Characteristics," Papers 1107.1834, arXiv.org.
    4. Zdeněk Drábek & Miloš Kopa & Matúš Maciak & Michal Pešta & Sebastiano Vitali, 2023. "Investment disputes and their explicit role in option market uncertainty and overall risk instability," Computational Management Science, Springer, vol. 20(1), pages 1-25, December.
    5. Tahar Ferhati, 2020. "SVI Model Free Wings," Working Papers hal-02517572, HAL.
    6. Sebastiano Vitali & Miloš Kopa & Gabriele Giana, 2023. "Implied volatility smoothing at COVID-19 times," Computational Management Science, Springer, vol. 20(1), pages 1-42, December.
    7. Martin Tegn'er & Stephen Roberts, 2019. "A Probabilistic Approach to Nonparametric Local Volatility," Papers 1901.06021, arXiv.org, revised Jan 2019.
    8. Arindam Kundu & Sumit Kumar & Nutan Kumar Tomar, 2019. "Option Implied Risk-Neutral Density Estimation: A Robust and Flexible Method," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 705-728, August.
    9. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    10. Miloš Kopa & Sebastiano Vitali & Tomáš Tichý & Radek Hendrych, 2017. "Implied volatility and state price density estimation: arbitrage analysis," Computational Management Science, Springer, vol. 14(4), pages 559-583, October.
    11. Maciak, Matúš, 2021. "Quantile LASSO with changepoints in panel data models applied to option pricing," Econometrics and Statistics, Elsevier, vol. 20(C), pages 166-175.
    12. Fengler, Matthias R. & Hin, Lin-Yee, 2015. "Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints," Journal of Econometrics, Elsevier, vol. 184(2), pages 242-261.
    13. Kim, Namhyoung & Lee, Jaewook, 2013. "No-arbitrage implied volatility functions: Empirical evidence from KOSPI 200 index options," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 36-53.
    14. Judith Glaser & Pascal Heider, 2012. "Arbitrage-free approximation of call price surfaces and input data risk," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 61-73, August.
    15. David Volkmann, 2021. "Explaining S&P500 option returns: an implied risk-adjusted approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 665-685, June.
    16. Tahar Ferhati, 2020. "Robust Calibration For SVI Model Arbitrage Free," Working Papers hal-02490029, HAL.
    17. Maciak, Matúš, 2021. "Quantile LASSO in arbitrage-free option markets," Econometrics and Statistics, Elsevier, vol. 18(C), pages 106-116.

  66. Xia, Yingcun & Härdle, Wolfgang, 2006. "Semi-parametric estimation of partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 97(5), pages 1162-1184, May.

    Cited by:

    1. Wu, Tracy Z. & Yu, Keming & Yu, Yan, 2010. "Single-index quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1607-1621, August.
    2. Lai, Peng & Wang, Qihua, 2014. "Semiparametric efficient estimation for partially linear single-index models with responses missing at random," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 33-50.
    3. Stéphane GREGOIR & Tristan-Pierre MAURY, 2014. "Empowerment Zones And The Housing Market In Paris Inner City," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 40, pages 69-82.
    4. Yehua Li & Marc G. Genton, 2009. "Single‐Index Additive Vector Autoregressive Time Series Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 369-388, September.
    5. Strzalkowska-Kominiak, Ewa & Cao, Ricardo, 2013. "Maximum likelihood estimation for conditional distribution single-index models under censoring," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 74-98.
    6. Lu, Jun & Zhu, Xuehu & Lin, Lu & Zhu, Lixing, 2019. "Estimation for biased partial linear single index models," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 1-13.
    7. Jun Zhang & Yao Yu & Li-Xing Zhu & Hua Liang, 2013. "Partial linear single index models with distortion measurement errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(2), pages 237-267, April.
    8. Michael Wegener & Göran Kauermann, 2017. "Forecasting in nonlinear univariate time series using penalized splines," Statistical Papers, Springer, vol. 58(3), pages 557-576, September.
    9. Zhensheng Huang, 2011. "Statistical estimation in partially linear single-index models with error-prone linear covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 339-350.
    10. Yang, Hu & Yang, Jing, 2014. "A robust and efficient estimation and variable selection method for partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 227-242.
    11. Lai, Peng & Wang, Qihua & Lian, Heng, 2012. "Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 422-432.
    12. Zijuan Chen & Suojin Wang, 2023. "Inferences for extended partially linear single-index models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 602-622, June.
    13. Jiang, Rong & Zhou, Zhan-Gong & Qian, Wei-Min & Chen, Yong, 2013. "Two step composite quantile regression for single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 180-191.
    14. Suli Cheng & Jianbao Chen, 2021. "Estimation of partially linear single-index spatial autoregressive model," Statistical Papers, Springer, vol. 62(1), pages 495-531, February.
    15. Giovanni Forchini & Raoul Theler, 2023. "Semi-parametric modelling of inefficiencies in stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 59(2), pages 135-152, April.
    16. Hilafu, Haileab & Wu, Wenbo, 2017. "Partial projective resampling method for dimension reduction: With applications to partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 1-14.
    17. Jun Zhang & Xia Cui & Heng Peng, 2020. "Estimation and hypothesis test for partial linear single-index multiplicative models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 699-740, June.
    18. Jia Chen & Jiti Gao & Degui Li, 2011. "Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions," Monash Econometrics and Business Statistics Working Papers 12/11, Monash University, Department of Econometrics and Business Statistics.
    19. Lin, Wei & Kulasekera, K.B., 2010. "Testing the equality of linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1156-1167, May.
    20. Lai, Peng & Li, Gaorong & Lian, Heng, 2013. "Quadratic inference functions for partially linear single-index models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 115-127.
    21. Jun Zhang & Nanguang Zhou & Zipeng Sun & Gaorong Li & Zhenghong Wei, 2016. "Statistical inference on restricted partial linear regression models with partial distortion measurement errors," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 304-331, November.
    22. Yi, Grace Y. & He, Wenqing & Liang, Hua, 2009. "Analysis of correlated binary data under partially linear single-index logistic models," Journal of Multivariate Analysis, Elsevier, vol. 100(2), pages 278-290, February.
    23. Huang, Lei & Jiang, Hui & Wang, Huixia, 2019. "A novel partial-linear single-index model for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 110-122.
    24. Shujie Ma & Peter X.-K. Song, 2015. "Varying Index Coefficient Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 341-356, March.
    25. Qingming Zou & Zhongyi Zhu & Jinglong Wang, 2009. "Local influence analysis for penalized Gaussian likelihood estimation in partially linear single-index models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(4), pages 905-918, December.
    26. Claudio Agostinelli & Ana M. Bianco & Graciela Boente, 2020. "Robust estimation in single-index models when the errors have a unimodal density with unknown nuisance parameter," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 855-893, June.
    27. Gueuning, Thomas & Claeskens, Gerda, 2016. "Confidence intervals for high-dimensional partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 13-29.
    28. Ding, Hui & Liu, Yanghui & Xu, Wenchao & Zhang, Riquan, 2017. "A class of functional partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 68-82.
    29. Wang, Xiaoguang & Shi, Xinyong, 2014. "Robust estimation for survival partially linear single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 140-152.
    30. Jun Zhang & Zhenghui Feng & Peirong Xu, 2015. "Estimating the conditional single-index error distribution with a partial linear mean regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 61-83, March.
    31. Grace Yi & Wenqing He & Hua Liang, 2011. "Semiparametric marginal and association regression methods for clustered binary data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(3), pages 511-533, June.
    32. Jiang, Rong & Yu, Keming, 2020. "Single-index composite quantile regression for massive data," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
    33. Huilan Liu & Hu Yang & Changgen Peng, 2019. "Weighted composite quantile regression for single index model with missing covariates at random," Computational Statistics, Springer, vol. 34(4), pages 1711-1740, December.
    34. Zhang, Wenyang & Li, Degui & Xia, Yingcun, 2015. "Estimation in generalised varying-coefficient models with unspecified link functions," Journal of Econometrics, Elsevier, vol. 187(1), pages 238-255.
    35. Jun Zhang, 2021. "Estimation and variable selection for partial linear single-index distortion measurement errors models," Statistical Papers, Springer, vol. 62(2), pages 887-913, April.
    36. Rong Jiang & Wei-Min Qian & Zhan-Gong Zhou, 2016. "Single-index composite quantile regression with heteroscedasticity and general error distributions," Statistical Papers, Springer, vol. 57(1), pages 185-203, March.
    37. Jianglin Fang & Wanrong Liu & Xuewen Lu, 2018. "Empirical likelihood for heteroscedastic partially linear single-index models with growing dimensional data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(3), pages 255-281, April.
    38. Qingming Zou & Zhongyi Zhu, 2014. "M-estimators for single-index model using B-spline," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 225-246, February.
    39. Lexin Li & Liping Zhu & Lixing Zhu, 2011. "Inference on the primary parameter of interest with the aid of dimension reduction estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 59-80, January.
    40. Moral-Arce, Ignacio & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 2011. "Low dimensional semiparametric estimation in a censored regression model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 118-129, January.
    41. Germán Aneiros & Philippe Vieu, 2015. "Partial linear modelling with multi-functional covariates," Computational Statistics, Springer, vol. 30(3), pages 647-671, September.
    42. Jia Chen & Jiti Gao & Degui Li, 2013. "Estimation in Partially Linear Single-Index Panel Data Models With Fixed Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 315-330, July.
    43. Zhenyu Jiang & Chengan Du & Assen Jablensky & Hua Liang & Zudi Lu & Yang Ma & Kok Lay Teo, 2014. "Analysis of Schizophrenia Data Using A Nonlinear Threshold Index Logistic Model," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-11, October.
    44. Liu, Jicai & Xu, Peirong & Lian, Heng, 2019. "Estimation for single-index models via martingale difference divergence," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 271-284.
    45. Xuan Wang & Qihua Wang & Xiao-Hua Zhou, 2015. "Partially varying coefficient single-index additive hazard models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(5), pages 817-841, October.
    46. Jiang, Rong & Qian, Wei-Min & Zhou, Zhan-Gong, 2016. "Weighted composite quantile regression for single-index models," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 34-48.
    47. Lian, Heng & Liang, Hua, 2016. "Separation of linear and index covariates in partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 56-70.
    48. Yazhao Lv & Riquan Zhang & Weihua Zhao & Jicai Liu, 2015. "Quantile regression and variable selection of partial linear single-index model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 375-409, April.
    49. Huang, Zhensheng, 2012. "Efficient inferences on the varying-coefficient single-index model with empirical likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4413-4420.
    50. Kharratzadeh, Milad & Coates, Mark, 2017. "Semi-parametric order-based generalized multivariate regression," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 89-102.
    51. Aldo Goia & Philippe Vieu, 2015. "A partitioned Single Functional Index Model," Computational Statistics, Springer, vol. 30(3), pages 673-692, September.
    52. Yazhao Lv & Riquan Zhang & Weihua Zhao & Jicai Liu, 2014. "Quantile regression and variable selection for the single-index model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1565-1577, July.
    53. Minggen Lu, 2018. "Spline-based quasi-likelihood estimation of mixed Poisson regression with single-index models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(1), pages 1-17, January.
    54. Ma, Shujie & Liang, Hua & Tsai, Chih-Ling, 2014. "Partially linear single index models for repeated measurements," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 354-375.
    55. Huang, Zhensheng & Pang, Zhen, 2012. "Corrected empirical likelihood inference for right-censored partially linear single-index model," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 276-284.
    56. Xu, Mengshan & Otsu, Taisuke, 2020. "Score estimation of monotone partially linear index model," LSE Research Online Documents on Economics 106698, London School of Economics and Political Science, LSE Library.
    57. Huang, Zhensheng & Pang, Zhen & Hu, Tao, 2013. "Testing structural change in partially linear single-index models with error-prone linear covariates," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 121-133.
    58. Zhang, Hong-Fan, 2021. "Iterative GMM for partially linear single-index models with partly endogenous regressors," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    59. Wu, Jingwei & Peng, Hanxiang & Tu, Wanzhu, 2019. "Large-sample estimation and inference in multivariate single-index models," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 382-396.
    60. Graciela Boente & Daniela Rodriguez, 2012. "Robust estimates in generalized partially linear single-index models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 386-411, June.
    61. Xu, Kai & Zhou, Yeqing, 2021. "Projection-averaging-based cumulative covariance and its use in goodness-of-fit testing for single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
    62. Lai, Peng & Wang, Qihua & Zhou, Xiao-Hua, 2014. "Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 241-256.
    63. Wang, Qin & Yao, Weixin, 2012. "An adaptive estimation of MAVE," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 88-100, February.
    64. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    65. Jia Chen & Degui Li & Hua Liang & Suojin Wang, 2014. "Semiparametric GEE Analysis in Partially Linear Single-Index Models for Longitudinal Data," Discussion Papers 14/26, Department of Economics, University of York.
    66. Lu, Xuewen & Cheng, Tsung-Lin, 2007. "Randomly censored partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1895-1922, November.
    67. Li, Gaorong & Zhu, Lixing & Xue, Liugen & Feng, Sanying, 2010. "Empirical likelihood inference in partially linear single-index models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 718-732, March.
    68. Isabel Proença & Horácio Faustino, 2015. "Modelling bilateral intra-industry trade indexes with panel data: a semiparametric approach," Computational Statistics, Springer, vol. 30(3), pages 865-884, September.
    69. Ewa Strzalkowska-Kominiak & Ricardo Cao, 2014. "Beran-based approach for single-index models under censoring," Computational Statistics, Springer, vol. 29(5), pages 1243-1261, October.
    70. Zhiyong Chen & Jianbao Chen, 2022. "Bayesian analysis of partially linear, single-index, spatial autoregressive models," Computational Statistics, Springer, vol. 37(1), pages 327-353, March.
    71. Taisuke Otsu & Mengshan Xu, 2019. "Score estimation of monotone partially linear index model," STICERD - Econometrics Paper Series 603, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    72. Liu, Jicai & Zhang, Riquan & Zhao, Weihua & Lv, Yazhao, 2013. "A robust and efficient estimation method for single index models," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 226-238.
    73. Hamri Mohamed Mehdi & Mekki Sanaà Dounya & Rabhi Abbes & Kadiri Nadia, 2022. "Single Functional Index Quantile Regression for Independent Functional Data Under Right-Censoring," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 26(1), pages 31-62, March.
    74. Chang, Ziqing & Xue, Liugen & Zhu, Lixing, 2010. "On an asymptotically more efficient estimation of the single-index model," Journal of Multivariate Analysis, Elsevier, vol. 101(8), pages 1898-1901, September.
    75. Xue, Liugen & Zhang, Jinghua, 2020. "Empirical likelihood for partially linear single-index models with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    76. Wenqing He & Grace Y. Yi, 2020. "Parametric and semiparametric estimation methods for survival data under a flexible class of models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 369-388, April.
    77. Shaojun Guo & John Leigh Box & Wenyang Zhang, 2017. "A Dynamic Structure for High-Dimensional Covariance Matrices and Its Application in Portfolio Allocation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 235-253, January.
    78. Yixin Fang & Heng Lian & Hua Liang, 2018. "A generalized partially linear framework for variance functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1147-1175, October.
    79. Liu, Yanghui & Li, Yehua & Carroll, Raymond J. & Wang, Naisyin, 2022. "Predictive functional linear models with diverging number of semiparametric single-index interactions," Journal of Econometrics, Elsevier, vol. 230(2), pages 221-239.
    80. Feng, Sanying & Xue, Liugen, 2015. "Model detection and estimation for single-index varying coefficient model," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 227-244.
    81. Huang, Zhensheng & Zhang, Riquan, 2011. "Efficient empirical-likelihood-based inferences for the single-index model," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 937-947, May.
    82. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.

  67. Yatchew, Adonis & Hardle, Wolfgang, 2006. "Nonparametric state price density estimation using constrained least squares and the bootstrap," Journal of Econometrics, Elsevier, vol. 133(2), pages 579-599, August.

    Cited by:

    1. Ricardo Crisóstomo, 2021. "Estimating real word probabilities: a forward-looking behavioral framework," CNMV Working Papers CNMV Working Papers no. 7, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    2. Gollier, Christian, 2009. "Portfolio Choices and Asset Prices: The Comparative Statics of Ambiguity Aversion," TSE Working Papers 09-068, Toulouse School of Economics (TSE).
    3. Jarrow, Robert A. & Kwok, Simon S., 2020. "Inferring Financial Bubbles from Option Data," Working Papers 2020-04, University of Sydney, School of Economics, revised Jun 2021.
    4. Gao, Zhikun & Tang, Yanlin & Wang, Huixia Judy & Wu, Guangying K. & Lin, Jeff, 2020. "Automatic identification of curve shapes with applications to ultrasonic vocalization," Computational Statistics & Data Analysis, Elsevier, vol. 148(C).
    5. Polkovnichenko, Valery & Zhao, Feng, 2013. "Probability weighting functions implied in options prices," Journal of Financial Economics, Elsevier, vol. 107(3), pages 580-609.
    6. Bo Zhao & Stewart Hodges, 2013. "Parametric modeling of implied smile functions: a generalized SVI model," Review of Derivatives Research, Springer, vol. 16(1), pages 53-77, April.
    7. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    8. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    9. Ana M. Monteiro & Antonio A. F. Santos, 2020. "Conditional risk-neutral density from option prices by local polynomial kernel smoothing with no-arbitrage constraints," Review of Derivatives Research, Springer, vol. 23(1), pages 41-61, April.
    10. Ana M. Monteiro & António A. F. Santos, 2022. "Option prices for risk‐neutral density estimation using nonparametric methods through big data and large‐scale problems," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 152-171, January.
    11. Shively, Thomas S. & Walker, Stephen G. & Damien, Paul, 2011. "Nonparametric function estimation subject to monotonicity, convexity and other shape constraints," Journal of Econometrics, Elsevier, vol. 161(2), pages 166-181, April.
    12. Omid M. Ardakani, 2022. "Option pricing with maximum entropy densities: The inclusion of higher‐order moments," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1821-1836, October.
    13. Zdenek Hlavka & Michal Pesta, 2006. "Constrained General Regression in Pseudo-Sobolev Spaces with Application to Option Pricing," SFB 649 Discussion Papers SFB649DP2006-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Gianluca Cassese, 2019. "Nonparametric Estimates Of Option Prices And Related Quantities," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(07), pages 1-29, November.
    15. Härdle, Wolfgang & Hlávka, Zdenek, 2009. "Dynamics of state price densities," Journal of Econometrics, Elsevier, vol. 150(1), pages 1-15, May.
    16. Arindam Kundu & Sumit Kumar & Nutan Kumar Tomar, 2019. "Option Implied Risk-Neutral Density Estimation: A Robust and Flexible Method," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 705-728, August.
    17. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    18. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.
    19. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    20. Xixuan Han & Boyu Wei & Hailiang Yang, 2018. "Index Options And Volatility Derivatives In A Gaussian Random Field Risk-Neutral Density Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-41, June.
    21. Matthias R. Fengler, 2005. "Arbitrage-Free Smoothing of the Implied Volatility Surface," SFB 649 Discussion Papers SFB649DP2005-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Fengler, Matthias R. & Hin, Lin-Yee, 2015. "Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints," Journal of Econometrics, Elsevier, vol. 184(2), pages 242-261.
    23. Thorsten Lehnert & Gildas Blanchard & Dennis Bams, 2014. "Evaluating Option Pricing Model Performance Using Model Uncertainty," LSF Research Working Paper Series 14-06, Luxembourg School of Finance, University of Luxembourg.
    24. Lu, Junwen & Qu, Zhongjun, 2021. "Sieve estimation of option-implied state price density," Journal of Econometrics, Elsevier, vol. 224(1), pages 88-112.
    25. Wolfgang Härdle & Zdenek Hlavka, 2005. "Dynamics of State Price Densities," SFB 649 Discussion Papers SFB649DP2005-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Birke, Melanie & Pilz, Kay F., 2007. "Nonparametric option pricing with no-arbitrage constraints," Technical Reports 2007,30, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    27. Thomas Mazzoni, 2018. "Asymptotic Expansion of Risk-Neutral Pricing Density," IJFS, MDPI, vol. 6(1), pages 1-26, March.
    28. Hwang, Eunju & Shin, Dong Wan, 2012. "Stationary bootstrap for kernel density estimators under ψ-weak dependence," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1581-1593.

  68. Wolfgang K. Härdle & Rouslan A. Moro & Dorothea Schäfer, 2004. "Support Vector Machines: eine neue Methode zum Rating von Unternehmen," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 71(49), pages 759-765.

    Cited by:

    1. Laura Auria & Rouslan A. Moro, 2008. "Support Vector Machines (SVM) as a Technique for Solvency Analysis," Discussion Papers of DIW Berlin 811, DIW Berlin, German Institute for Economic Research.

  69. Wang Q. & Linton O. & Hardle W., 2004. "Semiparametric Regression Analysis With Missing Response at Random," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 334-345, January.

    Cited by:

    1. Wangli Xu & Xu Guo, 2013. "Nonparametric checks for varying coefficient models with missing response at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(4), pages 459-482, May.
    2. Lai, Peng & Wang, Qihua, 2014. "Semiparametric efficient estimation for partially linear single-index models with responses missing at random," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 33-50.
    3. Zhong, Ping-Shou & Chen, Sixia, 2014. "Jackknife empirical likelihood inference with regression imputation and survey data," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 193-205.
    4. Ash Abebe & Huybrechts F. Bindele & Masego Otlaadisa & Boikanyo Makubate, 2021. "Robust estimation of single index models with responses missing at random," Statistical Papers, Springer, vol. 62(5), pages 2195-2225, October.
    5. Sun, Zhihua & Wang, Qihua & Dai, Pengjie, 2009. "Model checking for partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 636-651, April.
    6. Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
    7. Bianco, Ana & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2010. "Estimation of the marginal location under a partially linear model with missing responses," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 546-564, February.
    8. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassified data and an application to labour market transitions," ZEW Discussion Papers 15-043, ZEW - Leibniz Centre for European Economic Research.
    9. Tang, Niansheng & Xia, Linli & Yan, Xiaodong, 2019. "Feature screening in ultrahigh-dimensional partially linear models with missing responses at random," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 208-227.
    10. Chen, Songxi, 2012. "Estimation in semiparametric models with missing data," MPRA Paper 46216, University Library of Munich, Germany.
    11. Wangli Xu & Xu Guo & Lixing Zhu, 2012. "Goodness-of-fitting for partial linear model with missing response at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 103-118.
    12. Nengxiang Ling & Rui Kan & Philippe Vieu & Shuyu Meng, 2019. "Semi-functional partially linear regression model with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(1), pages 39-70, January.
    13. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Wang, Qihua & Sun, Zhihua, 2007. "Estimation in partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1470-1493, August.
    15. Chen, Xiaohong & Hong, Han & Tarozzi, Alessandro, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Working Papers 42, Yale University, Department of Economics.
    16. M. Hristache & V. Patilea, 2017. "Conditional moment models with data missing at random," Biometrika, Biometrika Trust, vol. 104(3), pages 735-742.
    17. Inkmann, J., 2005. "Inverse Probability Weighted Generalised Empirical Likelihood Estimators : Firm Size and R&D Revisited," Discussion Paper 2005-131, Tilburg University, Center for Economic Research.
    18. Wang, Zhaoliang & Xue, Liugen & Liu, Juanfang, 2019. "Checking nonparametric component for partially nonlinear model with missing response," Statistics & Probability Letters, Elsevier, vol. 149(C), pages 1-8.
    19. Liang, Hua & Su, Haiyan & Zou, Guohua, 2008. "Confidence intervals for a common mean with missing data with applications in an AIDS study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 546-553, December.
    20. Yongsong Qin & Jianjun Li, 2011. "Empirical likelihood for partially linear models with missing responses at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 497-511.
    21. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    22. Xue, Liugen & Xue, Dong, 2011. "Empirical likelihood for semiparametric regression model with missing response data," Journal of Multivariate Analysis, Elsevier, vol. 102(4), pages 723-740, April.
    23. Lai, Peng & Liu, Yiming & Liu, Zhi & Wan, Yi, 2017. "Model free feature screening for ultrahigh dimensional data with responses missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 201-216.
    24. Bindele, Huybrechts F., 2018. "Covariates missing at random under signed-rank inference," Econometrics and Statistics, Elsevier, vol. 8(C), pages 78-93.
    25. Qihua Wang & Tao Zhang & Wolfgang Karl Härdle, 2014. "An Extended Single Index Model with Missing Response at Random," SFB 649 Discussion Papers SFB649DP2014-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    26. Levon Demirdjian & Majid Mojirsheibani, 2019. "Kernel classification with missing data and the choice of smoothing parameters," Statistical Papers, Springer, vol. 60(5), pages 1487-1513, October.
    27. Xuewen Lu & Heng Lian & Wanrong Liu, 2012. "Semiparametric estimation for inverse density weighted expectations when responses are missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 139-152.
    28. Peixin Zhao & Xinrong Tang, 2016. "Imputation based statistical inference for partially linear quantile regression models with missing responses," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(8), pages 991-1009, November.
    29. Yan-Ting Xiao & Fu-Xiao Li, 2020. "Estimation in partially linear varying-coefficient errors-in-variables models with missing response variables," Computational Statistics, Springer, vol. 35(4), pages 1637-1658, December.
    30. Chen, Song Xi & Van Keilegom, Ingrid, 2013. "Estimation in semiparametric models with missing data," LIDAM Reprints ISBA 2013024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    31. Francesco Bravo & David Jacho-Chavez, 2011. "Empirical Likelihood for Efficient Semiparametric Average Treatment Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 1-24.
    32. Zhao, Hui & Zhao, Pu-Ying & Tang, Nian-Sheng, 2013. "Empirical likelihood inference for mean functionals with nonignorably missing response data," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 101-116.
    33. Francesco Bravo, 2013. "Partially linear varying coefficient models with missing at random responses," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 721-762, August.
    34. Xiaohui Liu & Zhizhong Wang & Xuemei Hu, 2011. "Testing heteroscedasticity in partially linear models with missing covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 321-337.
    35. Mariela Sued & Marina Valdora & Víctor Yohai, 2020. "Robust doubly protected estimators for quantiles with missing data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 819-843, September.
    36. Wangli Xu & Lixing Zhu, 2013. "Testing the adequacy of varying coefficient models with missing responses at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(1), pages 53-69, January.
    37. Lu Li & Niwen Zhou & Lixing Zhu, 2022. "Outcome regression-based estimation of conditional average treatment effect," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 987-1041, October.
    38. Bianco, Ana M. & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2015. "Robust inference in partially linear models with missing responses," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 88-98.
    39. Nian-Sheng Tang & Pu-Ying Zhao, 2013. "Empirical likelihood semiparametric nonlinear regression analysis for longitudinal data with responses missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 639-665, August.
    40. Yu-Ye Zou & Han-Ying Liang & Jing-Jing Zhang, 2015. "Nonlinear wavelet density estimation with data missing at random when covariates are present," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(8), pages 967-995, November.
    41. Ana M. Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2019. "Plug-in marginal estimation under a general regression model with missing responses and covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 106-146, March.
    42. Wang, Qihua & Su, Miaomiao & Wang, Ruoyu, 2021. "A beyond multiple robust approach for missing response problem," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    43. Bindele, Huybrechts F. & Nguelifack, Brice M., 2019. "Generalized signed-rank estimation for regression models with non-ignorable missing responses," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 14-33.
    44. Bindele, Huybrechts F. & Abebe, Ash, 2015. "Semi-parametric rank regression with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 117-132.
    45. Guo, Xu & Fang, Yun & Zhu, Xuehu & Xu, Wangli & Zhu, Lixing, 2018. "Semiparametric double robust and efficient estimation for mean functionals with response missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 325-339.
    46. Weiwei Zhang & Jingxuan Luo & Shengyun Ma, 2023. "Estimation in Semi-Varying Coefficient Heteroscedastic Instrumental Variable Models with Missing Responses," Mathematics, MDPI, vol. 11(23), pages 1-20, December.
    47. Qihua Wang & Gregg Dinse & Chunling Liu, 2012. "Hazard function estimation with cause-of-death data missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 415-438, April.
    48. Nengxiang Ling & Lilei Cheng & Philippe Vieu & Hui Ding, 2022. "Missing responses at random in functional single index model for time series data," Statistical Papers, Springer, vol. 63(2), pages 665-692, April.
    49. Ana Bianco & Graciela Boente & Wenceslao González-Manteiga & Ana Pérez-González, 2011. "Asymptotic behavior of robust estimators in partially linear models with missing responses: the effect of estimating the missing probability on the simplified marginal estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 524-548, November.
    50. Xue, Liugen & Zhang, Jinghua, 2020. "Empirical likelihood for partially linear single-index models with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    51. Shuanghua Luo & Changlin Mei & Cheng-yi Zhang, 2017. "Smoothed empirical likelihood for quantile regression models with response data missing at random," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(1), pages 95-116, January.
    52. Mojirsheibani, Majid & Montazeri, Zahra, 2007. "On nonparametric classification with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1051-1071, May.
    53. Yu Shen & Han-Ying Liang, 2018. "Quantile regression and its empirical likelihood with missing response at random," Statistical Papers, Springer, vol. 59(2), pages 685-707, June.
    54. Zhangong Zhou & Linjun Tang, 2019. "Testing for parametric component of partially linear models with missing covariates," Statistical Papers, Springer, vol. 60(3), pages 747-760, June.
    55. A. Pérez-González & J. Vilar-Fernández & W. González-Manteiga, 2009. "Asymptotic properties of local polynomial regression with missing data and correlated errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 85-109, March.
    56. Guo, Xu & Wang, Tao & Xu, Wangli & Zhu, Lixing, 2014. "Dimension reduction with missing response at random," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 228-242.
    57. Bryan S. Graham & Cristine Campos De Xavier Pinto & Daniel Egel, 2012. "Inverse Probability Tilting for Moment Condition Models with Missing Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 1053-1079.
    58. Tianfa Xie & Zhihua Sun & Liuquan Sun, 2012. "A consistent model specification test for a partial linear model with covariates missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 841-856, December.
    59. Hu, Yanan & Yang, Yaqi & Wang, Chunyu & Tian, Maozai, 2017. "Imputation in nonparametric quantile regression with complex data," Statistics & Probability Letters, Elsevier, vol. 127(C), pages 120-130.
    60. Shuanghua Luo & Cheng-yi Zhang, 2016. "Nonparametric $$M$$ M -type regression estimation under missing response data," Statistical Papers, Springer, vol. 57(3), pages 641-664, September.
    61. Qi-Hua Wang, 2009. "Statistical estimation in partial linear models with covariate data missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 47-84, March.

  70. Matthias Fengler & Wolfgang Härdle & Christophe Villa, 2003. "The Dynamics of Implied Volatilities: A Common Principal Components Approach," Review of Derivatives Research, Springer, vol. 6(3), pages 179-202, October.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. He, Xin-Jiang & Zhu, Song-Ping, 2017. "How should a local regime-switching model be calibrated?," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 149-163.
    3. Vedant Choudhary & Sebastian Jaimungal & Maxime Bergeron, 2023. "FuNVol: A Multi-Asset Implied Volatility Market Simulator using Functional Principal Components and Neural SDEs," Papers 2303.00859, arXiv.org, revised Dec 2023.
    4. Laurini, Márcio P., 2007. "Imposing No-Arbitrage Conditions In Implied Volatility Surfaces Using Constrained Smoothing Splines," Insper Working Papers wpe_89, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Beer, Simone & Braun, Alexander, 2022. "Market-consistent valuation of natural catastrophe risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
    6. Kun Li & Joseph D. Cursio & Yunchuan Sun, 2018. "Principal Component Analysis of Price Fluctuation in the Smart Grid Electricity Market," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    7. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    8. Tanha, Hassan & Dempsey, Michael, 2016. "The evolving dynamics of the Australian SPI 200 implied volatility surface," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 44-57.
    9. Michal Benko & Wolfgang Härdle & Alois Kneip, 2006. "Common Functional Principal Components," SFB 649 Discussion Papers SFB649DP2006-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    11. Krylova, Elizaveta & Nikkinen, Jussi & Vähämaa, Sami, 2009. "Cross-dynamics of volatility term structures implied by foreign exchange options," Journal of Economics and Business, Elsevier, vol. 61(5), pages 355-375, September.
    12. Ralf Brüggemann & Wolfgang Härdle & Julius Mungo & Carsten Trenkler, 2006. "VAR Modeling for Dynamic Semiparametric Factors of Volatility Strings," SFB 649 Discussion Papers SFB649DP2006-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Martin Magris & Perttu Barholm & Juho Kanniainen, 2017. "Implied volatility smile dynamics in the presence of jumps," Papers 1711.02925, arXiv.org, revised May 2020.
    14. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2019. "VCRIX - a volatility index for crypto-currencies," IRTG 1792 Discussion Papers 2019-027, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    15. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
    16. Fengler, Matthias R. & Wang, Qihua, 2003. "Fitting the Smile Revisited: A Least Squares Kernel Estimator for the Implied Volatility Surface," SFB 373 Discussion Papers 2003,25, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    17. Michal Benko & Alois Kneip, 2005. "Common functional component modelling," SFB 649 Discussion Papers SFB649DP2005-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Xiu Xu & Wolfgang K. Härdle & Cathy Yi-Hsuan Chen, 2016. "Dynamic credit default swaps curves in a network topology," SFB 649 Discussion Papers SFB649DP2016-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Chantziara, Thalia & Skiadopoulos, George, 2008. "Can the dynamics of the term structure of petroleum futures be forecasted? Evidence from major markets," Energy Economics, Elsevier, vol. 30(3), pages 962-985, May.
    20. Chen, Si & Zhou, Zhen & Li, Shenghong, 2016. "An efficient estimate and forecast of the implied volatility surface: A nonlinear Kalman filter approach," Economic Modelling, Elsevier, vol. 58(C), pages 655-664.
    21. Bernd Engelmann & Matthias Fengler & Morten Nalholm & Peter Schwendner, 2006. "Static versus dynamic hedges: an empirical comparison for barrier options," Review of Derivatives Research, Springer, vol. 9(3), pages 239-264, November.
    22. Sebastiano Vitali & Miloš Kopa & Gabriele Giana, 2023. "Implied volatility smoothing at COVID-19 times," Computational Management Science, Springer, vol. 20(1), pages 1-42, December.
    23. Panigirtzoglou, Nikolaos & Skiadopoulos, George, 2004. "A new approach to modeling the dynamics of implied distributions: Theory and evidence from the S&P 500 options," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1499-1520, July.
    24. Francesco Audrino & Dominik Colangelo, 2009. "Option trading strategies based on semi-parametric implied volatility surface prediction," University of St. Gallen Department of Economics working paper series 2009 2009-24, Department of Economics, University of St. Gallen.
    25. T. F. Coleman & Y. Kim & Y. Li & M. Patron, 2007. "Robustly Hedging Variable Annuities With Guarantees Under Jump and Volatility Risks," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 74(2), pages 347-376, June.
    26. Pavel Cizek & Karel Komorad, 2005. "Implied Trinomial Trees," SFB 649 Discussion Papers SFB649DP2005-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    27. Matthias Fengler & Wolfgang Härdle & Enno Mammen, 2005. "A Dynamic Semiparametric Factor Model for Implied Volatility String Dynamics," SFB 649 Discussion Papers SFB649DP2005-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    29. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    30. Barletta, Andrea & Santucci de Magistris, Paolo & Sloth, David, 2019. "It only takes a few moments to hedge options," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 251-269.
    31. Miloš Kopa & Sebastiano Vitali & Tomáš Tichý & Radek Hendrych, 2017. "Implied volatility and state price density estimation: arbitrage analysis," Computational Management Science, Springer, vol. 14(4), pages 559-583, October.
    32. Wenyong Zhang & Lingfei Li & Gongqiu Zhang, 2021. "A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface," Papers 2106.07177, arXiv.org, revised Jan 2022.
    33. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
    34. Han Lin Shang, 2011. "A survey of functional principal component analysis," Monash Econometrics and Business Statistics Working Papers 6/11, Monash University, Department of Econometrics and Business Statistics.
    35. Carol Alexander & Leonardo M. Nogueira, 2004. "Hedging with Stochastic and Local Volatility," ICMA Centre Discussion Papers in Finance icma-dp2004-10, Henley Business School, University of Reading, revised Dec 2004.
    36. Da Fonseca, José & Gottschalk, Katrin, 2014. "Cross-hedging strategies between CDS spreads and option volatility during crises," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 386-400.
    37. Gang Li & Chu Zhang, 2010. "On the Number of State Variables in Options Pricing," Management Science, INFORMS, vol. 56(11), pages 2058-2075, November.
    38. Bali, Juan Lucas & Boente, Graciela, 2017. "Robust estimators under a functional common principal components model," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 424-440.
    39. Massimo Guidolin & Kai Wang, 2022. "The Empirical Performance of Option Implied Volatility Surface-Driven Optimal Portfolios," BAFFI CAREFIN Working Papers 22190, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    40. Mónica Fuentes & Sergio Godoy, 2005. "Sovereign Spread in Emerging Markets: A Principal Component Analysis," Working Papers Central Bank of Chile 333, Central Bank of Chile.
    41. Yueh-Neng Lin & Shih-Kuo Yeh & Shih-Ching Chuan & Steven J. Jordan, 2008. "The link between intraday signals and call warrant mispricing," The Service Industries Journal, Taylor & Francis Journals, vol. 30(13), pages 2273-2288, November.
    42. Itkin, Andrey, 2015. "To sigmoid-based functional description of the volatility smile," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 264-291.
    43. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    44. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    45. Wallmeier, Martin, 2012. "Smile in Motion: An Intraday Analysis of Asymmetric Implied Volatility," FSES Working Papers 427, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

  71. Wolfgang Härdle & Joel Horowitz & Jens‐Peter Kreiss, 2003. "Bootstrap Methods for Time Series," International Statistical Review, International Statistical Institute, vol. 71(2), pages 435-459, August.

    Cited by:

    1. Maricela Cruz & Hernando Ombao & Daniel L. Gillen, 2022. "A Generalized Interrupted Time Series Model for Assessing Complex Health Care Interventions," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(3), pages 582-610, December.
    2. Thomas George & Chuan-Yang Hwang & Tavy Ronen, 2010. "Bootstrap refinements in tests of microstructure frictions," Review of Quantitative Finance and Accounting, Springer, vol. 35(1), pages 47-70, July.
    3. Buchmueller, Thomas C. & Jacobson, Mireille & Wold, Cheryl, 2006. "How far to the hospital?: The effect of hospital closures on access to care," Journal of Health Economics, Elsevier, vol. 25(4), pages 740-761, July.
    4. Finn E. Kydland & Peter Rupert & Roman Sustek, 2012. "Housing Dynamics over the Business Cycle," NBER Working Papers 18432, National Bureau of Economic Research, Inc.
    5. A. Talha Yalta, 2013. "Small Sample Bootstrap Inference of Level Relationships in the Presence of Autocorrelated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Working Papers 1301, TOBB University of Economics and Technology, Department of Economics.
    6. Palm, F.C. & Smeekes, S. & Urbain, J.R.Y.J., 2008. "Cross-sectional dependence robust block bootstrap panel unit root tests," Research Memorandum 048, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    7. Nawaz, Nasreen, 2017. "Robust Inference by Sub-sampling," MPRA Paper 116721, University Library of Munich, Germany, revised 08 Jun 2019.
    8. Juan A. Montecino & Gerald Epstein, 2014. "Intra-Financial Lending, Credit, and Capital Formation," Working Papers Series 21, Institute for New Economic Thinking.
    9. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    10. Miquel Oliu-Barton & Bary S R Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B Wolff, 2022. "The Effect of COVID Certificates on Vaccine Uptake, Health Outcomes, and the Economy," Post-Print hal-03813557, HAL.
    11. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    12. Robert L. Bray & Decio Coviello & Andrea Ichino & Nicola Persico, 2016. "Multitasking, Multiarmed Bandits, and the Italian Judiciary," Manufacturing & Service Operations Management, INFORMS, vol. 18(4), pages 545-558, October.
    13. Basha, Shabeen Afsar & Bennasr, Hamdi & Goaied, Mohamed, 2023. "Financial literacy, financial development, and leverage of small firms," International Review of Financial Analysis, Elsevier, vol. 86(C).
    14. D’Amato, Valeria & Haberman, Steven & Piscopo, Gabriella & Russolillo, Maria, 2012. "Modelling dependent data for longevity projections," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 694-701.
    15. Escanciano, J. Carlos, 2006. "Goodness-of-Fit Tests for Linear and Nonlinear Time Series Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 531-541, June.
    16. Robert L. Bray & Haim Mendelson, 2015. "Production Smoothing and the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 208-220, May.
    17. Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
    18. Westerlund, J. & Smeekes, S., 2013. "Robust block bootstrap panel predictability tests," Research Memorandum 060, Maastricht University, Graduate School of Business and Economics (GSBE).
    19. P. B. Zondi & Z. Robinson, 2021. "The Relationship between Government Debt and Economic Growth in South Africa with Specific Reference to Eskom," EuroEconomica, Danubius University of Galati, issue 2(40), pages 17-34, November.
    20. Chatenet, Q. & Remy, E. & Gagnon, M. & Fouladirad, M. & Tahan, A.S., 2021. "Modeling cavitation erosion using non-homogeneous gamma process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    21. A. Talha Yalta, 2016. "Bootstrap Inference of Level Relationships in the Presence of Serially Correlated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 339-366, August.
    22. Li, Y. & Donkers, A.C.D. & Melenberg, B., 2006. "The Non- and Semiparametric Analysis of MS Models : Some Applications," Discussion Paper 2006-95, Tilburg University, Center for Economic Research.
    23. Li, Jing, 2006. "The block bootstrap test of Hausman's exogeneity in the presence of serial correlation," Economics Letters, Elsevier, vol. 91(1), pages 76-82, April.
    24. Tae-Hwy Lee & Yundong Tu & Aman Ullah, 2015. "Forecasting Equity Premium: Global Historical Average Versus Local Historical Average and Constraints," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 393-402, July.
    25. Lee, Tae-Hwy & Tu, Yundong & Ullah, Aman, 2014. "Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 196-210.
    26. Calatayud, Julia & Jornet, Marc & Mateu, Jorge & Pinto, Carla M.A., 2023. "A new population model for urban infestations," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    27. Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
    28. Skripnikov, A. & Michailidis, G., 2019. "Regularized joint estimation of related vector autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 164-177.
    29. J. Vilar-Fernández & J. Vilar-Fernández & W. González-Manteiga, 2007. "Bootstrap tests for nonparametric comparison of regression curves with dependent errors," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 123-144, May.
    30. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    31. Palczewski, Andrzej & Palczewski, Jan, 2014. "Theoretical and empirical estimates of mean–variance portfolio sensitivity," European Journal of Operational Research, Elsevier, vol. 234(2), pages 402-410.
    32. James G. MacKinnon, 2006. "Bootstrap Methods In Econometrics," Working Paper 1028, Economics Department, Queen's University.
    33. Finn E. Kydland & Peter Rupert & Roman Šustek, 2016. "Housing Dynamics Over The Business Cycle," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(4), pages 1149-1177, November.
    34. James G. MacKinnon, 2007. "Bootstrap Hypothesis Testing," Working Paper 1127, Economics Department, Queen's University.
    35. S. Yaser Samadi & Tharindu P. De Alwis, 2023. "Fourier Methods for Sufficient Dimension Reduction in Time Series," Papers 2312.02110, arXiv.org.
    36. David Atance & Ana Debón & Eliseo Navarro, 2020. "A Comparison of Forecasting Mortality Models Using Resampling Methods," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    37. Chavleishvili, Sulkhan & Kremer, Manfred & Lund-Thomsen, Frederik, 2023. "Quantifying financial stability trade-offs for monetary policy: a quantile VAR approach," Working Paper Series 2833, European Central Bank.
    38. Nan Lu, 2018. "La modélisation de l’indice CAC 40 avec un modèle basé agent," Erudite Ph.D Dissertations, Erudite, number ph18-02 edited by François Legendre, December.
    39. Jentsch, Carsten & Kreiss, Jens-Peter, 2010. "The multiple hybrid bootstrap -- Resampling multivariate linear processes," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2320-2345, November.
    40. Rodrigo Mariscal & Andrew Powell, 2012. "Forecasting Inflation Risks in Latin America: A Technical Note," Research Department Publications 4785, Inter-American Development Bank, Research Department.
    41. van Baal, Pieter H. & Wong, Albert, 2012. "Time to death and the forecasting of macro-level health care expenditures: Some further considerations," Journal of Health Economics, Elsevier, vol. 31(6), pages 876-887.
    42. Paulo M.M. Rodrigues & Gabriel Zsurkis, 2020. "The expected time to cross a threshold and its determinants: A simple and flexible framework," Working Papers w202006, Banco de Portugal, Economics and Research Department.
    43. Kosowski, Robert & Naik, Narayan Y. & Teo, Melvyn, 2007. "Do hedge funds deliver alpha? A Bayesian and bootstrap analysis," Journal of Financial Economics, Elsevier, vol. 84(1), pages 229-264, April.
    44. Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  72. Delecroix, Michel & Härdle, Wolfgang & Hristache, Marian, 2003. "Efficient estimation in conditional single-index regression," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 213-226, August.

    Cited by:

    1. Jianhong Shi & Qian Yang & Xiongya Li & Weixing Song, 2017. "Effects of measurement error on a class of single-index varying coefficient regression models," Computational Statistics, Springer, vol. 32(3), pages 977-1001, September.
    2. Minggen Lu & Dana Loomis, 2013. "Spline-based semiparametric estimation of partially linear Poisson regression with single-index models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(4), pages 905-922, December.
    3. Bucher, Axel & El Ghouch, Anouar & Van Keilegom, Ingrid, 2014. "Single-index quantile regression models for censored data," LIDAM Discussion Papers ISBA 2014001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Huybrechts F. Bindele & Ash Abebe & Karlene N. Meyer, 2018. "General rank-based estimation for regression single index models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1115-1146, October.
    5. Ming-Yueh Huang & Chin-Tsang Chiang, 2017. "Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear-Index," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(2), pages 396-424, June.
    6. Yin, Xiangrong & Li, Bing & Cook, R. Dennis, 2008. "Successive direction extraction for estimating the central subspace in a multiple-index regression," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1733-1757, September.
    7. Strzalkowska-Kominiak, Ewa & Cao, Ricardo, 2013. "Maximum likelihood estimation for conditional distribution single-index models under censoring," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 74-98.
    8. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    9. Donkers, Bas & Schafgans, Marcia M. A., 2005. "A method of moments estimator for semiparametric index models," LSE Research Online Documents on Economics 6815, London School of Economics and Political Science, LSE Library.
    10. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
    11. Lai, Peng & Wang, Qihua & Lian, Heng, 2012. "Bias-corrected GEE estimation and smooth-threshold GEE variable selection for single-index models with clustered data," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 422-432.
    12. Weiyu Li & Valentin Patilea, 2018. "A dimension reduction approach for conditional Kaplan–Meier estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 295-315, June.
    13. Li, Weiyu & Patilea, Valentin, 2017. "A new minimum contrast approach for inference in single-index models," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 47-59.
    14. Juan Carlos Escanciano & Kyungchul Song, 2007. "Asymptotically Optimal Tests for Single-Index Restrictions with a Focus on Average Partial Effects," PIER Working Paper Archive 07-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    15. Catalina Bolancé & Ricardo Cao & Montserrat Guillen, 2018. "“Flexible maximum conditional likelihood estimation for single-index models to predict accident severity with telematics data”," IREA Working Papers 201829, University of Barcelona, Research Institute of Applied Economics, revised Dec 2018.
    16. Jianqing Fan & Yongyi Guo & Mengxin Yu, 2021. "Policy Optimization Using Semi-parametric Models for Dynamic Pricing," Papers 2109.06368, arXiv.org, revised May 2022.
    17. Kadiri Nadia & Rabhi Abbes & Bouchentouf Amina Angelika, 2018. "Strong uniform consistency rates of conditional quantile estimation in the single functional index model under random censorship," Dependence Modeling, De Gruyter, vol. 6(1), pages 197-227, November.
    18. Chiang, Chin-Tsang & Huang, Ming-Yueh, 2012. "New estimation and inference procedures for a single-index conditional distribution model," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 271-285.
    19. Zhou, Xiao-Hua & Liang, Hua, 2006. "Semi-parametric single-index two-part regression models," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1378-1390, March.
    20. Escanciano, Juan Carlos & Song, Kyungchul, 2010. "Testing single-index restrictions with a focus on average derivatives," Journal of Econometrics, Elsevier, vol. 156(2), pages 377-391, June.
    21. Chen, Tao & Parker, Thomas, 2014. "Semiparametric efficiency for partially linear single-index regression models," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 376-386.
    22. Andrés Alonso & Ana Sipols & Silvia Quintas, 2013. "A single-index model procedure for interpolation intervals in time series," Computational Statistics, Springer, vol. 28(4), pages 1463-1484, August.
    23. Chin-Shang Li & Minggen Lu, 2018. "A lack-of-fit test for generalized linear models via single-index techniques," Computational Statistics, Springer, vol. 33(2), pages 731-756, June.
    24. Ming-Yueh Huang & Chin-Tsang Chiang, 2017. "An Effective Semiparametric Estimation Approach for the Sufficient Dimension Reduction Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1296-1310, July.
    25. Akkal Fatima & Kadiri Nadia & Rabhi Abbes, 2021. "Asymptotic Normality of Conditional Density and Conditional Mode in the Functional Single Index Model," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(1), pages 1-24, March.
    26. Graciela Boente & Daniela Rodriguez, 2012. "Robust estimates in generalized partially linear single-index models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 386-411, June.
    27. Attaoui, Said & Laksaci, Ali & Ould Said, Elias, 2011. "A note on the conditional density estimate in the single functional index model," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 45-53, January.
    28. Ai, Chunrong & You, Jinhong & Zhou, Yong, 2011. "Statistical inference using a weighted difference-based series approach for partially linear regression models," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 601-618, March.
    29. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    30. Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal, 2020. "Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height," International Journal of Forecasting, Elsevier, vol. 36(2), pages 515-530.
    31. Said Attaoui, 2014. "Strong uniform consistency rates and asymptotic normality of conditional density estimator in the single functional index modeling for time series data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(3), pages 257-286, July.
    32. Haibo Zhou & Jinhong You & Bin Zhou, 2010. "Statistical inference for fixed-effects partially linear regression models with errors in variables," Statistical Papers, Springer, vol. 51(3), pages 629-650, September.

  73. Hardle W. & Sperlich S. & Spokoiny V., 2001. "Structural Tests in Additive Regression," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1333-1347, December.

    Cited by:

    1. Donkers, Bas & Schafgans, Marcia M. A., 2005. "A method of moments estimator for semiparametric index models," LSE Research Online Documents on Economics 6815, London School of Economics and Political Science, LSE Library.
    2. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    3. Yousefi, Shahriar & Weinreich, Ilona & Reinarz, Dominik, 2005. "Wavelet-based prediction of oil prices," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 265-275.
    4. Manuel Wiesenfarth & Tatyana Krivobokova & Stephan Klasen & Stefan Sperlich, 2012. "Direct Simultaneous Inference in Additive Models and Its Application to Model Undernutrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1286-1296, December.
    5. Rui Li & Yuanyuan Zhang, 2021. "Two-stage estimation and simultaneous confidence band in partially nonlinear additive model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(8), pages 1109-1140, November.
    6. Stefan Sperlich, 2013. "Comments on: An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 419-427, September.
    7. Felix Abramovich & Italia Feis & Theofanis Sapatinas, 2009. "Optimal testing for additivity in multiple nonparametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 691-714, September.
    8. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  74. Wolfgang Härdle & Torsten Kleinow & Rolf Tschernig, 2001. "Web Quantlets for Time Series Analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 179-188, March.

    Cited by:

    1. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Neuwirth, E., 2003. "Computational Statistics with Spreadsheets Towards Efficiency, Reproducibility and Security," SFB 373 Discussion Papers 2003,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Kleinow, Torsten & Lehmann, Heiko, 2002. "Client/server based statistical computing," SFB 373 Discussion Papers 2002,49, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Rönz, Bernd, 2001. "MM*Stat - a multimedia tool for teaching of statistics," SFB 373 Discussion Papers 2001,85, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Härdle, Wolfgang & Lehmann, Heiko & Rönz, Bernd, 2001. "MM*STAT: Eine interaktive Einführung in die Welt der Statistik," SFB 373 Discussion Papers 2001,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Aydınlı, Gökhan & Härdle, Wolfgang Karl & Rönz, Bernd, 2003. "E-learning, e-teaching of statistics: A new challenge," SFB 373 Discussion Papers 2003,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Härdle, Wolfgang & Rönz, Bernd, 2002. "E-learning / e-teaching of statistics: Students' and teachers' views," SFB 373 Discussion Papers 2002,84, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.

  75. Christian M. Hafner & Wolfgang HÄrdle, 2000. "Discrete time option pricing with flexible volatility estimation," Finance and Stochastics, Springer, vol. 4(2), pages 189-207.

    Cited by:

    1. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2012. "GARCH Option Valuation: Theory and Evidence," CREATES Research Papers 2012-50, Department of Economics and Business Economics, Aarhus University.
    2. Lars Stentoft, 2008. "American Option Pricing Using GARCH Models and the Normal Inverse Gaussian Distribution," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 540-582, Fall.
    3. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    4. Fengler, Matthias & Melnikov, Alexander, 2017. "GARCH option pricing models with Meixner innovations," Economics Working Paper Series 1702, University of St. Gallen, School of Economics and Political Science.
    5. Karanasos, Menelaos & Kim, Jinki, 2006. "A re-examination of the asymmetric power ARCH model," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 113-128, January.
    6. Härdle, Wolfgang & Sperlich, Stefan, 1997. "Financial calculations on the net," SFB 373 Discussion Papers 1997,42, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. M, El Babsiri & Jean-Michel Zakoïan, 1997. "Contemporaneous Asymmetry in GARCH Processes," Working Papers 97-03, Center for Research in Economics and Statistics.
    8. Radovan Parrák, 2013. "The Economic Valuation of Variance Forecasts: An Artificial Option Market Approach," Working Papers IES 2013/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2013.
    9. Anna Pajor, 2009. "Bayesian Analysis of the Box-Cox Transformation in Stochastic Volatility Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 81-90.
    10. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    11. Badescu, Alexandru M. & Kulperger, Reg J., 2008. "GARCH option pricing: A semiparametric approach," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 69-84, August.
    12. Jacobi, Frank, 2005. "ARCH-Prozesse und ihre Erweiterungen - Eine empirische Untersuchung für Finanzmarktzeitreihen -," Arbeitspapiere des Instituts für Statistik und Ökonometrie 31, Johannes Gutenberg-Universität Mainz, Institut für Statistik und Ökonometrie.
    13. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Pricing individual stock options using both stock and market index information," Journal of Banking & Finance, Elsevier, vol. 111(C).
    14. Lars Stentoft, 2011. "What we can learn from pricing 139,879 Individual Stock Options," CREATES Research Papers 2011-52, Department of Economics and Business Economics, Aarhus University.
    15. Jin-Chuan Duan & Peter H. Ritchken & Zhiqiang Sun, 2006. "Jump starting GARCH: pricing and hedging options with jumps in returns and volatilities," Working Papers (Old Series) 0619, Federal Reserve Bank of Cleveland.
    16. Peter Christoffersen & Kris Jacobs, 2002. "Which Volatility Model for Option Valuation?," CIRANO Working Papers 2002s-33, CIRANO.
    17. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
    18. Thorsten Lehnert & Gildas Blanchard & Dennis Bams, 2014. "Evaluating Option Pricing Model Performance Using Model Uncertainty," LSF Research Working Paper Series 14-06, Luxembourg School of Finance, University of Luxembourg.
    19. Duan, Jin-Chuan & Wei, Jason, 2005. "Executive stock options and incentive effects due to systematic risk," Journal of Banking & Finance, Elsevier, vol. 29(5), pages 1185-1211, May.
    20. Papantonis, Ioannis, 2016. "Volatility risk premium implications of GARCH option pricing models," Economic Modelling, Elsevier, vol. 58(C), pages 104-115.

  76. Peter Hall & Wolfgang Härdle & Torsten Kleinow & Peter Schmidt, 2000. "Semiparametric Bootstrap Approach to Hypothesis Tests and Confidence Intervals for the Hurst Coefficient," Statistical Inference for Stochastic Processes, Springer, vol. 3(3), pages 263-276, October.

    Cited by:

    1. Beran, Jan & Shumeyko, Yevgen, 2012. "Bootstrap testing for discontinuities under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 322-347.
    2. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," Papers 1608.01895, arXiv.org, revised Mar 2018.
    3. Myoungji Lee & Marc G. Genton & Mikyoung Jun, 2016. "Testing Self-Similarity Through Lamperti Transformations," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 426-447, September.
    4. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Li, Wen & Yu, Cindy & Carriquiry, Alicia & Kliemann, Wolfgang, 2011. "The asymptotic behavior of the R/S statistic for fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 81(1), pages 83-91, January.
    6. Erhan Bayraktar & H. Vincent Poor & Ronnie Sircar, 2007. "Estimating the Fractal Dimension of the S&P 500 Index using Wavelet Analysis," Papers math/0703834, arXiv.org.
    7. Garcin, Matthieu, 2017. "Estimation of time-dependent Hurst exponents with variational smoothing and application to forecasting foreign exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 462-479.
    8. Mikkel Bennedsen, 2016. "Semiparametric inference on the fractal index of Gaussian and conditionally Gaussian time series data," CREATES Research Papers 2016-21, Department of Economics and Business Economics, Aarhus University.

  77. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.

    Cited by:

    1. Sukjin Han, 2012. "Nonparametric Estimation of Triangular Simultaneous Equations Models under Weak Identification," Department of Economics Working Papers 140414, The University of Texas at Austin, Department of Economics, revised Apr 2014.
    2. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    3. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    4. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    5. Guo, Zheng-Feng & Shintani, Mototsugu, 2011. "Nonparametric lag selection for nonlinear additive autoregressive models," Economics Letters, Elsevier, vol. 111(2), pages 131-134, May.
    6. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2014. "Testing for additivity in partially linear regression with possibly missing responses," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 51-61.
    7. Martins-Filho, Carlos & yang, ke, 2007. "Finite sample performance of kernel-based regression methods for non-parametric additive models under common bandwidth selection criterion," MPRA Paper 39295, University Library of Munich, Germany.
    8. Yang, Lijian & Sperlich, Stefan & Hardle, Wolfgang, 2000. "Derivative estimation and testing in generalized additive models," DES - Working Papers. Statistics and Econometrics. WS 10084, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    10. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    11. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and predicting the distribution of the number of visits to the medical doctor," MAGKS Papers on Economics 201148, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    12. Wolfgang Karl Hardle & Elena Silyakova, 2020. "Implied Basket Correlation Dynamics," Papers 2009.09770, arXiv.org.
    13. Härdle Wolfgang Karl & Silyakova Elena, 2016. "Implied basket correlation dynamics," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 1-20, September.
    14. Berthold R. Haag, 2008. "Non‐parametric Regression Tests Using Dimension Reduction Techniques," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 719-738, December.
    15. Grasshoff, Ulrike & Schwalbach, Joachim & Sperlich, Stefan, 1999. "Executive pay and corporate financial performance. An exploratiove data analysis," DES - Working Papers. Statistics and Econometrics. WS 6382, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Graciela Boente & Alejandra Martínez & Matías Salibián-Barrera, 2017. "Robust estimators for additive models using backfitting," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(4), pages 744-767, October.
    17. Rodriguez Poo, Juan M. & Sperlich, Stefan & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 246-272, August.
    19. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    20. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    21. Michael Scholz & Stefan Sperlich & Jens Perch Nielsen, 2012. "Nonparametric prediction of stock returns with generated bond yields," Graz Economics Papers 2012-10, University of Graz, Department of Economics.

  78. Wolfgang Härdle & Alois Kneip, 1999. "Testing a Regression Model When We Have Smooth Alternatives in Mind," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(2), pages 221-238, June.

    Cited by:

    1. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
    2. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.

  79. Wolfgang Härdle & Helmut Lütkepohl & Rong Chen, 1997. "A Review of Nonparametric Time Series Analysis," International Statistical Review, International Statistical Institute, vol. 65(1), pages 49-72, April.

    Cited by:

    1. Chen, Rong, 1998. "Functional coefficient autoregressive models: Estimation and tests of hypotheses," SFB 373 Discussion Papers 1998,10, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Wolfgang Karl Härdle & Rainer Schulz & Weining Wang, 2010. "Prognose mit nichtparametrischen Verfahren," SFB 649 Discussion Papers SFB649DP2010-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Wu, Wei Biao & Huang, Yinxiao & Huang, Yibi, 2010. "Kernel estimation for time series: An asymptotic theory," Stochastic Processes and their Applications, Elsevier, vol. 120(12), pages 2412-2431, December.
    4. Ayse Yilmaz & Ufuk Yolcu, 2022. "Dendritic neuron model neural network trained by modified particle swarm optimization for time‐series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 793-809, July.
    5. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    6. Park, Jin-Hong & Bandyopadhyay, Dipankar & Letourneau, Elizabeth, 2014. "Examining deterrence of adult sex crimes: A semi-parametric intervention time-series approach," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 198-207.
    7. Mohamed Chikhi & Claude Diebolt, 2006. "Nonparametric Analysis of Financial Time Series by the Kernel Methodology," Working Papers 06-11, Association Française de Cliométrie (AFC).
    8. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    9. Tschernig, Rolf & Yang, Lijian, 2000. "Nonparametric estimation of generalized impulse response function," SFB 373 Discussion Papers 2000,89, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," LSE Research Online Documents on Economics 28868, London School of Economics and Political Science, LSE Library.
    11. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    12. Michael Wegener & Göran Kauermann, 2017. "Forecasting in nonlinear univariate time series using penalized splines," Statistical Papers, Springer, vol. 58(3), pages 557-576, September.
    13. Tierney, Heather L.R., 2010. "Real-Time Data Revisions and the PCE Measure of Inflation," MPRA Paper 22387, University Library of Munich, Germany, revised Apr 2010.
    14. Sami MESTIRI, 2022. "Modeling the volatility of Bitcoin returns using Nonparametric GARCH models," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 2-16, June.
    15. Luz M. Gómez & Rogério F. Porto & Pedro A. Morettin, 2021. "Nonparametric regression with warped wavelets and strong mixing processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1203-1228, December.
    16. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    17. Göran Kauermann, 2006. "Nonparametric models and their estimation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 137-152, March.
    18. Xinyi Wang & Qing Zhao & Lang Tong, 2024. "Forecasting Electricity Market Signals via Generative AI," Papers 2403.05743, arXiv.org, revised Apr 2024.
    19. Norberto Rodríguez & Patricia Siado, 2003. "Un Pronóstico No Paramétrico De La Inflación Colombiana," Borradores de Economia 3691, Banco de la Republica.
    20. N. Balakrishna & Hira L. Koul, 2017. "Varying kernel marginal density estimator for a positive time series," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(3), pages 531-552, July.
    21. Jürgen Franke & Peter Mwita & Weining Wang, 2015. "Nonparametric estimates for conditional quantiles of time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 107-130, January.
    22. Xinli Yu & Zheng Chen & Yuan Ling & Shujing Dong & Zongyi Liu & Yanbin Lu, 2023. "Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting," Papers 2306.11025, arXiv.org.
    23. Tao Chen & Yixuan Li & Renfang Tian, 2023. "A Functional Data Approach for Continuous-Time Analysis Subject to Modeling Discrepancy under Infill Asymptotics," Mathematics, MDPI, vol. 11(20), pages 1-27, October.
    24. Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
    25. Tierney, Heather L.R., 2013. "Forecasting and Tracking Real-Time Data Revisions in Inflation Persistence," MPRA Paper 53374, University Library of Munich, Germany, revised Nov 2013.
    26. Jin-Hong Park, 2012. "Nonparametric approach to intervention time series modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1397-1408, December.
    27. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    28. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707.
    29. Härdle, Wolfgang Karl & Chen, Ying & Schulz, Rainer, 2004. "Prognose mit nichtparametrischen Verfahren," Papers 2004,07, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    30. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    31. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    32. R. J. Biscay & Marc Lavielle & Carenne Ludeña, 2005. "Estimation of Nonparametric Autoregressive Time Series Models Under Dynamical Constraints," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(3), pages 371-397, May.
    33. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    34. Göran Kauermann & Timo Teuber & Peter Flaschel, 2012. "Exploring US Business Cycles with Bivariate Loops Using Penalized Spline Regression," Computational Economics, Springer;Society for Computational Economics, vol. 39(4), pages 409-427, April.
    35. HARDLE, Wolfgang & HAFNER, Christian M., 2000. "Discrete time option pricing with flexible volatility estimation," LIDAM Reprints CORE 1439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. Xialu Liu & Zongwu Cai & Rong Chen, 2015. "Functional coefficient seasonal time series models with an application of Hawaii tourism data," Computational Statistics, Springer, vol. 30(3), pages 719-744, September.
    37. Lütkepohl, Helmut, 1999. "Vector autoregressive analysis," SFB 373 Discussion Papers 1999,31, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    38. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Aug 2023.
    39. Bai, Zhidong & Hui, Yongchang & Wong, Wing-Keung, 2012. "New Non-Linearity Test to Circumvent the Limitation of Volterra Expansion," MPRA Paper 41872, University Library of Munich, Germany.
    40. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    41. Nottingham, Quinton J. & Cook, Deborah F., 2001. "Local linear regression for estimating time series data," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 209-217, August.
    42. Cline, Daren B. H. & Pu, Huay-min H., 1999. "Stability of nonlinear AR(1) time series with delay," Stochastic Processes and their Applications, Elsevier, vol. 82(2), pages 307-333, August.
    43. Lütkepohl, Helmut, 1999. "Vector autoregressions," SFB 373 Discussion Papers 1999,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    44. Liu, Xialu & Xiao, Han & Chen, Rong, 2016. "Convolutional autoregressive models for functional time series," Journal of Econometrics, Elsevier, vol. 194(2), pages 263-282.
    45. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    46. CHIKHI, Mohamed, 2009. "Identification non paramétrique d’un processus non linéaire hétéroscédastique [Nonparametric identification of heteroscedastic nonlinear process]," MPRA Paper 82108, University Library of Munich, Germany, revised 2009.
    47. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    48. Cai, Zongwu & Fan, Jianqing, 2000. "Average Regression Surface for Dependent Data," Journal of Multivariate Analysis, Elsevier, vol. 75(1), pages 112-142, October.
    49. Heiler, Siegfried, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Papers 99/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    50. Jungwoo Kim & Joocheol Kim, 2017. "Nonparametric forecasting with one-sided kernel adopting pseudo one-step ahead data," Working papers 2017rwp-102, Yonsei University, Yonsei Economics Research Institute.
    51. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear modal regression for dependent data with application for predicting COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1424-1453, July.
    52. Chikhi, Mohamed & Terraza, Michel, 2002. "Un essai de prévision non paramétrique de l'action France Télécom [A nonparametric prediction test of the France Telecom stock proces]," MPRA Paper 77268, University Library of Munich, Germany, revised Dec 2003.
    53. Eduardo Mendes & Alvaro Veiga & MArcelo Cunha Medeiros, 2007. "Estimation And Asymptotic Theory For A New Class Of Mixture Models," Textos para discussão 538, Department of Economics PUC-Rio (Brazil).
    54. Gao, Jiti & Tong, Howell, 2002. "Nonparametric and semiparametric regression model selection," MPRA Paper 11987, University Library of Munich, Germany, revised Feb 2004.
    55. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    56. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    57. Silvano Bordignon & Carlo Gaetan & Francesco Lisi, 2002. "Nonlinear models for ground-level ozone forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 227-245, June.
    58. Hafner, C.M. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2005. "Semi-Parametric Modelling of Correlation Dynamics," Econometric Institute Research Papers EI 2005-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    59. De Gooijer, Jan G. & Ray, Bonnie K., 2003. "Modeling vector nonlinear time series using POLYMARS," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 73-90, February.

  80. Hardle, Wolfgang & Kirman, Alan, 1995. "Nonclassical demand : A model-free examination of price-quantity relations in the Marseille fish market," Journal of Econometrics, Elsevier, vol. 67(1), pages 227-257, May.

    Cited by:

    1. Linda Ponta & Mailan Trinh & Marco Raberto & Enrico Scalas & Silvano Cincotti, 2012. "Modeling non-stationarities in high-frequency financial time series," Papers 1212.0479, arXiv.org, revised Feb 2017.
    2. Guillotreau, Patrice & Jiménez-Toribio, Ramón, 2011. "The price effect of expanding fish auction markets," Journal of Economic Behavior & Organization, Elsevier, vol. 79(3), pages 211-225, August.
    3. Ali Ellouze & Bastien Fernandez, 2023. "Population dynamics in fresh product markets with no posted prices," Papers 2311.03987, arXiv.org.
    4. Daniele Giachini, 2018. "Rationality and Asset Prices under Belief Heterogeneity," LEM Papers Series 2018/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Mauro Gallegati & Gianfranco Giulioni & Alan Kirman & Antonio Palestrini, 2010. "What's that got to do with the price of fish? Buyers behavior on the Ancona fish market," Working Papers halshs-00545129, HAL.
    6. Kevin Primicerio & Damien Challet & Stanislao Gualdi, 2021. "Collective rationality and functional wisdom of the crowd in far-from-rational institutional investors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 153-171, January.
    7. François-Charles Wolff & Frank Asche, 2022. "Pricing heterogeneity and transaction mode: Evidence from the French fish market," Post-Print hal-03913067, HAL.
    8. Geoffrey M. Hodgson, 2019. "The great crash of 2008 and the reform of economics," Chapters, in: Jonathan Michie (ed.), The Handbook of Globalisation, Third Edition, chapter 28, pages 439-456, Edward Elgar Publishing.
    9. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
    10. Kathryn Graddy, 2006. "Markets: The Fulton Fish Market," Journal of Economic Perspectives, American Economic Association, vol. 20(2), pages 207-220, Spring.
    11. Daniele Giachini, 2021. "Rationality and asset prices under belief heterogeneity," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 207-233, January.
    12. Andreas Karpf & Antoine Mandel & Stefano Battiston, 2018. "Price and network dynamics in the European carbon market," Post-Print halshs-01905985, HAL.
    13. David Morton de Lachapelle & Damien Challet, 2009. "Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior," Papers 0912.4723, arXiv.org, revised Jun 2010.
    14. Itay P. Fainmesser, 2012. "Community Structure and Market Outcomes: A Repeated Games-in-Networks Approach," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 32-69, February.
    15. Alfnes, Frode & Rickertsen, Kyrre, 2009. "Unstable Individual Preferences and Stable Aggregate Demand: French Consumers’ Willingness to Pay for Farmed and Wild Cod," 2009 Conference, August 16-22, 2009, Beijing, China 49968, International Association of Agricultural Economists.
    16. Laurent Gobillon & François Charles Wolff & Patrice Guillotreau, 2013. "Evaluating the law of one price using micro panel data," Working Papers halshs-00849075, HAL.
    17. Damien Challet, 2016. "Regrets, learning and wisdom," Post-Print hal-01312973, HAL.
    18. Kirman, Alan & Wolfgang Hardle & Rainer Schulz & Axel Werwatz, 2003. "Transactions That Did Not Happen and Their Influence on Prices," Royal Economic Society Annual Conference 2003 123, Royal Economic Society.
    19. Dhananjay (Dan) K. Gode & Shyam Sunder, 2000. "Double Auction Dynamics: Structural Effects Of Non-Binding Price Controls," Yale School of Management Working Papers ysm1, Yale School of Management.
    20. Gallegati, Mauro & Kirman, Alan, 2019. "20 years of WEHIA: A journey in search of a safer road," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 5-14.
    21. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    22. David Cayla, 2014. "" Concurrence ", de quoi parlons-nous ?," Working Papers halshs-00994773, HAL.
    23. Franck Galtier & François Bousquet & Martine Antona & Pierre Bommel, 2012. "Markets as communication systems," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 161-201, January.
    24. Keuzenkamp, Hugo A. & Magnus, Jan R., 1995. "On tests and significance in econometrics," Journal of Econometrics, Elsevier, vol. 67(1), pages 5-24, May.
    25. Homans, Frances R. & Wilen, James E., 2000. "Market Rent Dissipation In Regulated Open Access Fisheries," 2000 Annual meeting, July 30-August 2, Tampa, FL 21878, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    26. Beard, Rodney, 2008. "A dynamic model of renewable resource harvesting with Bertrand competition," MPRA Paper 8916, University Library of Munich, Germany.
    27. Alfnes, Frode & Rickertsen, Kyrre & Shogren, Jason F., 2011. "Unstable Individual Bids and Stable Market Demand," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114219, European Association of Agricultural Economists.
    28. Morra, Wayne & Hearn, Gail & Buck, Andrew J., 2009. "The market for bushmeat: Colobus Satanas on Bioko Island," Ecological Economics, Elsevier, vol. 68(10), pages 2619-2626, August.
    29. Giulioni, Gianfranco & Bucciarelli, Edgardo, 2011. "Agents’ ability to manage information in centralized markets: Comparing two wholesale fish markets," Journal of Economic Behavior & Organization, Elsevier, vol. 80(1), pages 34-49.
    30. Fainmesser, Itay P. & Goldberg, David A., 2018. "Cooperation in partly observable networked markets," Games and Economic Behavior, Elsevier, vol. 107(C), pages 220-237.
    31. Giovanni Dosi, 2023. "Why is economics the only discipline with so many curves going up and down? There is an alternative," LEM Papers Series 2023/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    32. Homans, Frances R. & Wilen, James E., 2005. "Markets and rent dissipation in regulated open access fisheries," Journal of Environmental Economics and Management, Elsevier, vol. 49(2), pages 381-404, March.
    33. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    34. Itay P. Fainmesser & David A. Goldberg, 2011. "Bilateral and Community Enforcement in a Networked Market with Simple Strategies," Working Papers 2011-2, Brown University, Department of Economics.

  81. Hardle, W. & Park, B. U. & Tsybakov, A. B., 1995. "Estimation of Non-sharp Support Boundaries," Journal of Multivariate Analysis, Elsevier, vol. 55(2), pages 205-218, November.

    Cited by:

    1. Hall, Peter & Nussbaum, Michael & Stern, Steven E., 1997. "On the Estimation of a Support Curve of Indeterminate Sharpness," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 204-232, August.
    2. Abdelaati Daouia & Jean-Pierre Florens & Léopold Simar, 2020. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," Post-Print hal-02573853, HAL.
    3. Girard, Séphane & Jacob, Pierre, 2009. "Frontier estimation with local polynomials and high power-transformed data," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1691-1705, September.
    4. Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2009. "Frontier Estimation and Extreme Values Theory," TSE Working Papers 10-165, Toulouse School of Economics (TSE).
    5. Anderson, Gordon & Linton, Oliver & Whang, Yoon-Jae, 2012. "Nonparametric estimation and inference about the overlap of two distributions," Journal of Econometrics, Elsevier, vol. 171(1), pages 1-23.
    6. U. Park, Byeong, 2001. "On estimating the slope of increasing boundaries," Statistics & Probability Letters, Elsevier, vol. 52(1), pages 69-72, March.
    7. Abdelaati Daouia & Hohsuk Noh & Byeong U. Park, 2016. "Data envelope fitting with constrained polynomial splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 3-30, January.
    8. Daouia, Abdelaati & Girard, Stéphane & Guillou, Armelle, 2014. "A Γ-moment approach to monotonic boundary estimation," Journal of Econometrics, Elsevier, vol. 178(2), pages 727-740.
    9. Cheng, Ming-Yen & Hall, Peter, 2006. "Methods for tracking support boundaries with corners," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1870-1893, September.
    10. Abdelaati Daouia & Laurent Gardes & Stéphane Girard & Alexandre Lekina, 2011. "Kernel estimators of extreme level curves," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 311-333, August.
    11. Gijbels, Irène & Mammen, Enno & Park, Byeong U. & Simar, Léopold, 1998. "On estimation of monotone and concave frontier functions," SFB 373 Discussion Papers 1998,9, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Klemelä, Jussi, 2004. "Complexity penalized support estimation," Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 274-297, February.
    13. Girard, Stéphane & Guillou, Armelle & Stupfler, Gilles, 2013. "Frontier estimation with kernel regression on high order moments," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 172-189.
    14. Natalie Neumeyer & Leonie Selk & Charles Tillier, 2020. "Semi-parametric transformation boundary regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1287-1315, December.
    15. Biau, Gérard & Cadre, Benoît & Pelletier, Bruno, 2008. "Exact rates in density support estimation," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2185-2207, November.
    16. Girard, Stéphane & Jacob, Pierre, 2008. "Frontier estimation via kernel regression on high power-transformed data," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 403-420, March.
    17. Jeong, Seok-Oh & Park, Byeong U., 2004. "Limit Distribution of Convex-Hull Estimators of Boundaries," Papers 2004,39, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    18. Hwang, J. H. & Park, B. U. & Ryu, W., 2002. "Limit theorems for boundary function estimators," Statistics & Probability Letters, Elsevier, vol. 59(4), pages 353-360, October.
    19. Hall, Peter & Park, Byeong U., 2004. "Bandwidth choice for local polynomial estimation of smooth boundaries," Journal of Multivariate Analysis, Elsevier, vol. 91(2), pages 240-261, November.
    20. Daouia, Abdelaati & Laurent, Thibault & Noh, Hohsuk, 2015. "npbr: A Package for Nonparametric Boundary Regression in R," TSE Working Papers 15-576, Toulouse School of Economics (TSE).
    21. Girard, Stéphane, 2004. "On the asymptotic normality of the L1-error for Haar series estimates of Poisson point processes boundaries," Statistics & Probability Letters, Elsevier, vol. 66(1), pages 81-90, January.
    22. Aaron, C. & Bodart, O., 2016. "Local convex hull support and boundary estimation," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 82-101.
    23. Goldenshluger, A. & Tsybakov, A., 2004. "Estimating the endpoint of a distribution in the presence of additive observation errors," Statistics & Probability Letters, Elsevier, vol. 68(1), pages 39-49, June.
    24. Meister, Alexander, 2006. "Estimating the support of multivariate densities under measurement error," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1702-1717, September.

  82. Horowitz, Joel L. & Härdle, Wolfgang, 1994. "Testing a Parametric Model Against a Semiparametric Alternative," Econometric Theory, Cambridge University Press, vol. 10(5), pages 821-848, December.

    Cited by:

    1. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    2. Ellison, Glenn & Ellison, Sara Fisher, 2000. "A simple framework for nonparametric specification testing," Journal of Econometrics, Elsevier, vol. 96(1), pages 1-23, May.
    3. Herwartz, H. & Xu, F., 2009. "A new approach to bootstrap inference in functional coefficient models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2155-2167, April.
    4. Cui Rui & Li Yuhao, 2024. "Goodness-of-Fit for Conditional Distributions: An Approach Using Principal Component Analysis and Component Selection," Papers 2403.10352, arXiv.org.
    5. Escanciano, Juan Carlos & Jacho-Chávez, David T., 2010. "Approximating the critical values of Cramér-von Mises tests in general parametric conditional specifications," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 625-636, March.
    6. Manuel A. Domínguez & Ignacio N. Lobato, 2020. "Specification testing with estimated variables," Econometric Reviews, Taylor & Francis Journals, vol. 39(5), pages 476-494, May.
    7. Grant, Darren, 2016. "The essential economics of threshold-based incentives: Theory, estimation, and evidence from the Western States 100," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 180-197.
    8. Hall, Peter & Yatchew, Adonis, 2005. "Unified approach to testing functional hypotheses in semiparametric contexts," Journal of Econometrics, Elsevier, vol. 127(2), pages 225-252, August.
    9. Darren Grant, 2010. "The Simple Economics of Thresholds: Evidence from the Western States 100," Working Papers 1004, Sam Houston State University, Department of Economics and International Business.
    10. Li, Q. & Wang, Suojin, 1998. "A simple consistent bootstrap test for a parametric regression function," Journal of Econometrics, Elsevier, vol. 87(1), pages 145-165, August.
    11. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    12. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    13. Ait-Sahalia, Yacine & Bickel, Peter J. & Stoker, Thomas M., 2001. "Goodness-of-fit tests for kernel regression with an application to option implied volatilities," Journal of Econometrics, Elsevier, vol. 105(2), pages 363-412, December.
    14. González-Manteiga, Wenceslao & Quintela-del-Río, Alejandro & Vieu, Philippe, 2002. "A note on variable selection in nonparametric regression with dependent data," Statistics & Probability Letters, Elsevier, vol. 57(3), pages 259-268, April.
    15. León, Carmelo J. & Araña, Jorge E. & Hanemann, W. Michael & Riera, Pere, 2014. "Heterogeneity and emotions in the valuation of non-use damages caused by oil spills," Ecological Economics, Elsevier, vol. 97(C), pages 129-139.
    16. Li, Qi, 1999. "Consistent model specification tests for time series econometric models," Journal of Econometrics, Elsevier, vol. 92(1), pages 101-147, September.

  83. Hardle, Wolfgang & Manski, Charles F., 1993. "Nonparametric and semiparametric approaches to discrete response analysis," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 1-2, July.

    Cited by:

    1. Erik Bergkvist, 2001. "The value of time and forecasting of flowsin freight transportation," ERSA conference papers ersa01p271, European Regional Science Association.
    2. McDonald, James B., 1996. "An application and comparison of some flexible parametric and semi-parametric qualitative response models," Economics Letters, Elsevier, vol. 53(2), pages 145-152, November.
    3. William Greene, 2007. "Discrete Choice Modeling," Working Papers 07-6, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Murat GENÇ & Murray SMITH, 2008. "Wage Gaps in the New Zealand Labour Market," EcoMod2008 23800042, EcoMod.

  84. W. Härdle & P. Hall, 1993. "On the backfitting algorithm for additive regression models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 47(1), pages 43-57, March.

    Cited by:

    1. David Conde & Miguel A. Fernández & Cristina Rueda & Bonifacio Salvador, 2021. "Isotonic boosting classification rules," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(2), pages 289-313, June.
    2. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    3. Jianbao Chen & Suli Cheng, 2021. "GMM Estimation of a Partially Linear Additive Spatial Error Model," Mathematics, MDPI, vol. 9(6), pages 1-28, March.
    4. Chèze-Payaud, Nathalie & Poggi, Jean-Michel & Portier, Bruno, 1998. "Estimation and test of linearity for a class of additive nonlinear models," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 189-201, September.
    5. Hegland, Markus & McIntosh, Ian & Turlach, Berwin A., 1999. "A parallel solver for generalised additive models," Computational Statistics & Data Analysis, Elsevier, vol. 31(4), pages 377-396, October.
    6. Opsomer, Jean D., 2000. "Asymptotic Properties of Backfitting Estimators," Journal of Multivariate Analysis, Elsevier, vol. 73(2), pages 166-179, May.
    7. Cheng, Suli & Chen, Jianbao, 2023. "GMM estimation of partially linear additive spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).

  85. Hall, Peter & Hardle, Wolfgang & Simar, Leopold, 1993. "On the inconsistency of bootstrap distribution estimators," Computational Statistics & Data Analysis, Elsevier, vol. 16(1), pages 11-18, June.
    See citations under working paper version above.
  86. Hardle, Wolfgang & Hildenbrand, Werner & Jerison, Michael, 1991. "Empirical Evidence on the Law of Demand," Econometrica, Econometric Society, vol. 59(6), pages 1525-1549, November.

    Cited by:

    1. Hiroaki Kaido, 2014. "Asymptotically efficient estimation of weighted average derivatives with an interval censored variable," CeMMAP working papers 03/14, Institute for Fiscal Studies.
    2. David Calnitsky & Asher Dupuy-Spencer, 2013. "The economic consequences of homo economicus: neoclassical economic theory and the fallacy of market optimality," The Journal of Philosophical Economics, Bucharest Academy of Economic Studies, The Journal of Philosophical Economics, vol. 6(2), May.
    3. Marcia M Schafgans & Victoria Zinde-Walshyz, 2008. "Smoothness Adaptive AverageDerivative Estimation," STICERD - Econometrics Paper Series 529, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    5. Koebel, Bertrand M. & Falk, Martin, 1999. "Curvature conditions and substitution pattern among capital, energy, materials and heterogeneous labour," ZEW Discussion Papers 99-06, ZEW - Leibniz Centre for European Economic Research.
    6. Hans-Jürgen Salchow, 2005. "Non-existence of equilibria with free elimination," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00195903, HAL.
    7. Yulia Kotlyarova & Marcia M Schafgans & Victoria Zinde-Walsh, 2011. "Adapting Kernel Estimation to Uncertain Smoothness," STICERD - Econometrics Paper Series 557, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    8. Adena, Maja & Huck, Steffen & Rasul, Imran, 2017. "Testing consumer theory: evidence from a natural field experiment," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(2), pages 89-108.
    9. Jean-Michel Grandmont & Alan Kirman, 1996. "Aggregation, Learning and Rationality," International Economic Association Series, in: Beth Allen (ed.), Economics in a Changing World, chapter 3, pages 63-89, Palgrave Macmillan.
    10. YOSHIKAWA Hiroshi & ARATA Yoshiyuki, 2023. "A Reconsideration of Microeconomic Foundations of Macroeconomics," Discussion papers 23079, Research Institute of Economy, Trade and Industry (RIETI).
    11. Holger Dette & Stefan Hoderlein & Natalie Neumeyer, 2013. "Testing Multivariate Economic Restrictions Using Quantiles: The Example of Slutsky Negative Semidefiniteness," Boston College Working Papers in Economics 836, Boston College Department of Economics.
    12. B.U.PARK & Wolfgang HAERDLE, "undated". "Testing increasing dispersion," Statistic und Oekonometrie 9314, Humboldt Universitaet Berlin.
    13. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    14. W D A Bryant, 2009. "General Equilibrium:Theory and Evidence," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6875, January.
    15. Matsushita, Yukitoshi & Otsu, Taisuke, 2018. "Likelihood inference on semiparametric models: average derivative and treatment effect," LSE Research Online Documents on Economics 85870, London School of Economics and Political Science, LSE Library.
    16. Stefan Hoderlein, 2009. "How Many Consumers are Rational?," Boston College Working Papers in Economics 748, Boston College Department of Economics.
    17. Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2021. "Average Derivative Estimation Under Measurement Error," Econometric Theory, Cambridge University Press, vol. 37(5), pages 1004-1033, October.
    18. Evstigneev, I. V. & Hildenbrand, W. & Jerison, M., 1997. "Metonymy and cross-section demand," Journal of Mathematical Economics, Elsevier, vol. 28(4), pages 397-414, November.
    19. INOSE Junya, 2014. "Representative Agent in a Form of Probability Distribution," Discussion papers 14038, Research Institute of Economy, Trade and Industry (RIETI).
    20. Jouini, Elyès & Napp, Clotilde & Nocetti, Diego, 2013. "On multivariate prudence," Journal of Economic Theory, Elsevier, vol. 148(3), pages 1255-1267.
    21. Michael Jerison, 2023. "Social welfare and the unrepresentative representative consumer," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(1), pages 5-28, February.
    22. Yukitoshi Matsushita & Taisuke Otsu, 2018. "Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect," The Japanese Economic Review, Springer, vol. 69(2), pages 133-155, June.
    23. Larsson, Lars-Göran, 2009. "On the Law of Demand. - A mathematically simple descriptive approach for general probability density functions," Working Papers in Economics 396, University of Gothenburg, Department of Economics.
    24. Koebel, Bertrand M. & Falk, Martin & Laisney, François, 2000. "Imposing and testing curvature conditions on a Box-Cox function," ZEW Discussion Papers 00-70, ZEW - Leibniz Centre for European Economic Research.
    25. Michael Jerison, 1997. "Nonrepresentative Representative Consumers," Discussion Papers 97-01, University at Albany, SUNY, Department of Economics.
    26. Mongin, Philippe, 2006. "On the confirmation of the law of demand," LSE Research Online Documents on Economics 58432, London School of Economics and Political Science, LSE Library.
    27. Evstigneev, Igor & Taksar, Michael, 2009. "Dynamic interaction models of economic equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 166-182, January.
    28. Werner Hildenbrand & Alois Kneip, 2005. "On behavioral heterogeneity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 25(1), pages 155-169, January.
    29. Brighi, Luigi, 2004. "A stronger criterion for the Weak Weak Axiom," Journal of Mathematical Economics, Elsevier, vol. 40(1-2), pages 93-103, February.
    30. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, University Library of Munich, Germany, revised 05 Mar 1996.
    31. Adil Ahmad Mughal, 2022. "Kantian Epistemology in Examination of the Axiomatic Principles of Economics: the Synthetic a Priori in the Economic Structure of Society," Working Papers hal-03787520, HAL.
    32. Larsson, Lars-Göran, 2010. "General Properties of Expected Demand Functions: Negativity (No Giffen Good) and Homogeneity - A Descriptive Non Utility Maximizing Approach," Working Papers in Economics 469, University of Gothenburg, Department of Economics.
    33. Zizhuo Wang & Chaolin Yang & Hongsong Yuan & Yaowu Zhang, 2021. "Aggregation Bias in Estimating Log‐Log Demand Function," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 3906-3922, November.
    34. Hildenbrand, Werner, 1989. "Facts and ideas in microeconomic theory," European Economic Review, Elsevier, vol. 33(2-3), pages 251-276, March.
    35. Jerison, Michael, 1999. "Dispersed excess demands, the weak axiom and uniqueness of equilibrium," Journal of Mathematical Economics, Elsevier, vol. 31(1), pages 15-48, February.
    36. Kneip, Alois, 1999. "Behavioral heterogeneity and structural properties of aggregate demand," Journal of Mathematical Economics, Elsevier, vol. 31(1), pages 49-79, February.
    37. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    38. Larsson, Lars-Göran, 2012. "On Expected Demand Functions without Utility Maximization," Working Papers in Economics 527, University of Gothenburg, Department of Economics.
    39. Hardle, W. & Park, B. U., 1995. "Testing increasing dispersion," Computational Statistics & Data Analysis, Elsevier, vol. 19(6), pages 641-653, June.
    40. Michael Jerison & John K.-H. Quah, 2006. "Law of Demand," Discussion Papers 06-07, University at Albany, SUNY, Department of Economics.
    41. Evstigneev, I. & Taksar, M., 1994. "Stochastic equilibria on graphs, I," Journal of Mathematical Economics, Elsevier, vol. 23(5), pages 401-433, September.
    42. Edmond Malinvaud, 1993. "Regard d'un ancien sur les nouvelles théories de la croissance," Revue Économique, Programme National Persée, vol. 44(2), pages 171-188.
    43. Jacinta C. Nwachukwu, 2017. "Tenure and Spending Within UK Households at the End of the Recent Recession," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 1075-1104, September.
    44. Alan Kirman, 2006. "Heterogeneity in Economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(1), pages 89-117, May.
    45. Banerjee, Anurag, 2007. "A method of estimating the average derivative," Journal of Econometrics, Elsevier, vol. 136(1), pages 65-88, January.
    46. Guerrien, Bernard, 1992. "Où en est le programme de recherche néo-classique?," L'Actualité Economique, Société Canadienne de Science Economique, vol. 68(4), pages 564-586, décembre.
    47. Paul Oslington, 2012. "General Equilibrium: Theory and Evidence," The Economic Record, The Economic Society of Australia, vol. 88(282), pages 446-448, September.

  87. Carroll, R. J. & Härdle, W., 1989. "Symmetrized nearest neighbor regression estimates," Statistics & Probability Letters, Elsevier, vol. 7(4), pages 315-318, February.

    Cited by:

    1. Yanqin Fan & Ruixuan Liu, 2015. "Symmetrized Multivariate k -NN Estimators," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 828-848, December.
    2. Wolfgang Karl Härdle & Natalia Sirotko-Sibirskaya & Weining Wang, 2014. "TENET: Tail-Event driven NETwork risk," SFB 649 Discussion Papers SFB649DP2014-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  88. Härdle, Wolfgang, 1989. "Asymptotic maximal deviation of M-smoothers," Journal of Multivariate Analysis, Elsevier, vol. 29(2), pages 163-179, May.

    Cited by:

    1. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    2. Liugen Xue, 2010. "Empirical Likelihood Local Polynomial Regression Analysis of Clustered Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(4), pages 644-663, December.
    3. Shujie Ma & Lijian Yang, 2011. "A jump-detecting procedure based on spline estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(1), pages 67-81.
    4. Wolfgang Karl Härdle & Ya'acov Ritov & Weining Wang, 2013. "Tie the straps: uniform bootstrap confidence bands for bounded influence curve estimators," SFB 649 Discussion Papers SFB649DP2013-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Katharina Proksch, 2016. "On confidence bands for multivariate nonparametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(1), pages 209-236, February.
    6. Yuanyuan Zhang & Lijian Yang, 2018. "A smooth simultaneous confidence band for correlation curve," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 247-269, June.
    7. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang K. Härdle, 2016. "Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 607-626, December.
    8. Shuzhuan Zheng & Rong Liu & Lijian Yang & Wolfgang Karl Härdle, 2014. "Simultaneous Confidence Corridors and Variable Selection for Generalized Additive Models," SFB 649 Discussion Papers SFB649DP2014-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Gørgens, Tue, 2002. "Nonparametric comparison of regression curves by local linear fitting," Statistics & Probability Letters, Elsevier, vol. 60(1), pages 81-89, November.
    10. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    11. Birke, Melanie & Bissantz, Nicolai & Holzmann, Hajo, 2008. "Confidence bands for inverse regression models with application to gel electrophoresis," Technical Reports 2008,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    12. Bissantz, Nicolai & Dümbgen, Lutz & Holzmann, Hajo & Munk, Axel, 2007. "Nonparametric confidence bands in deconvolution density estimation," Technical Reports 2007,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    13. Li Cai & Lijian Yang, 2015. "A smooth simultaneous confidence band for conditional variance function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 632-655, September.
    14. K. De Brabanter & Y. Liu & C. Hua, 2016. "Convergence rates for uniform confidence intervals based on local polynomial regression estimators," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 31-48, March.
    15. Néstor Aguilera & Liliana Forzani & Pedro Morin, 2011. "On uniform consistent estimators for convex regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 897-908.
    16. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.
    17. Härdle, Wolfgang K. & Song, Song, 2010. "Confidence Bands In Quantile Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1180-1200, August.
    18. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Härdle, 2014. "Confidence Corridors for Multivariate Generalized Quantile Regression," SFB 649 Discussion Papers SFB649DP2014-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
    20. Ali Al-Sharadqah & Majid Mojirsheibani, 2020. "A simple approach to construct confidence bands for a regression function with incomplete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 81-99, March.
    21. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
    22. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2008. "Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility," Journal of Econometrics, Elsevier, vol. 143(2), pages 227-262, April.
    23. Sun, Yan, 2017. "Estimation of single-index model with spatial interaction," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 36-45.
    24. Lijie Gu & Suojin Wang & Lijian Yang, 2019. "Simultaneous confidence bands for the distribution function of a finite population in stratified sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 983-1005, August.

  89. W. Härdle, 1987. "Resistant Smoothing Using the Fast Fourier Transform," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(1), pages 104-111, March.

    Cited by:

    1. Pinkse, Joris, 1998. "A consistent nonparametric test for serial independence," Journal of Econometrics, Elsevier, vol. 84(2), pages 205-231, June.
    2. Fernandez, J. M. Vilar & Manteiga, W. Gonzalez, 2000. "Resampling for checking linear regression models via non-parametric regression estimation," Computational Statistics & Data Analysis, Elsevier, vol. 35(2), pages 211-231, December.

  90. Härdle, Wolfgang, 1986. "Approximations to the mean integrated squared error with applications to optimal bandwidth selection for nonparametric regression function estimators," Journal of Multivariate Analysis, Elsevier, vol. 18(1), pages 150-168, February.

    Cited by:

    1. Kozek, A. S. & Yin, J., 2004. "On Gauss quadrature and partial cross validation," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 431-448, April.

  91. Wolfgang Härdle & Pham‐Dinh Tuan, 1986. "Some Theory On M‐Smoothing Of Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 191-204, May.

    Cited by:

    1. Bonsoo Koo & Oliver Linton, 2013. "Let's get LADE: robust estimation of semiparametric multiplicative volatility models," CeMMAP working papers 11/13, Institute for Fiscal Studies.

  92. Marron, James Stephen & Härdle, Wolfgang, 1986. "Random approximations to some measures of accuracy in nonparametric curve estimation," Journal of Multivariate Analysis, Elsevier, vol. 20(1), pages 91-113, October.

    Cited by:

    1. Estévez-Pérez, Graciela, 2002. "On convergence rates for quadratic errors in kernel hazard estimation," Statistics & Probability Letters, Elsevier, vol. 57(3), pages 231-241, April.
    2. Kozek, A. S. & Yin, J., 2004. "On Gauss quadrature and partial cross validation," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 431-448, April.
    3. Chacón, José E. & Rodríguez-Casal, Alberto, 2010. "A note on the universal consistency of the kernel distribution function estimator," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1414-1419, September.
    4. Wu, Colin O., 1997. "A Cross-Validation Bandwidth Choice for Kernel Density Estimates with Selection Biased Data," Journal of Multivariate Analysis, Elsevier, vol. 61(1), pages 38-60, April.
    5. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
    6. Timmermans, Catherine & Delsol, Laurent & von Sachs, Rainer, 2013. "Using Bagidis in nonparametric functional data analysis: Predicting from curves with sharp local features," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 421-444.
    7. Max Köhler & Anja Schindler & Stefan Sperlich, 2011. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 95, Courant Research Centre PEG.
    8. J. Vilar, 1995. "Kernel estimation of the regression function with random sampling times," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(1), pages 137-178, June.
    9. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.
    10. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2007. "Nonparametric Density Estimation for Multivariate Bounded Data," Cahiers de recherche 0732, CIRPEE.
    11. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    12. Dippon, J. & Fritz, P. & Kohler, M., 2002. "A statistical approach to case based reasoning, with application to breast cancer data," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 579-602, September.
    13. Élie Youndjé & Martin Wells, 2008. "Optimal bandwidth selection for multivariate kernel deconvolution density estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(1), pages 138-162, May.
    14. Daren Cline, 1990. "Optimal kernel estimation of densities," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 42(2), pages 287-303, June.
    15. Salim Bouzebda & Amel Nezzal & Tarek Zari, 2022. "Uniform Consistency for Functional Conditional U -Statistics Using Delta-Sequences," Mathematics, MDPI, vol. 11(1), pages 1-39, December.
    16. Aldo Goia & Philippe Vieu, 2015. "A partitioned Single Functional Index Model," Computational Statistics, Springer, vol. 30(3), pages 673-692, September.
    17. Sun, Liuquan, 1997. "Bandwidth choice for hazard rate estimators from left truncated and right censored data," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 101-114, December.
    18. K. Benhenni & F. Ferraty & M. Rachdi & P. Vieu, 2007. "Local smoothing regression with functional data," Computational Statistics, Springer, vol. 22(3), pages 353-369, September.
    19. Timmermans, Catherine & Delsol, Laurent & von Sachs, Rainer, 2011. "Using Bagidis in nonparametric functional data analysis: predicting from curves with sharp local features," LIDAM Discussion Papers ISBA 2011020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Sancetta, Alessio, 2013. "Weak conditions for shrinking multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 285-300.
    21. Ferreira García, María Eva & Núñez Antón, Vicente Alfredo & Rodríguez Poo, Juan M., 1999. "Two-Stage Nonparametric Regression for Longitudinal Data," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    22. Małgorzata Łazȩcka & Jan Mielniczuk, 2023. "Squared error-based shrinkage estimators of discrete probabilities and their application to variable selection," Statistical Papers, Springer, vol. 64(1), pages 41-72, February.
    23. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    24. Matthew D. Baird, 2014. "Cross Validation Bandwidth Selection for Derivatives of Multidimensional Densities," Working Papers WR-1060, RAND Corporation.

  93. Collomb, Gérard & Härdle, Wolfgang, 1986. "Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations," Stochastic Processes and their Applications, Elsevier, vol. 23(1), pages 77-89, October.

    Cited by:

    1. Burton Hollifield & Robert A. Miller & patrik Sandas, "undated". "An Empirical Analysis of Limit Order Markets," Rodney L. White Center for Financial Research Working Papers 29-99, Wharton School Rodney L. White Center for Financial Research.
    2. Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," LIDAM Discussion Papers CORE 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Lewbel, Arthur, 1995. "Consistent nonparametric hypothesis tests with an application to Slutsky symmetry," Journal of Econometrics, Elsevier, vol. 67(2), pages 379-401, June.
    4. Holger Dette & Regine Scheder, 2011. "Estimation of additive quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 245-265, April.
    5. Lee, Myoung-jae & Vella, Francis, 2006. "A semi-parametric estimator for censored selection models with endogeneity," Journal of Econometrics, Elsevier, vol. 130(2), pages 235-252, February.
    6. Franke, Jürgen & Kreiss, Jens-Peter & Mammen, Enno, 1997. "Bootstrap of kernel smoothing in nonlinear time series," SFB 373 Discussion Papers 1997,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Zhu, Xuehu & Chen, Fei & Guo, Xu & Zhu, Lixing, 2016. "Heteroscedasticity testing for regression models: A dimension reduction-based model adaptive approach," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 263-283.
    8. Jürgen Franke & Peter Mwita & Weining Wang, 2015. "Nonparametric estimates for conditional quantiles of time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(1), pages 107-130, January.
    9. Arthur Lewbel, 2000. "Asymptotic Trimming for Bounded Density Plug-in Estimators," Boston College Working Papers in Economics 479, Boston College Department of Economics, revised 30 Oct 2000.
    10. Aradillas-Lopez, Andres, 2010. "Semiparametric estimation of a simultaneous game with incomplete information," Journal of Econometrics, Elsevier, vol. 157(2), pages 409-431, August.
    11. Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation for Research in Economics, Yale University.
    12. Azzedine, Nadjia & Laksaci, Ali & Ould-Saïd, Elias, 2008. "On robust nonparametric regression estimation for a functional regressor," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3216-3221, December.
    13. Donkers, A.C.D. & Schafgans, M., 2003. "A Derivative Based Estimator for Semiparametric Index Models," Discussion Paper 2003-22, Tilburg University, Center for Economic Research.
    14. Scheder, Regine & Dette, Holger, 2005. "Strictly monotone and smooth nonparametric regression for two or more variables," Technical Reports 2005,17, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    15. Stoker, Thomas M., 1987. "Equivalence of direct and indirect estimators of average derivatives," Working papers 1961-87., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    16. Saliha Derrar & Ali Laksaci & Elias Ould Saïd, 2020. "M-estimation of the regression function under random left truncation and functional time series model," Statistical Papers, Springer, vol. 61(3), pages 1181-1202, June.
    17. Boente, Graciela & Vahnovan, Alejandra, 2015. "Strong convergence of robust equivariant nonparametric functional regression estimators," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 1-11.
    18. Masry, Elias, 1996. "Multivariate regression estimation local polynomial fitting for time series," Stochastic Processes and their Applications, Elsevier, vol. 65(1), pages 81-101, December.
    19. Néstor Aguilera & Liliana Forzani & Pedro Morin, 2011. "On uniform consistent estimators for convex regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 897-908.
    20. Dette, Holger & von Lieres und Wilkau, Carsten & Sperlich, Stefan, 2001. "A comparison of different nonparametric methods for inference on additive models," Technical Reports 2001,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    21. Joseph Ngatchou-Wandji & Marwa Ltaifa & Didier Alain Njamen Njomen & Jia Shen, 2022. "Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    22. Zeng, Peng & Zhu, Yu, 2010. "An integral transform method for estimating the central mean and central subspaces," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 271-290, January.
    23. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.
    24. Cai, Zongwu & Ould-Saïd, Elias, 2003. "Local M-estimator for nonparametric time series," Statistics & Probability Letters, Elsevier, vol. 65(4), pages 433-449, December.
    25. Zhou, Yong & Liang, Hua, 2000. "Asymptotic Normality for L1 Norm Kernel Estimator of Conditional Median under [alpha]-Mixing Dependence," Journal of Multivariate Analysis, Elsevier, vol. 73(1), pages 136-154, April.
    26. Xue, Sen & Yang, Thomas Tao & Zhou, Qiankun, 2018. "Binary choice model with interactive effects," Economic Modelling, Elsevier, vol. 70(C), pages 338-350.
    27. Omar Fetitah & Mohammed Kadi Attouch & Salah Khardani & Ali Righi, 2023. "Robust nonparametric equivariant regression for functional data with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 899-929, November.
    28. Peter C.B. Phillips & Joon Y. Park, 1998. "Nonstationary Density Estimation and Kernel Autoregression," Cowles Foundation Discussion Papers 1181, Cowles Foundation for Research in Economics, Yale University.
    29. Mohamed Lemdani & Elias Ould Saïd, 2017. "Nonparametric robust regression estimation for censored data," Statistical Papers, Springer, vol. 58(2), pages 505-525, June.

  94. Härdle, Wolfgang, 1984. "Robust regression function estimation," Journal of Multivariate Analysis, Elsevier, vol. 14(2), pages 169-180, April.

    Cited by:

    1. Lee, Myoung-jae & Melenberg, Bertrand, 1998. "Bounding quantiles in sample selection models," Economics Letters, Elsevier, vol. 61(1), pages 29-35, October.
    2. Robinson, P. M., 1995. "The approximate distribution of nonparametric regression estimates," Statistics & Probability Letters, Elsevier, vol. 23(2), pages 193-201, May.
    3. Guillermo Henry & Daniela Rodriguez, 2009. "Robust nonparametric regression on Riemannian manifolds," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(5), pages 611-628.
    4. Chen, Jia & Li, Degui & Zhang, Lixin, 2010. "Robust estimation in a nonlinear cointegration model," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 706-717, March.
    5. Bianco, Ana M. & Spano, Paula M., 2017. "Robust estimation in partially linear errors-in-variables models," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 46-64.
    6. Bianco, Ana M. & Boente, Graciela & Sombielle, Susana, 2011. "Robust estimation for nonparametric generalized regression," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1986-1994.
    7. Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 1999. "Nonparametric Bounds on the Income Distribution in the Presence of Item Nonresponse," Discussion Paper 1999-33, Tilburg University, Center for Economic Research.
    8. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.
    10. Omar Fetitah & Mohammed Kadi Attouch & Salah Khardani & Ali Righi, 2023. "Robust nonparametric equivariant regression for functional data with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 899-929, November.

  95. Matthias R. Fengler & Wolfgang K. Härdle & Enno Mammen, 0. "A semiparametric factor model for implied volatility surface dynamics," Journal of Financial Econometrics, Oxford University Press, vol. 5(2), pages 189-218.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. Enno Mammen & Byeong U. Park & Melanie Schienle, 2012. "Additive Models: Extensions and Related Models," SFB 649 Discussion Papers SFB649DP2012-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Barbara Choroś-Tomczyk & Wolfgang Karl Härdle & Ostap Okhrin, 2013. "CDO Surfaces Dynamics," SFB 649 Discussion Papers SFB649DP2013-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Georgios Chalamandaris & Andrianos Tsekrekos, 2013. "Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian–Pacific Currency Options," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 327-358, March.
    5. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," Papers 1106.3915, arXiv.org.
    6. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    7. Bastien Baldacci, 2020. "High-frequency dynamics of the implied volatility surface," Papers 2012.10875, arXiv.org.
    8. Enzo Giacomini & Wolfgang Härdle & Volker Krätschmer, 2008. "Dynamic Semiparametric Factor Models in Risk Neutral Density Estimation," SFB 649 Discussion Papers SFB649DP2008-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    11. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.
    12. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Oliver Linton & Jens Perch Nielsen & Søren Feodor Nielsen, 2009. "Non-parametric regression with a latent time series," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 187-207, July.
    14. Song Song & Wolfgang K. Härdle & Ya'acov Ritov, 2010. "High Dimensional Nonstationary Time Series Modelling with Generalized Dynamic Semiparametric Factor Model," SFB 649 Discussion Papers SFB649DP2010-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Borak, Szymon & Weron, Rafal, 2008. "A semiparametric factor model for electricity forward curve dynamics," MPRA Paper 10421, University Library of Munich, Germany.
    16. Jan Maruhn & Morten Nalholm & Matthias Fengler, 2011. "Static hedges for reverse barrier options with robustness against skew risk: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, vol. 11(5), pages 711-727.
    17. Bernd Engelmann & Matthias Fengler & Morten Nalholm & Peter Schwendner, 2006. "Static versus dynamic hedges: an empirical comparison for barrier options," Review of Derivatives Research, Springer, vol. 9(3), pages 239-264, November.
    18. Ulze, Markus & Stadler, Johannes & Rathgeber, Andreas W., 2021. "No country for old distributions? On the comparison of implied option parameters between the Brownian motion and variance gamma process," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 163-184.
    19. Wolfgang Karl Hardle & Elena Silyakova, 2020. "Implied Basket Correlation Dynamics," Papers 2009.09770, arXiv.org.
    20. Alejandro Bernales & Massimo Guidolin, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Working Papers 565, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    21. Francesco Audrino & Dominik Colangelo, 2009. "Option trading strategies based on semi-parametric implied volatility surface prediction," University of St. Gallen Department of Economics working paper series 2009 2009-24, Department of Economics, University of St. Gallen.
    22. Francesco Audrino & Dominik Colagelo, 2007. "Forecasting Implied Volatility Surfaces," University of St. Gallen Department of Economics working paper series 2007 2007-42, Department of Economics, University of St. Gallen.
    23. Härdle Wolfgang Karl & Silyakova Elena, 2016. "Implied basket correlation dynamics," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 1-20, September.
    24. Enzo Giacomini & Wolfgang Härdle, 2007. "Statistics of Risk Aversion," SFB 649 Discussion Papers SFB649DP2007-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    25. Taboga, Marco, 2016. "Option-implied probability distributions: How reliable? How jagged?," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 453-469.
    26. Fengler, Matthias & Hin, Lin-Yee, 2011. "Semi-nonparametric estimation of the call price surface under strike and time-to-expiry no-arbitrage constraints," Economics Working Paper Series 1136, University of St. Gallen, School of Economics and Political Science, revised May 2013.
    27. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    28. Wenyong Zhang & Lingfei Li & Gongqiu Zhang, 2021. "A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface," Papers 2106.07177, arXiv.org, revised Jan 2022.
    29. Fengler, Matthias R. & Hin, Lin-Yee, 2015. "Semi-nonparametric estimation of the call-option price surface under strike and time-to-expiry no-arbitrage constraints," Journal of Econometrics, Elsevier, vol. 184(2), pages 242-261.
    30. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
    31. Da Fonseca, José & Gottschalk, Katrin, 2014. "Cross-hedging strategies between CDS spreads and option volatility during crises," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 386-400.
    32. Yaxiong Zeng & Diego Klabjan, 2017. "Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling," Papers 1706.01833, arXiv.org, revised Jun 2018.
    33. Likai Chen & Weining Wang & Wei Biao Wu, 2017. "Dynamic Semiparametric Factor Model with a Common Break," SFB 649 Discussion Papers SFB649DP2017-026, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    34. Stefan Trück & Wolfgang Härdle & Rafal Weron, 2012. "The relationship between spot and futures CO2 emission allowance prices in the EU-ETS," HSC Research Reports HSC/12/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    35. Wolfgang Karl Härdle & Elena Silyakova, 2012. "Implied Basket Correlation Dynamics," SFB 649 Discussion Papers SFB649DP2012-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    36. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    37. Ostap Okhrin & Stefan Trück, 2015. "Editorial to the special issue on Applicable semiparametrics of computational statistics," Computational Statistics, Springer, vol. 30(3), pages 641-646, September.
    38. Wallmeier, Martin, 2012. "Smile in Motion: An Intraday Analysis of Asymmetric Implied Volatility," FSES Working Papers 427, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

Software components

    Sorry, no citations of software components recorded.

Chapters

  1. Bruno Spilak & Wolfgang Karl Härdle, 2022. "Tail-Risk Protection: Machine Learning Meets Modern Econometrics," Springer Books, in: Cheng-Few Lee & Alice C. Lee (ed.), Encyclopedia of Finance, edition 0, chapter 92, pages 2177-2211, Springer.
    See citations under working paper version above.
  2. Enzo Giacomini & Michael Handel & Wolfgang K. Härdle, 2009. "Time Dependent Relative Risk Aversion," Contributions to Economics, in: Georg Bol & Svetlozar T. Rachev & Reinhold Würth (ed.), Risk Assessment, pages 15-46, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Pavel Cizek & Wolfgang Karl Härdle & Rafal Weron, 2011. "Statistical Tools for Finance and Insurance (2nd edition)," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook1101.

    Cited by:

    1. Michael Kurz, 2018. "Closed-form approximations in derivatives pricing: The Kristensen-Mele approach," Papers 1804.08904, arXiv.org.
    2. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Constrained Kelly portfolios under alpha-stable laws," IRTG 1792 Discussion Papers 2019-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    4. Niels Wesselhöfft & Wolfgang K. Härdle, 2020. "Risk-Constrained Kelly Portfolios Under Alpha-Stable Laws," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 801-826, March.
    5. Denis-Alexandre Trottier & Van Son Lai & Anne-Sophie Charest, 2017. "CAT Bond Spreads Via HARA Utility and Nonparametric Tests," Working Papers 2017-002, Department of Research, Ipag Business School.
    6. Philipp Gschöpf & Wolfgang Karl Härdle & Andrija Mihoci, 2015. "TERES - Tail Event Risk Expectile based Shortfall," SFB 649 Discussion Papers SFB649DP2015-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Javed, Farrukh & Loperfido, Nicola & Mazur, Stepan, 2020. "Edgeworth Expansions for Multivariate Random Sums," Working Papers 2020:9, Örebro University, School of Business.
    8. Kucharczyk, Daniel & Wyłomańska, Agnieszka & Zimroz, Radosław, 2017. "Structural break detection method based on the Adaptive Regression Splines technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 499-511.
    9. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    10. Tsyganov, Aleksander & Baskakov, Valery & Yazykov, Andrey & Sheparnev, Nikolay & Yanenko, Evgeny & Grysenkova, Yulia, 2019. "The impact of the bonus-malus system on the insurance ratemaking in the system of compulsory insurance of the responsibility of transport owners in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 123-141.
    11. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT Calibration of the Heston Model," Mathematics, MDPI, vol. 9(5), pages 1-20, March.
    12. Lenkšas, A. & Mackevičius, V., 2015. "Weak approximation of Heston model by discrete random variables," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 113(C), pages 1-15.
    13. J. Martin van Zyl, 2018. "An Empirical Study of the Behaviour of the Sample Kurtosis in Samples from Symmetric Stable Distributions," Papers 1811.00476, arXiv.org, revised Nov 2018.
    14. Claudio Fontana & Alessandro Gnoatto & Guillaume Szulda, 2021. "CBI-time-changed Lévy processes for multi-currency modeling," Working Papers 14/2021, University of Verona, Department of Economics.
    15. Royuela-del-Val, Javier & Simmross-Wattenberg, Federico & Alberola-López, Carlos, 2017. "libstable: Fast, Parallel, and High-Precision Computation of α-Stable Distributions in R, C/C++, and MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i01).
    16. Sergey Nasekin & Wolfgang Karl Hardle, 2020. "Model-driven statistical arbitrage on LETF option markets," Papers 2009.09713, arXiv.org.
    17. Alexander Lipton, 2024. "Hydrodynamics of Markets:Hidden Links Between Physics and Finance," Papers 2403.09761, arXiv.org.
    18. Krzysztof Burnecki & Zbigniew Palmowski & Marek Teuerle & Aleksandra Wilkowska, 2023. "Ruin probability for the quota share model with~phase-type distributed claims," Papers 2303.07705, arXiv.org.
    19. Omar El Euch & Mathieu Rosenbaum, 2016. "The characteristic function of rough Heston models," Papers 1609.02108, arXiv.org.

  2. Pavel Cizek & Wolfgang Karl Härdle & Rafal Weron, 2005. "Statistical Tools for Finance and Insurance," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0501.

    Cited by:

    1. Burnecki, Krzysztof & Weron, Rafal, 2010. "Simulation of Risk Processes," MPRA Paper 25444, University Library of Munich, Germany.
      • Härdle, Wolfgang Karl & Burnecki, Krzysztof & Weron, Rafał, 2004. "Simulation of risk processes," Papers 2004,01, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    2. Cui, Yiran & del Baño Rollin, Sebastian & Germano, Guido, 2017. "Full and fast calibration of the Heston stochastic volatility model," European Journal of Operational Research, Elsevier, vol. 263(2), pages 625-638.
    3. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    4. Alexander Lipton & Andrey Gal & Andris Lasis, 2013. "Pricing of vanilla and first generation exotic options in the local stochastic volatility framework: survey and new results," Papers 1312.5693, arXiv.org.
    5. Rafal Weron, 2005. "Market price of risk implied by Asian-style electricity options," Econometrics 0502003, University Library of Munich, Germany.
    6. Jentsch, Carsten & Leucht, Anne & Meyer, Marco & Beering, Carina, 2016. "Empirical characteristic functions-based estimation and distance correlation for locally stationary processes," Working Papers 16-15, University of Mannheim, Department of Economics.
    7. Maria Mercè Claramunt & Maite Màrmol, 2020. "Refundable deductible insurance," Working Papers hal-02909299, HAL.
    8. Arkadiusz Filip & Marcin Wienke, 2013. "Odporność składki kwantylowej ze względu na zaburzenia rozkładu wielkości pojedynczej szkody w modelu ryzyka łącznego," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 31, pages 137-155.
    9. Weron, Rafał & Burnecki, Krzysztof, 2004. "Modeling the risk process in the XploRe computing environment," Papers 2004,08, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    10. Sebastien TERRA, 2009. "Zipf's Law for Cities: On a New Testing Procedure," Working Papers 200920, CERDI.
    11. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    12. Cizek, P. & Tamine, J. & Härdle, W.K., 2006. "Smoothed L-estimation of Regression Function," Discussion Paper 2006-20, Tilburg University, Center for Economic Research.
    13. Krzysztof Burnecki & Joanna Janczura & Rafał Weron, 2010. "Building Loss Models," SFB 649 Discussion Papers SFB649DP2010-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Michal Benko & Wolfgang Härdle & Alois Kneip, 2006. "Common Functional Principal Components," SFB 649 Discussion Papers SFB649DP2006-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(3), pages 239-270, July.
    16. Kita-Wojciechowska Kinga & Kidziński Łukasz, 2019. "Google Street View image predicts car accident risk," Central European Economic Journal, Sciendo, vol. 6(53), pages 151-163, January.
    17. Ma, Zong-Gang & Ma, Chao-Qun, 2013. "Pricing catastrophe risk bonds: A mixed approximation method," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 243-254.
    18. Frisén, Marianne, 2008. "Introduction to financial surveillance," Research Reports 2008:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    19. Dassios, Angelos & Qu, Yan & Zhao, Hongbiao, 2018. "Exact simulation for a class of tempered stable," LSE Research Online Documents on Economics 86981, London School of Economics and Political Science, LSE Library.
    20. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    21. Janczura, Joanna & Weron, Rafal, 2011. "Black swans or dragon kings? A simple test for deviations from the power law," MPRA Paper 28959, University Library of Munich, Germany.
    22. Ana Preda & Mirela Monea & Lorand Bogdanffy, 2016. "Simulation Insured Results by Purchasing a Life Insurance," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 16(2), pages 109-116.
    23. Broda, Simon A. & Krause, Jochen & Paolella, Marc S., 2018. "Approximating expected shortfall for heavy-tailed distributions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 184-203.
    24. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    25. Dufour, Jean-Marie & Kurz-Kim, Jeong-Ryeol, 2010. "Exact inference and optimal invariant estimation for the stability parameter of symmetric [alpha]-stable distributions," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 180-194, March.
    26. Michele Leonardo Bianchi & Gian Luca Tassinari & Frank J. Fabozzi, 2016. "Riding With The Four Horsemen And The Multivariate Normal Tempered Stable Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pages 1-28, June.
    27. Raquel BARREIRA & Tristan PRYER & Qi TANG, 2009. "A Practical Approach To Model Banking Risks Using Loss Distribution Approach (Lda) In Basel Ii Framework," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(4(10)_Win), pages 483-493.
    28. Dobrislav Dobrev & Travis D. Nesmith & Dong Hwan Oh, 2016. "Accurate Evaluation of Expected Shortfall for Linear Portfolios with Elliptically Distributed Risk Factors," Finance and Economics Discussion Series 2016-065, Board of Governors of the Federal Reserve System (U.S.).
    29. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2005. "Integrable e-lements for Statistics Education," SFB 649 Discussion Papers SFB649DP2005-058, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Brahimi, Brahim & Abdelli, Jihane, 2016. "Estimating the distortion parameter of the proportional hazards premium for heavy-tailed losses under Lévy-stable regime," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 135-143.
    31. Dila Puspita & Adam Kolkiewicz & Ken Seng Tan, 2020. "Discrete Time Ruin Probability for Takaful (Islamic Insurance) with Investment and Qard-Hasan (Benevolent Loan) Activities," JRFM, MDPI, vol. 13(9), pages 1-24, September.
    32. Eudald Romo & Luis Ortiz-Gracia, 2021. "SWIFT calibration of the Heston model," Papers 2103.01570, arXiv.org.
    33. Mariana Hatmanu & Cristina Cautisanu & Mihaela Ifrim, 2020. "The Impact of Interest Rate, Exchange Rate and European Business Climate on Economic Growth in Romania: An ARDL Approach with Structural Breaks," Sustainability, MDPI, vol. 12(7), pages 1-23, April.
    34. Michal Benko & Alois Kneip, 2005. "Common functional component modelling," SFB 649 Discussion Papers SFB649DP2005-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    35. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    36. Songkomkrit Chaiyakan & Phantipa Thipwiwatpotjana, 2021. "Bounds on mean absolute deviation portfolios under interval-valued expected future asset returns," Computational Management Science, Springer, vol. 18(2), pages 195-212, June.
    37. J. M. Vilar & R. Cao & M. C. Ausin & C. Gonzalez-Fragueiro, 2009. "Nonparametric analysis of aggregate loss models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(2), pages 149-166.
    38. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    39. Kiss, Gábor Dávid & Kosztopulosz, Andreász, 2012. "The impact of the crisis on the monetary autonomy of Central and Eastern European countries," Public Finance Quarterly, Corvinus University of Budapest, vol. 57(1), pages 28-52.
    40. Agnieszka Janek & Tino Kluge & Rafał Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," SFB 649 Discussion Papers SFB649DP2010-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    41. Liang, Yingjie & Chen, Wen, 2015. "A cumulative entropy method for distribution recognition of model error," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 729-735.
    42. Weron, Rafał, 2004. "Computationally intensive Value at Risk calculations," Papers 2004,32, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    43. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models or electricity spot prices," MPRA Paper 20546, University Library of Munich, Germany.
    44. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
    45. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 225-239.
    46. Jan-Henning Trustorff & Paul Konrad & Jens Leker, 2011. "Credit risk prediction using support vector machines," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 565-581, May.
    47. Chen, Ying & Härdle, Wolfgang & Spokoiny, Vladimir, 2010. "GHICA -- Risk analysis with GH distributions and independent components," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 255-269, March.
    48. Climent Hernández José Antonio & Venegas Martínez Francisco, 2013. "Valuación de opciones sobre subyacentes con rendimientos a-estables," Contaduría y Administración, Accounting and Management, vol. 58(4), pages 119-150, octubre-d.
    49. Wolfgang Härdle & Sigbert Klinke & Uwe Ziegenhagen, 2006. "e-Learning Statistics - A Selective Review," SFB 649 Discussion Papers SFB649DP2006-024, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    50. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    51. Alessandro Gnoatto & Martino Grasselli, 2013. "An analytic multi-currency model with stochastic volatility and stochastic interest rates," Papers 1302.7246, arXiv.org, revised Mar 2013.
    52. Joanna Janczura & Rafal Weron, 2012. "Inference for Markov-regime switching models of electricity spot prices," HSC Research Reports HSC/12/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    53. Alessandro Gnoatto, 2017. "Coherent Foreign Exchange Market Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-29, February.
    54. Ana Preda & Gheorghe Matei & Lorand Bogdanffy, 2016. "The Prognosis of the Main Indicators for Sizing the Global Insurance Market," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 16(2), pages 101-108.
    55. Sebastian, Orzeł & Agnieszka, Wyłomańska, 2010. "Calibration of the subdiffusive arithmetic Brownian motion with tempered stable waiting-times," MPRA Paper 28593, University Library of Munich, Germany.
    56. Wylomanska-, Agnieszka, 2010. "Measures of dependence for Ornstein-Uhlenbeck processes with tempered stable distribution," MPRA Paper 28535, University Library of Munich, Germany, revised 2010.
    57. Anna Chernobai & Krzysztof Burnecki & Svetlozar Rachev & Stefan Trueck & Rafal Weron, 2005. "Modeling catastrophe claims with left-truncated severity distributions (extended version)," HSC Research Reports HSC/05/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    58. Anna Chernobai & Krzysztof Burnecki & Svetlozar Rachev & Stefan Trück & Rafał Weron, 2006. "Modelling catastrophe claims with left-truncated severity distributions," Computational Statistics, Springer, vol. 21(3), pages 537-555, December.
    59. Adam Misiorek & Rafal Weron, 2010. "Heavy-tailed distributions in VaR calculations," HSC Research Reports HSC/10/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    60. Wyłomańska, Agnieszka & Chechkin, Aleksei & Gajda, Janusz & Sokolov, Igor M., 2015. "Codifference as a practical tool to measure interdependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 412-429.
    61. Kai Detlefsen & Wolfgang Härdle & Rouslan Moro, 2007. "Empirical Pricing Kernels and Investor Preferences," SFB 649 Discussion Papers SFB649DP2007-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    62. Leif Andersen & Alexander Lipton, 2013. "Asymptotics For Exponential Lévy Processes And Their Volatility Smile: Survey And New Results," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-98.
    63. Pawel Mista, 2006. "Analytical and numerical approach to corporate operational risk modelling," HSC Research Reports HSC/06/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    64. Janczura, Joanna & Weron, Rafal, 2011. "Goodness-of-fit testing for the marginal distribution of regime-switching models," MPRA Paper 32532, University Library of Munich, Germany.
    65. Taisei Kaizoji & Michiko Miyano, 2017. "Zipf's law for share price and company fundamentals," Papers 1702.00144, arXiv.org.
    66. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    67. Têtu Alexandre & Lai Van Son & Soumaré Issouf & Gendron Michel, 2015. "Hedging Flood Losses Using Cat Bonds," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 149-184, July.
    68. Marcin Pitera & Aleksei Chechkin & Agnieszka Wyłomańska, 2022. "Goodness-of-fit test for $$\alpha$$ α -stable distribution based on the quantile conditional variance statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 387-424, June.
    69. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    70. Gajda, Janusz & Bartnicki, Grzegorz & Burnecki, Krzysztof, 2018. "Modeling of water usage by means of ARFIMA–GARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 644-657.
    71. Abbasi, B. & Hosseinifard, S.Z. & Coit, D.W., 2010. "A neural network applied to estimate Burr XII distribution parameters," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 647-654.
    72. Leif Andersen & Alexander Lipton, 2012. "Asymptotics for Exponential Levy Processes and their Volatility Smile: Survey and New Results," Papers 1206.6787, arXiv.org.
    73. Han Lin Shang, 2011. "A survey of functional principal component analysis," Monash Econometrics and Business Statistics Working Papers 6/11, Monash University, Department of Econometrics and Business Statistics.
    74. Vyacheslav Gorovoy & Vadim Linetsky, 2007. "Intensity‐Based Valuation Of Residential Mortgages: An Analytically Tractable Model," Mathematical Finance, Wiley Blackwell, vol. 17(4), pages 541-573, October.
    75. Fred Espen Benth & Jūratė Šaltytė Benth, 2012. "Modeling and Pricing in Financial Markets for Weather Derivatives," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8457, January.
    76. Tan, Ken Seng & Wei, Pengyu & Wei, Wei & Zhuang, Sheng Chao, 2020. "Optimal dynamic reinsurance policies under a generalized Denneberg’s absolute deviation principle," European Journal of Operational Research, Elsevier, vol. 282(1), pages 345-362.
    77. Burnecki, Krzysztof & Misiorek, Adam & Weron, Rafal, 2010. "Loss Distributions," MPRA Paper 22163, University Library of Munich, Germany.
    78. Burnecki, Krzysztof & Gajda, Janusz & Sikora, Grzegorz, 2011. "Stability and lack of memory of the returns of the Hang Seng index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(18), pages 3136-3146.
    79. Climent-Hernández, José Antonio & Venegas-Martínez, Francisco & Ortiz-Arango, Francisco, 2014. "Portafolio óptimo y productos estructurados en mercados alpha-estables: un enfoque de minimización de riesgo [Optimal Portfolio and Structured Notes in alpha-stable Markets: a Risk Minimization App," MPRA Paper 57740, University Library of Munich, Germany.
    80. Janczura, Joanna & Orzeł, Sebastian & Wyłomańska, Agnieszka, 2011. "Subordinated α-stable Ornstein–Uhlenbeck process as a tool for financial data description," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4379-4387.
    81. Ole E. Barndorff-Nielsen & Fred Espen Benth & Almut E. D. Veraart, 2013. "Modelling energy spot prices by volatility modulated L\'{e}vy-driven Volterra processes," Papers 1307.6332, arXiv.org.
    82. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    83. Denecke, Liesa & Müller, Christine H., 2011. "Robust estimators and tests for bivariate copulas based on likelihood depth," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2724-2738, September.
    84. Szymon Borak & Matthias Fengler & Wolfgang Härdle, 2005. "DSFM fitting of Implied Volatility Surfaces," SFB 649 Discussion Papers SFB649DP2005-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    85. Ying Chen & Wolfgang Härdle & Vladimir Spokoiny, 2006. "GHICA - Risk Analysis with GH Distributions and Independent Components," SFB 649 Discussion Papers SFB649DP2006-078, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    86. Bernardi, Mauro & Maruotti, Antonello & Petrella, Lea, 2012. "Skew mixture models for loss distributions: A Bayesian approach," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 617-623.
    87. Marcin Rudź, 2015. "A method of calculating exact ruin probabilities in discrete time models," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 37, pages 307-322.
    88. Zbigniew Michna & Aleksander Weron, 2007. "Asymptotic behavior of the finite time ruin probability of a gamma Levy process," HSC Research Reports HSC/07/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    89. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

  3. Härdle,Wolfgang, 1992. "Applied Nonparametric Regression," Cambridge Books, Cambridge University Press, number 9780521429504.

    Cited by:

    1. Ashis K. Gangopadhyay & Robert disario & Dipak K. Dey, 1997. "A nonparametric approach to k-sample inference based on entropy-super-," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 8(3), pages 237-252, September.
    2. Aedo, Cristían & Nuñez, Sergio, 2004. "The Impact of Training Policies in Latin America and the Caribbean: The Case of Programa Joven," IDB Publications (Working Papers) 3287, Inter-American Development Bank.
    3. Gabor Nagy & Gergo Barta & Tamas Henk, 2015. "Portfolio optimization using local linear regression ensembles in RapidMiner," Papers 1506.08690, arXiv.org.
    4. Lionel Page & Robert T. Clemen, 2013. "Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-," Economic Journal, Royal Economic Society, vol. 123(568), pages 491-513, May.
    5. Susumu Imai & Neelam Jain, 2005. "Bayesian Estimation of Dynamic Discrete Choice Models," 2005 Meeting Papers 432, Society for Economic Dynamics.
    6. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    7. Cristian Aedo, "undated". "The Impact of Training Policies in Latin America and the Caribbean: The Case of "Programa Joven"," ILADES-UAH Working Papers inv131, Universidad Alberto Hurtado/School of Economics and Business.
    8. Dorn, Sabrina & Egger, Peter, 2012. "On the Distribution of Exchange Rate Regime Treatment Effects on International Trade," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62054, Verein für Socialpolitik / German Economic Association.
    9. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    10. Dora L. Costa & Matthew E. Kahn, 2004. "Changes in the Value of Life, 1940--1980," Journal of Risk and Uncertainty, Springer, vol. 29(2), pages 159-180, September.
    11. Fortin, Nicole M., 1997. "L’impact des règles de prêts hypothécaires sur l’offre de travail des femmes au Canada : évidence paramétrique et non paramétrique," L'Actualité Economique, Société Canadienne de Science Economique, vol. 73(1), pages 129-159, mars-juin.
    12. Marco Modica, 2014. "Does the EU have homogeneous urban structure area? The role of agglomeration and the impact of shocks on urban structure," ERSA conference papers ersa14p229, European Regional Science Association.
    13. Cristian Aedo & Sergio Nuñez, 2004. "Efectos de las políticas de capacitación en América Latina y el Caribe: el caso del Programa Joven," Research Department Publications 3176, Inter-American Development Bank, Research Department.
    14. Jan Eeckhout, 2004. "Gibrat's Law for (All) Cities," American Economic Review, American Economic Association, vol. 94(5), pages 1429-1451, December.
    15. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.
    16. Jaromír Kukal & Tran Van Quang, 2014. "Neparametrický heuristický přístup k odhadu modelu GARCH-M a jeho výhody [Estimating a GARCH-M Model by a Non-Parametric Heuristic Method and Its Advantages]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 100-116.
    17. Emre Barut & Warren Powell, 2014. "Optimal learning for sequential sampling with non-parametric beliefs," Journal of Global Optimization, Springer, vol. 58(3), pages 517-543, March.
    18. Noyan Aydin Taner Akmercan, 2016. "Forecasting of Households Consumption Expenditure with Nonparametric Regression: The Case of Turkey," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 19(2), pages 19-32, November.
    19. Rama CONT, 1998. "Beyond implied volatility: extracting information from option prices," Finance 9804002, University Library of Munich, Germany.
    20. B. Wade Brorsen & John Coombs & Kim Anderson, 1995. "The cost of forward contracting wheat," Agribusiness, John Wiley & Sons, Ltd., vol. 11(4), pages 349-354.
    21. Cristian Aedo & Sergio Nuñez, 2004. "The Impact of Training Policies in Latin America and the Caribbean: The Case of Programa Joven," Research Department Publications 3175, Inter-American Development Bank, Research Department.
    22. Mangalova, Ekaterina & Shesterneva, Olesya, 2016. "Sequence of nonparametric models for GEFCom2014 probabilistic electric load forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1023-1028.
    23. D. K. Ginther, "undated". "A nonparametric analysis of the U.S. earnings distribution," Institute for Research on Poverty Discussion Papers 1067-95, University of Wisconsin Institute for Research on Poverty.
    24. Čížek, Pavel, 2004. "(Non) Linear Regression Modeling," Papers 2004,11, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.