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Christian Matthias Hafner

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.

Working papers

  1. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Janeway Institute Working Papers 2206, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bachmair, K., 2023. "The Effects of the LIBOR Scandal on Volatility and Liquidity in LIBOR Futures Markets," Cambridge Working Papers in Economics 2303, Faculty of Economics, University of Cambridge.

  2. Hafner, Christian, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," LIDAM Reprints ISBA 2020031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Li, Shaoran & Linton, Oliver, 2021. "When will the Covid-19 pandemic peak?," Journal of Econometrics, Elsevier, vol. 220(1), pages 130-157.
    2. Zhangbo Yang & Jiahao Zhang & Shanxing Gao & Hui Wang, 2022. "Complex Contact Network of Patients at the Beginning of an Epidemic Outbreak: An Analysis Based on 1218 COVID-19 Cases in China," IJERPH, MDPI, vol. 19(2), pages 1-17, January.
    3. Sergio A. Chillon & Mikel Millan & Iñigo Aramendia & Unai Fernandez-Gamiz & Ekaitz Zulueta & Xabier Mendaza-Sagastizabal, 2021. "Natural Ventilation Characterization in a Classroom under Different Scenarios," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
    4. Ewen Gallic & Michel Lubrano & Pierre Michel, 2021. "Optimal lockdowns: Analysing the efficiency of sanitary policies in Europe during the first wave," Working Papers halshs-03145861, HAL.
    5. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2020. "Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis," IJERPH, MDPI, vol. 17(18), pages 1-35, September.
    6. Monika Małgorzata Wojcieszak-Zbierska & Anna Jęczmyk & Jan Zawadka & Jarosław Uglis, 2020. "Agritourism in the Era of the Coronavirus (COVID-19): A Rapid Assessment from Poland," Agriculture, MDPI, vol. 10(9), pages 1-19, September.
    7. Amanda M. Y. Chu & Thomas W. C. Chan & Mike K. P. So & Wing-Keung Wong, 2021. "Dynamic Network Analysis of COVID-19 with a Latent Pandemic Space Model," IJERPH, MDPI, vol. 18(6), pages 1-22, March.
    8. Samuel Domínguez-Amarillo & Jesica Fernández-Agüera & Sonia Cesteros-García & Roberto Alonso González-Lezcano, 2020. "Bad Air Can Also Kill: Residential Indoor Air Quality and Pollutant Exposure Risk during the COVID-19 Crisis," IJERPH, MDPI, vol. 17(19), pages 1-33, September.
    9. Anna Gloria Billé & Massimiliano Caporin, 2022. "Impact of COVID-19 on financial returns: a spatial dynamic panel data model with random effects," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-21, December.

  3. Chen, Cathy Yi-Hsuan & Hafner, Christian, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," LIDAM Reprints ISBA 2019053, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. 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).
    2. Luca Mungo & Silvia Bartolucci & Laura Alessandretti, 2023. "Cryptocurrency co-investment network: token returns reflect investment patterns," Papers 2301.02027, arXiv.org, revised Jan 2023.
    3. Shigeyuki Hamori, 2020. "Recent Advancements in Section “Financial Technology and Innovation”," JRFM, MDPI, vol. 13(12), pages 1-2, December.
    4. Silvia Bartolucci & Fabio Caccioli & Pierpaolo Vivo, 2019. "A percolation model for the emergence of the Bitcoin Lightning Network," Papers 1912.03556, arXiv.org.
    5. Ozkan Haykir & Ibrahim Yagli, 2022. "Speculative bubbles and herding in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-33, December.
    6. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    7. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    8. 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).
    9. Kumar, Anoop S & Padakandla, Steven Raj, 2023. "Do NFTs act as a good hedge and safe haven against Cryptocurrency fluctuations?," Finance Research Letters, Elsevier, vol. 56(C).
    10. 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.
    11. Ramit Sawhney & Shivam Agarwal & Vivek Mittal & Paolo Rosso & Vikram Nanda & Sudheer Chava, 2022. "Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models," Papers 2206.06320, arXiv.org.
    12. Kensuke Ito & Kyohei Shibano & Gento Mogi, 2022. "Bubble Prediction of Non-Fungible Tokens (NFTs): An Empirical Investigation," Papers 2203.12587, arXiv.org, revised Jun 2022.
    13. 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.
    14. Caferra, Rocco, 2022. "Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    15. Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
    16. Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
    17. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    18. Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024. "Quantifying neural network uncertainty under volatility clustering," Papers 2402.14476, arXiv.org.
    19. Bowden, James & Gemayel, Roland, 2022. "Sentiment and trading decisions in an ambiguous environment: A study on cryptocurrency traders," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    20. Burggraf, Tobias & Rudolf, Markus, 2021. "Cryptocurrencies and the low volatility anomaly," Finance Research Letters, Elsevier, vol. 40(C).
    21. Chen, Cathy Yi-hsuan & Okhrin, Yarema & Wang, Tengyao, 2022. "Monitoring network changes in social media," LSE Research Online Documents on Economics 113742, London School of Economics and Political Science, LSE Library.
    22. Thomas E. Koker & Dimitrios Koutmos, 2020. "Cryptocurrency Trading Using Machine Learning," JRFM, MDPI, vol. 13(8), pages 1-7, August.
    23. Marco Ortu & Nicola Uras & Claudio Conversano & Giuseppe Destefanis & Silvia Bartolucci, 2021. "On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning," Papers 2102.08189, arXiv.org, revised Feb 2021.
    24. Melisa Ozdamar & Levent Akdeniz & Ahmet Sensoy, 2021. "Lottery-like preferences and the MAX effect in the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

  4. Bingduo Yang & Christian M. Hafner & Guannan Liu & Wei Long, 2019. "Semiparametric Estimation and Variable Selection for Single-index Copula Models," Working Papers 2019-07-05, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

    Cited by:

    1. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    2. 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.
    3. 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".

  5. HAFNER Christian, & KYRIAKOPOULOU Dimitra,, 2019. "Exponential-type GARCH models with linear-in-variance risk premium," LIDAM Discussion Papers CORE 2019013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Antonis Demos, 2023. "Estimation of Asymmetric Stochastic Volatility in Mean Models," DEOS Working Papers 2309, Athens University of Economics and Business.
    2. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.

  6. Bingduo Yang & Zongwu Cai & Christian M. Hafner & Guannan Liu, 2019. "Time-Varying Mixture Copula Models with Copula Selection," Working Papers 2019-07-05, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.

    Cited by:

    1. Naeem, Muhammad Abubakr & Bouri, Elie & Costa, Mabel D. & Naifar, Nader & Shahzad, Syed Jawad Hussain, 2021. "Energy markets and green bonds: A tail dependence analysis with time-varying optimal copulas and portfolio implications," Resources Policy, Elsevier, vol. 74(C).

  7. HAFNER Christian, & HERWARTZ Helmut, & MAXAND Simone,, 2018. "Identification of structural multivariate GARCH models," LIDAM Discussion Papers CORE 2018020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Manuel Carlos Nogueira & Mara Madaleno, 2022. "Are Sustainability Indices Infected by the Volatility of Stock Indices? Analysis before and after the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-13, November.
    2. Fengler, Matthias & Polivka, Jeannine, 2022. "Structural Volatility Impulse Response Analysis," Economics Working Paper Series 2211, University of St. Gallen, School of Economics and Political Science.
    3. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    4. 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).
    5. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    6. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    7. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    8. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.
    9. Hafner, Christian M. & Herwartz, Helmut, 2023. "Correlation impulse response functions," Finance Research Letters, Elsevier, vol. 57(C).
    10. Hafner, Christian M. & Herwartz, Helmut, 2023. "Asymmetric volatility impulse response functions," Economics Letters, Elsevier, vol. 222(C).
    11. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).

  8. Hafner, C. & Linton, O. & Tang, H., 2018. "Estimation of a Multiplicative Correlation Structure in the Large Dimensional Case," Cambridge Working Papers in Economics 1878, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    2. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    3. Chen, Xin & Yang, Dan & Xu, Yan & Xia, Yin & Wang, Dong & Shen, Haipeng, 2023. "Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data," Journal of Econometrics, Elsevier, vol. 232(2), pages 544-564.

  9. HAFNER Christian,, 2018. "Testing for bubbles in cryptocurrencies with time-varying volatility," LIDAM Discussion Papers CORE 2018019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jean-Louis Bago & Koffi Akakpo & Imad Rherrad & Ernest Ouédraogo, 2021. "Volatility Spillover and International Contagion of Housing Bubbles," JRFM, MDPI, vol. 14(7), pages 1-14, June.
    2. Chen, Cathy Yi-Hsuan & Hafner, Christian, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," LIDAM Reprints ISBA 2019053, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Yang Hu, 2023. "A review of Phillips‐type right‐tailed unit root bubble detection tests," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 141-158, February.
    4. 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".
    5. 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".
    6. De Pace, Pierangelo & Rao, Jayant, 2023. "Comovement and instability in cryptocurrency markets," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 173-200.
    7. Stefan Richter & Weining Wang & Wei Biao Wu, 2018. "A supreme test for periodic explosive GARCH," Papers 1812.03475, arXiv.org.
    8. 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".
    9. 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.
    10. Pavel Baboshkin & Alexey Mikhaylov & Zaffar Ahmed Shaikh, 2022. "Sustainable Cryptocurrency Growth Impossible? Impact of Network Power Demand on Bitcoin Price," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 116-130, June.
    11. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    12. Stefan Richter & Weining Wang & Wei Biao Wu, 2023. "Testing for parameter change epochs in GARCH time series," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 467-491.
    13. 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).
    14. Chuffart, Thomas, 2022. "Interest in cryptocurrencies predicts conditional correlation dynamics," Finance Research Letters, Elsevier, vol. 46(PA).
    15. 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".
    16. 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".
    17. 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.
    18. 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".
    19. 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".
    20. 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".
    21. 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.
    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".
    23. Tomás Caravello & Zacharias Psaradakis & Martín Sola, 2021. "Rational Bubbles: Too Many to be True?," Department of Economics Working Papers 2021_06, Universidad Torcuato Di Tella.
    24. Kim, Alisa & Trimborn, Simon & Härdle, Wolfgang Karl, 2021. "VCRIX — A volatility index for crypto-currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    25. 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).
    26. Bellón, Carlos & Figuerola-Ferretti, Isabel, 2022. "Bubbles in Ethereum," Finance Research Letters, Elsevier, vol. 46(PB).
    27. Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
    28. Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
    29. Panayiotis Theodossiou & Polina Ellina & Christos S. Savva, 2022. "Stochastic properties and pricing of bitcoin using a GJR-GARCH model with conditional skewness and kurtosis components," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 695-716, August.
    30. 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".
    31. 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".
    32. 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.
    33. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    34. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    35. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    36. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
    37. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    38. Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    39. 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".
    40. 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).
    41. Eiji Kurozumi & Anton Skrobotov & Alexey Tsarev, 2020. "Time-Transformed Test for the Explosive Bubbles under Non-stationary Volatility," Papers 2012.13937, arXiv.org, revised Nov 2021.
    42. Andrada-Félix, Julián & Fernandez-Perez, Adrian & Sosvilla-Rivero, Simón, 2020. "Distant or close cousins: Connectedness between cryptocurrencies and traditional currencies volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    43. 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.
    44. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    45. George Tzagkarakis & Frantz Maurer, 2023. "Horizon-Adaptive Extreme Risk Quantification for Cryptocurrency Assets," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1251-1286, October.
    46. Adam Hayes, 2018. "Bitcoin price and its marginal cost of production: support for a fundamental value," Papers 1805.07610, arXiv.org.
    47. 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".
    48. 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.
    49. 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.
    50. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    51. 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".
    52. Gil-Alana, Luis Alberiko & Abakah, Emmanuel Joel Aikins & Rojo, María Fátima Romero, 2020. "Cryptocurrencies and stock market indices. Are they related?," Research in International Business and Finance, Elsevier, vol. 51(C).
    53. 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.
    54. Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
    55. Jalan, Akanksha & Matkovskyy, Roman & Urquhart, Andrew & Yarovaya, Larisa, 2023. "The role of interpersonal trust in cryptocurrency adoption," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    56. 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".
    57. Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).
    58. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    59. Christian M. Hafner, 2020. "Alternative Assets and Cryptocurrencies," JRFM, MDPI, vol. 13(1), pages 1-3, January.
    60. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    61. 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".
    62. 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.
    63. Riccardo De Blasis, 2023. "Weighted-indexed semi-Markov model: calibration and application to financial modeling," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    64. 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".
    65. Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024. "Quantifying neural network uncertainty under volatility clustering," Papers 2402.14476, arXiv.org.
    66. Anyfantaki, Sofia & Arvanitis, Stelios & Topaloglou, Nikolas, 2021. "Diversification benefits in the cryptocurrency market under mild explosivity," European Journal of Operational Research, Elsevier, vol. 295(1), pages 378-393.
    67. 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".
    68. Troster, Victor & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Macedo, Demian Nicolás, 2019. "Bitcoin returns and risk: A general GARCH and GAS analysis," Finance Research Letters, Elsevier, vol. 30(C), pages 187-193.
    69. 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.
    70. Lee, Seungho & Meslmani, Nabil El & Switzer, Lorne N., 2020. "Pricing Efficiency and Arbitrage in the Bitcoin Spot and Futures Markets," Research in International Business and Finance, Elsevier, vol. 53(C).
    71. 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".
    72. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
    73. Bernd Süssmuth, 2022. "The mutual predictability of Bitcoin and web search dynamics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 435-454, April.
    74. Chen, Cathy Yi-hsuan & Okhrin, Yarema & Wang, Tengyao, 2022. "Monitoring network changes in social media," LSE Research Online Documents on Economics 113742, London School of Economics and Political Science, LSE Library.
    75. 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".

  10. Hafner, Christian & Manner, Hans & Simar, Leopold, 2018. "The “wrong skewnessâ€Ω problem in stochastic frontier models: A new approach," LIDAM Reprints ISBA 2018009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Simar, Léopold & Wilson, Paul, 2021. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," LIDAM Discussion Papers ISBA 2021003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Neubauer, Florian & Songsermsawas, Tisorn & Kámiche-Zegarra, Joanna & Bravo-Ureta, Boris E., 2022. "Technical efficiency and technological gaps correcting for selectivity bias: Insights from a value chain project in Nepal," Food Policy, Elsevier, vol. 112(C).
    3. Alecos Papadopoulos, 2021. "Stochastic frontier models using the Generalized Exponential distribution," Journal of Productivity Analysis, Springer, vol. 55(1), pages 15-29, February.
    4. Christopher F. Parmeter & Shirong Zhao, 2023. "An alternative corrected ordinary least squares estimator for the stochastic frontier model," Empirical Economics, Springer, vol. 64(6), pages 2831-2857, June.

  11. BOCART Fabian Y.R.P., & GHYSELS Eric, & HAFNER Christian,, 2018. "Monthly art market returns," LIDAM Discussion Papers CORE 2018028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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).
    2. Santeramo, Fabio G. & Dominguez, Ignacio Perez, 2021. "On the Effects of the COVID Epidemic on Global and Local Food Access and Availability of Strategic Sectors: Role of Trade and Implications for Policymakers," Commissioned Papers 309037, International Agricultural Trade Research Consortium.

  12. Christian M. HAFNER & Alexandre LAUWERS, 2017. "An augmented Taylor rule for the Federal Reserve's response to asset prices," LIDAM Reprints CORE 2882, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Devasmita Jena & Ishika Kataruka, 2022. "Monetary Response to Oil Price Shock in Asian Oil Importing Countries: Evaluation of Inflation Targeting Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(4), pages 809-825, December.
    2. Jaromir Baxa & Jan Zacek, 2022. "Monetary Policy and the Financial Cycle: International Evidence," Working Papers 2022/4, Czech National Bank.
    3. Mariia A. Molodchik & Carlos Jardon & Angel Barajas, 2015. "The Firm Size Effect On Performance Due To Intangible Resources," HSE Working papers WP BRP 35/MAN/2015, National Research University Higher School of Economics.

  13. GAO, Zhengyuan & HAFNER, Christian, 2016. "Looking Backward and Looking Forward," LIDAM Discussion Papers CORE 2016014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dvouletý Ondřej & Čadil Jan & Mirošník Karel, 2019. "Do Firms Supported by Credit Guarantee Schemes Report Better Financial Results 2 Years After the End of Intervention?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(1), pages 1-20, January.
    2. Yingxiu Zhao & Wei Zhang & Xiangyu Kong, 2019. "Dynamic Cross-Correlations between Participants’ Attentions to P2P Lending and Offline Loan in the Private Lending Market," Complexity, Hindawi, vol. 2019, pages 1-8, December.

  14. Hafner, Christian & Lauwers, Alexandre, 2015. "An augmented Taylor rule for the Federal Reserve’s response to asset prices," LIDAM Discussion Papers ISBA 2015028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Trinil Arimurti & Bruce Morley, 2020. "Do Capital Flows Matter for Monetary Policy Setting in Inflation Targeting Economies?," JRFM, MDPI, vol. 13(7), pages 1-15, June.

  15. Hafner, Christian & Manner, H. & Simar, L., 2015. "The “wrong skewness” problem in stochastic frontier models: a new approach," LIDAM Discussion Papers CORE 2015014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Oleg Badunenko & Daniel J. Henderson, 2024. "Production analysis with asymmetric noise," Journal of Productivity Analysis, Springer, vol. 61(1), pages 1-18, February.
    2. Parmeter, Christopher F. & Simar, Léopold & Van Keilegom, Ingrid & Zelenyuk, Valentin, 2021. "Inference in the Nonparametric Stochastic Frontier Model," LIDAM Discussion Papers ISBA 2021029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Rita, Rui & Marques, Vitor & Lúcia Costa, Ana & Matos Chaves, Inês & Gomes, Joana & Paulino, Paulo, 2018. "Efficiency performance and cost structure of Portuguese energy “utilities” – Non-parametric and parametric analysis," Energy, Elsevier, vol. 155(C), pages 35-45.
    4. Graziella Bonanno & Filippo Domma, 2022. "Analytical Derivations of New Specifications for Stochastic Frontiers with Applications," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
    5. Simar, Léopold & Wilson, Paul, 2021. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," LIDAM Discussion Papers ISBA 2021003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Neubauer, Florian & Songsermsawas, Tisorn & Kámiche-Zegarra, Joanna & Bravo-Ureta, Boris E., 2022. "Technical efficiency and technological gaps correcting for selectivity bias: Insights from a value chain project in Nepal," Food Policy, Elsevier, vol. 112(C).
    7. Alecos Papadopoulos, 2021. "Stochastic frontier models using the Generalized Exponential distribution," Journal of Productivity Analysis, Springer, vol. 55(1), pages 15-29, February.
    8. Christopher F. Parmeter & Shirong Zhao, 2023. "An alternative corrected ordinary least squares estimator for the stochastic frontier model," Empirical Economics, Springer, vol. 64(6), pages 2831-2857, June.
    9. Cheol-Keun Cho & Peter Schmidt, 2020. "The wrong skew problem in stochastic frontier models when inefficiency depends on environmental variables," Empirical Economics, Springer, vol. 58(5), pages 2031-2047, May.

  16. Christian M. Hafner & Sebastien Laurent & Francesco Violante, 2015. "Weak diffusion limits of dynamic conditional correlation models," CREATES Research Papers 2015-03, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. 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.
    2. Christian M. Hafner & Sébastien Laurent & Francesco Violante, 2017. "Weak Diffusion Limits of Dynamic Conditional Correlation Models," Post-Print hal-01590010, HAL.
    3. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    4. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    5. Ding, Y., 2020. "Diffusion Limits of Real-Time GARCH," Cambridge Working Papers in Economics 20112, Faculty of Economics, University of Cambridge.

  17. Fabian Y.R.P. BOCART & Christian M. HAFNER, 2015. "Volatility of Price Indices for Heterogeneous Goods with Applications to the Fine Art Market," LIDAM Reprints CORE 2771, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Fabian Y.R.P. Bocart & Eric Ghysels & Christian M. Hafner, 2020. "Monthly Art Market Returns," JRFM, MDPI, vol. 13(5), pages 1-22, May.
    2. Roar Adland & Pierre Cariou & François-Charles Wolff, 2018. "Comparing transaction-based and expert-generated price indices in the market for offshore support vessels," Working Papers halshs-01843720, HAL.
    3. 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).
    4. Garay, Urbi, 2021. "Determinants of art prices and performance by movements: Long-run evidence from an emerging market," Journal of Business Research, Elsevier, vol. 127(C), pages 413-426.
    5. Dimson, Elroy & Rousseau, Peter L. & Spaenjers, Christophe, 2013. "The Price of Wine," Working Papers 164656, American Association of Wine Economists.
    6. Arkadiusz J. Derkacz & Artur Gajda, 2022. "Changes in the Structure of the Apartments Rental Segment in Poland During the COVID-19 Pandemic," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 156-166.
    7. Fur, Eric Le, 2021. "Fine Wines in a Diversified Portfolio of Collectibles," 2021 Conference, August 17-31, 2021, Virtual 315852, International Association of Agricultural Economists.

  18. Ben Omrane, Walid & Hafner, Christian, 2015. "Macroeconomic news surprises and volatility spillover in foreign exchange markets," LIDAM Reprints ISBA 2015028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.
    2. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    3. Roy Trivedi, Smita, 2018. "Exchange rate volatility: Trader's beliefs and the role of news," MPRA Paper 89330, University Library of Munich, Germany.
    4. Smita Roy Trivedi, 2022. "The Janus view: Do market participants looking into the past impact foreign exchange volatility?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3990-4001, October.
    5. Haidong Cai & Shamim Ahmed & Ying Jiang & Xiaoquan Liu, 2020. "The impact of US macroeconomic news announcements on Chinese commodity futures," Quantitative Finance, Taylor & Francis Journals, vol. 20(12), pages 1927-1966, December.
    6. Munazza Jabeen & Abdul Rashid, 2022. "Macroeconomic News and Exchange Rates: Exploring the Role of Order Flow," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(2), pages 222-245, May.
    7. Adrian Cantemir CĂLIN & Radu LUPU, 2016. "The Effects Of Labor Market News On International Financial Markets," Romanian Economic Business Review, Romanian-American University, vol. 11(2), pages 207-215, June.
    8. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    9. Ayadi, Mohamed A. & Ben Omrane, Walid & Lazrak, Skander & Yan, Xusheng, 2020. "OPEC production decisions, macroeconomic news, and volatility in the Canadian currency and oil markets," Finance Research Letters, Elsevier, vol. 37(C).
    10. Munazza Jabeen & Abdul Rashid & Hajra Ihsan, 2022. "The news effects on exchange rate returns and volatility: Evidence from Pakistan," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 745-769, January.
    11. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.
    12. Ekinci, Cumhur & Akyildirim, Erdinc & Corbet, Shaen, 2019. "Analysing the dynamic influence of US macroeconomic news releases on Turkish stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 155-164.
    13. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    14. Vortelinos, Dimitrios I. & Koulakiotis, Athanasios & Tsagkanos, Athanasios, 2017. "Intraday analysis of macroeconomic news surprises and asymmetries in mini-futures markets," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 150-168.
    15. Ben Omrane, Walid & Savaşer, Tanseli, 2017. "Exchange rate volatility response to macroeconomic news during the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 130-143.

  19. Christian M. HAFNER & Arie PREMINGER, 2015. "An ARCH Model Without Intercept," LIDAM Reprints CORE 2770, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Li, Dong & Ling, Shiqing & Zhu, Ke, 2016. "ZD-GARCH model: a new way to study heteroscedasticity," MPRA Paper 68621, University Library of Munich, Germany.
    2. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
    3. Zhu, Ke, 2023. "A new generalized exponentially weighted moving average quantile model and its statistical inference," Journal of Econometrics, Elsevier, vol. 237(1).
    4. Li, Dong & Zhang, Xingfa & Zhu, Ke & Ling, Shiqing, 2018. "The ZD-GARCH model: A new way to study heteroscedasticity," Journal of Econometrics, Elsevier, vol. 202(1), pages 1-17.
    5. Kejin Wu & Sayar Karmakar, 2021. "Model-Free Time-Aggregated Predictions for Econometric Datasets," Forecasting, MDPI, vol. 3(4), pages 1-14, December.

  20. HÃ≠rdle, Wolfgang Karl & Prastyo, Dedy Dwi & Hafner, Christian, 2014. "Support Vector Machines with Evolutionary Model Selection for Default Prediction," LIDAM Reprints ISBA 2014016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. 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.

  21. HAFNER, Christian & PREMINGER, Arie, 2014. "A note on the Tobit model in the presence of a duration variable," LIDAM Discussion Papers CORE 2014013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dong Feng & Jian Li & Xintao Li & Zaisheng Zhang, 2019. "The Effects of Urban Sprawl and Industrial Agglomeration on Environmental Efficiency: Evidence from the Beijing–Tianjin–Hebei Urban Agglomeration," Sustainability, MDPI, vol. 11(11), pages 1-12, May.

  22. Michael McAleer & Christian M. Hafner, 2014. "A One Line Derivation of EGARCH," Documentos de Trabajo del ICAE 2014-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    Cited by:

    1. Chia-Lin Chang & Michael McAleer, 2017. "The Fiction of Full BEKK," Documentos de Trabajo del ICAE 2017-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & Maasoumi, Esfandiar & McAleer, Michael & Pérez-Amaral, Teodosio, 2019. "Choosing expected shortfall over VaR in Basel III using stochastic dominance," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 95-113.
    3. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    4. Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Esfandiar Maasoumi & Michael McAleer & Teodosio Pérez-Amaral, 2015. "A Stochastic Dominance Approach to the Basel III Dilemma: Expected Shortfall or VaR?," Documentos de Trabajo del ICAE 2015-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Swarn Chatterjee & Amy Hubble, 2016. "Day-Of-The-Week Effect In Us Biotechnology Stocks — Do Policy Changes And Economic Cycles Matter?," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 1-17, June.
    6. Guillaume Gaetan Martinet & Michael McAleer, 2014. "On the Invertibility of EGARCH," Working Papers in Economics 14/21, University of Canterbury, Department of Economics and Finance.
    7. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Tinbergen Institute Discussion Papers 17-051/III, Tinbergen Institute.
    8. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Asai, M. & Chang, C-L. & McAleer, M.J., 2016. "Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers," Econometric Institute Research Papers EI2016-41, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Chia-Lin Chang & Michael McAleer, 2017. "The Correct Regularity Condition and Interpretation of Asymmetry in EGARCH," Tinbergen Institute Discussion Papers 17-056/III, Tinbergen Institute.
    11. Zopiatis, A. & Savva, C.S. & Lambertides, N. & McAleer, M.J., 2016. "Tourism Stocks in Times of Crises: an Econometric Investigation of Non-macro Factors," Econometric Institute Research Papers TI 2016-104/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Fengming Qin & Junru Zhang & Zhaoyong Zhang, 2018. "RMB Exchange Rates and Volatility Spillover across Financial Markets in China and Japan," Risks, MDPI, vol. 6(4), pages 1-26, October.
    13. Chang, C-L. & McAleer, M.J. & Wang, C-H., 2016. "An Econometric Analysis of ETF and ETF Futures in Financial and Energy Markets Using Generated Regressors," Econometric Institute Research Papers EI2016-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "An Event Study Analysis of Political Events, Disasters, and Accidents for Chinese Tourists to Taiwan," Sustainability, MDPI, vol. 10(11), pages 1-77, November.
    15. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    16. Chang, Chia-Lin & Jiménez-Martín, Juan-Ángel & Maasoumi, Esfandiar & Pérez-Amaral, Teodosio, 2015. "A stochastic dominance approach to financial risk management strategies," Journal of Econometrics, Elsevier, vol. 187(2), pages 472-485.
    17. Urom, Christian & Onwuka, Kevin O. & Uma, Kalu E. & Yuni, Denis N., 2020. "Regime dependent effects and cyclical volatility spillover between crude oil price movements and stock returns," International Economics, Elsevier, vol. 161(C), pages 10-29.
    18. Kostyrka, Andreï & Malakhov, Dmitry, 2021. "Was there ever a shift: Empirical analysis of structural-shift tests for return volatility," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 110-139.
    19. Michael McAleer, 2014. "Asymmetry and Leverage in Conditional Volatility Models," Econometrics, MDPI, vol. 2(3), pages 1-6, September.
    20. Najam Iqbal & Muhammad Saqib Manzoor & Muhammad Ishaq Bhatti, 2021. "Asymmetry and Leverage with News Impact Curve Perspective in Australian Stock Returns’ Volatility during COVID-19," JRFM, MDPI, vol. 14(7), pages 1-15, July.
    21. Asai, M. & McAleer, M.J., 2016. "Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes," Econometric Institute Research Papers EI2016-35, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Junru Zhang & Hadrian Geri Djajadikerta & Zhaoyong Zhang, 2018. "Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    23. Elena Villar-Rubio & María-Dolores Huete-Morales & Federico Galán-Valdivieso, 2023. "Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 13(3), pages 500-509, September.
    24. Chia-Lin Chang & Michael McAleer & Shu-Han Hsu, 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Documentos de Trabajo del ICAE 2018-11, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    25. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Econometric Institute Research Papers EI2016-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    26. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2013. "The Impact of China on Stock Returns and Volatility in the Taiwan Tourism Industry," Tinbergen Institute Discussion Papers 13-118/III, Tinbergen Institute.
    27. Chang, C-L. & McAleer, M.J. & Tian, J., 2016. "Modelling and Testing Volatility Spillovers in Oil and Financial Markets for USA, UK and China," Econometric Institute Research Papers EI2016-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    28. Chia-Lin Chang & Michael McAleer, 2018. "The Fiction of Full BEKK: Pricing Fossil Fuels and Carbon Emissions," Tinbergen Institute Discussion Papers 17-015/III, Tinbergen Institute.
    29. David E. Allen & Michael McAleer, 2017. "Theoretical and Empirical Differences Between Diagonal and Full BEKK for Risk Management," Documentos de Trabajo del ICAE 2017-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    30. Usha Rekha Chinthapalli, 2021. "A Comparative Analysis on Probability of Volatility Clusters on Cryptocurrencies, and FOREX Currencies," JRFM, MDPI, vol. 14(7), pages 1-23, July.
    31. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
    32. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    33. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," JRFM, MDPI, vol. 11(4), pages 1-25, September.
    34. Dey, Asim K. & Hoque, G.M. Toufiqul & Das, Kumer P. & Panovska, Irina, 2022. "Impacts of COVID-19 local spread and Google search trend on the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    35. Yuki Toyoshima, 2018. "Testing for Causality-In-Mean and Variance between the UK Housing and Stock Markets," JRFM, MDPI, vol. 11(2), pages 1-10, April.
    36. Karima Saci, 2022. "Modelling the Relationship Between Trading Volume and Stock Returns Volatility for Islamic and Conventional Banks: The Case of Saudi Arabia نمذجة العلاقة بين حجم التداول وتقلب عوائد الأسهم للبنوك الإس," Journal of King Abdulaziz University: Islamic Economics, King Abdulaziz University, Islamic Economics Institute., vol. 35(1), pages 41-55, January.
    37. Usman M. Umer, Metin Coskun, Kasim Kiraci, 2018. "Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 3(1), pages 23-42, March.
    38. Chia-Lin Chang & Shu-Han Hsu & Michael McAleer, 2018. "An event study of chinese tourists to Taiwan," Documentos de Trabajo del ICAE 2018-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    39. Nader Trabelsi & Aviral Kumar Tiwari, 2023. "CO2 Emission Allowances Risk Prediction with GAS and GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 775-805, February.
    40. Philip Hans Franses & Eva Janssens, 2017. "Recovering Historical Inflation Data from Postage Stamps Prices," JRFM, MDPI, vol. 10(4), pages 1-11, November.
    41. Yeguang Chi & Wenyan Hao, 2020. "A Horserace of Volatility Models for Cryptocurrency: Evidence from Bitcoin Spot and Option Markets," Papers 2010.07402, arXiv.org.
    42. Swarn Chatterjee, 2017. "Day of the Week Effect in biotechnology stocks: An Application of the GARCH processes," Papers 1701.07175, arXiv.org.
    43. Victor Shevchuk & Roman Kopych, 2021. "Exchange Rate Volatility, Currency Misalignment, and Risk of Recession in the Central and Eastern European Countries," Risks, MDPI, vol. 9(5), pages 1-19, May.
    44. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    45. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    46. Tonmoy Choudhury & Simone Scagnelli & Jaime Yong & Zhaoyong Zhang, 2021. "Non-Traditional Systemic Risk Contagion within the Chinese Banking Industry," Sustainability, MDPI, vol. 13(14), pages 1-16, July.

  23. Christian M. Hafner & Michael McAleer, 2014. "A One Line Derivation of DCC: Application of a Vector Random Coefficient Moving Average Process," Working Papers in Economics 14/19, University of Canterbury, Department of Economics and Finance.

    Cited by:

    1. Chang, C-L. & Liu, C-P. & McAleer, M.J., 2016. "Volatility Spillovers for Spot, Futures, and ETF Prices in Energy and Agriculture," Econometric Institute Research Papers EI2016-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Tinbergen Institute Discussion Papers 17-051/III, Tinbergen Institute.
    3. Chang, C-L. & McAleer, M.J. & Wang, C-H., 2016. "An Econometric Analysis of ETF and ETF Futures in Financial and Energy Markets Using Generated Regressors," Econometric Institute Research Papers EI2016-31, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    5. Syed Kumail Abbas Rizvi & Bushra Naqvi & Nawazish Mirza, 2022. "Is green investment different from grey? Return and volatility spillovers between green and grey energy ETFs," Annals of Operations Research, Springer, vol. 313(1), pages 495-524, June.
    6. Chang, C-L. & McAleer, M.J. & Wang, Y., 2016. "Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances," Econometric Institute Research Papers EI2016-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Econometric Institute Research Papers EI2016-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn," Documentos de Trabajo del ICAE 2016-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    9. Chang, C-L. & McAleer, M.J. & Tian, J., 2016. "Modelling and Testing Volatility Spillovers in Oil and Financial Markets for USA, UK and China," Econometric Institute Research Papers EI2016-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  24. Hafner, Christian & Breitung, Jörg, 2014. "A simple model for now-casting volatility series," LIDAM Discussion Papers CORE 2014060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    2. Kejin Wu & Sayar Karmakar, 2023. "A model-free approach to do long-term volatility forecasting and its variants," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    3. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    4. Kelvin Mutum, 2020. "Volatility Forecast Incorporating Investors’ Sentiment and its Application in Options Trading Strategies: A Behavioural Finance Approach at Nifty 50 Index," Vision, , vol. 24(2), pages 217-227, June.
    5. Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.

  25. El Mehdi, Rachida & Hafner, Christian, 2014. "Inference in stochastic frontier analysis with dependent error terms," LIDAM Reprints ISBA 2014028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Kexin Li & Jianxu Liu & Yuting Xue & Sanzidur Rahman & Songsak Sriboonchitta, 2022. "Consequences of Ignoring Dependent Error Components and Heterogeneity in a Stochastic Frontier Model: An Application to Rice Producers in Northern Thailand," Agriculture, MDPI, vol. 12(8), pages 1-17, July.
    2. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    3. Alecos Papadopoulos & Christopher F. Parmeter & Subal C. Kumbhakar, 2021. "Modeling dependence in two-tier stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 56(2), pages 85-101, December.
    4. Benjamin M. Tabak & Daniel O. Cajueiro & Marina V. B. Dias, 2014. "The Adequacy of Deterministic and Parametric Frontiers to Analyze the Efficiency of Indian Commercial Banks," Working Papers Series 350, Central Bank of Brazil, Research Department.
    5. Emilio Gómez-Déniz & Nancy Dávila-Cárdenes & Alejandro Leiva-Arcas & María J. Martínez-Patiño, 2021. "Measuring Efficiency in the Summer Olympic Games Disciplines: The Case of the Spanish Athletes," Mathematics, MDPI, vol. 9(21), pages 1-15, October.
    6. Mamonov Mikhail E. & Parmeter Christopher F. & Prokhorov Artem B., 2022. "Dependence modeling in stochastic frontier analysis," Dependence Modeling, De Gruyter, vol. 10(1), pages 123-144, January.
    7. Schmidt, Rouven & Kneib, Thomas, 2023. "Multivariate distributional stochastic frontier models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    8. Alecos Papadopoulos, 2023. "The noise error component in stochastic frontier analysis," Empirical Economics, Springer, vol. 64(6), pages 2795-2829, June.
    9. Alecos Papadopoulos & Christopher F. Parmeter, 2024. "The wrong skewness problem in stochastic frontier analysis: a review," Journal of Productivity Analysis, Springer, vol. 61(2), pages 121-134, April.
    10. Jianxu Liu & Mengjiao Wang & Ji Ma & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry," Mathematics, MDPI, vol. 8(2), pages 1-23, February.

  26. Bauwens, Luc & Hafner, Christian & Pierret, Diane, 2013. "Modelling multivariate volatility of electricity futures," LIDAM Reprints ISBA 2013030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    3. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    4. Escribano, Álvaro & Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.

  27. El Mehdi, Rachida & Hafner, Christian, 2013. "Local government efficiency: The case of Moroccan municipalities," LIDAM Discussion Papers ISBA 2013001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Francesco Aiello & Graziella Bonanno & Luigi Capristo, 2017. "Explaining Differences In Efficiency: The Case Of Local Government Literature," Working Papers 201704, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    2. Aiello, Francesco & Bonanno, Graziella & Capristo, Luigi, 2018. "Explaining differences in efficiency. A meta-study on local government literature," MPRA Paper 88982, University Library of Munich, Germany.
    3. Isabel Narbón-Perpiñá & Mª Teresa Balaguer-Coll & Marko Petrovic & Emili Tortosa-Ausina, 2017. "Which estimator to measure local governments’ cost efficiency? An application to Spanish municipalities," Working Papers 2017/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. William Orlando Prieto Bustos & Joan Miguel Tejedor Estupiñán, 2019. "Eficiencia Técnica de las Instituciones Públicas Locales en Colombia," Revista de Estudios Regionales, Universidades Públicas de Andalucía, vol. 2, pages 15-41.
    5. Isabel Narbón-Perpiñá & Kristof De Witte, 2016. "Local governments’ efficiency: A systematic literature review – Part I," Working Papers 2016/20, Economics Department, Universitat Jaume I, Castellón (Spain).
    6. Isabel Narbón-Perpiñá & Maria Teresa Balaguer-Coll & Marko Petrović & Emili Tortosa-Ausina, 2020. "Which estimator to measure local governments’ cost efficiency? The case of Spanish municipalities," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(1), pages 51-82, March.

  28. Fabian Y.R.P. Bocart & Christian M. Hafner, 2013. "Fair re-valuation of wine as an investment," SFB 649 Discussion Papers SFB649DP2013-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Connor, Linda H., 2016. "Energy futures, state planning policies and coal mine contests in rural New South Wales," Energy Policy, Elsevier, vol. 99(C), pages 233-241.
    2. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Eric Le Fur & Jean-François Outreville, 2019. "Fine wine returns: a review of the literature," Journal of Asset Management, Palgrave Macmillan, vol. 20(3), pages 196-214, May.
    6. Chiara Canta & Marie-Louise Leroux, 2016. "Public and Private Hospitals, Congestion, and Redistribution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(1), pages 42-66, February.
    7. WOLSEY, Laurence & YAMAN , Hand & ,, 2013. "Continuous knapsack sets with divisible capacities," LIDAM Discussion Papers CORE 2013063, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Bocart, F. & Hafner, C., 2013. "Fair re-valuation of wine as an investment," LIDAM Discussion Papers ISBA 2013003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Ben Ameur, Hachmi & Le Fur, Eric, 2020. "Volatility transmission to the fine wine market," Economic Modelling, Elsevier, vol. 85(C), pages 307-316.
    10. Adam Sȩdziwy, 2015. "Sustainable Street Lighting Design Supported by Hypergraph-Based Computational Model," Sustainability, MDPI, vol. 8(1), pages 1-13, December.
    11. Hare, Stephanie, 2016. "For your eyes only: U.S. technology companies, sovereign states, and the battle over data protection," Business Horizons, Elsevier, vol. 59(5), pages 549-561.
    12. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  29. HAFNER, Christian & LINTON, Oliver, 2013. "An almost closed form estimator for the EGARCH model," LIDAM Discussion Papers CORE 2013022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. DEMOS Antonis, & KYRIAKOPOULOU Dimitra,, 2018. "Finite sample theory and bias correction of maximum likelihood estimators in the EGARCH model," LIDAM Discussion Papers CORE 2018007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Hafner, Christian & Kyriakopoulou, Dimitra, 2020. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," LIDAM Reprints ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Chiara Canta & Marie-Louise Leroux, 2016. "Public and Private Hospitals, Congestion, and Redistribution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(1), pages 42-66, February.
    6. Carnero M. Angeles & Pérez Ana, 2021. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-19, February.
    7. Bocart, F. & Hafner, C., 2013. "Fair re-valuation of wine as an investment," LIDAM Discussion Papers ISBA 2013003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Prono Todd, 2018. "Closed-form estimators for finite-order ARCH models as simple and competitive alternatives to QMLE," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    9. GOERTZ, Johanna & MANIQUET, François, 2013. "Large elections with multiple alternatives: a Condorcet Jury Theorem and inefficient equilibria," LIDAM Discussion Papers CORE 2013023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Ahsan, Md. Nazmul & Dufour, Jean-Marie, 2021. "Simple estimators and inference for higher-order stochastic volatility models," Journal of Econometrics, Elsevier, vol. 224(1), pages 181-197.
    11. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  30. Hafner C. & Linton, O., 2013. "An Almost Closed Form Estimator for the EGARCH," LIDAM Discussion Papers ISBA 2013010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Hafner, Christian & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The EGARCH Model," LIDAM Reprints ISBA 2017040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Chiara Canta & Marie-Louise Leroux, 2016. "Public and Private Hospitals, Congestion, and Redistribution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(1), pages 42-66, February.
    5. Bocart, F. & Hafner, C., 2013. "Fair re-valuation of wine as an investment," LIDAM Discussion Papers ISBA 2013003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. GOERTZ, Johanna & MANIQUET, François, 2013. "Large elections with multiple alternatives: a Condorcet Jury Theorem and inefficient equilibria," LIDAM Discussion Papers CORE 2013023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  31. Hafner, Christian, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," LIDAM Reprints ISBA 2012027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Takaki Hayashi & Yuta Koike, 2017. "Multi-scale analysis of lead-lag relationships in high-frequency financial markets," Papers 1708.03992, arXiv.org, revised May 2020.
    2. Concepción González-Concepción & María Candelaria Gil-Fariña & Celina Pestano-Gabino, 2018. "Wavelet power spectrum and cross-coherency of Spanish economic variables," Empirical Economics, Springer, vol. 55(2), pages 855-882, September.
    3. Takaki Hayashi & Yuta Koike, 2016. "Wavelet-based methods for high-frequency lead-lag analysis," Papers 1612.01232, arXiv.org, revised Nov 2018.

  32. Fabian Y.R.P. Bocart & Christian M. Hafner, 2012. "Volatility of price indices for heterogeneous goods," SFB 649 Discussion Papers SFB649DP2012-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Dimson, Elroy & Rousseau, Peter L. & Spaenjers, Christophe, 2013. "The Price of Wine," Working Papers 164656, American Association of Wine Economists.
    2. Renneboog, L.D.R. & Spaenjers, C., 2011. "Hard Assets : The Returns on Rare Diamonds and Gems," Discussion Paper 2011-056, Tilburg University, Center for Economic Research.

  33. 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. 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.
    2. 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.
    3. 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.

  34. Hafner, Christian & Reznikova, O., 2012. "On the estimation of dynamic conditional correlation models," LIDAM Reprints ISBA 2012021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    2. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-953, CIRJE, Faculty of Economics, University of Tokyo.
    3. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    4. Hendrych, R. & Cipra, T., 2016. "On conditional covariance modelling: An approach using state space models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 304-317.
    5. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    6. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    7. Narayan, S. & Sriananthakumar, S. & Islam, S.Z., 2014. "Stock market integration of emerging Asian economies: Patterns and causes," Economic Modelling, Elsevier, vol. 39(C), pages 19-31.
    8. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    9. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    10. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    11. Elie Bouri & Naji Jalkh & Peter Molnár & David Roubaud, 2017. "Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?," Applied Economics, Taylor & Francis Journals, vol. 49(50), pages 5063-5073, October.
    12. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    13. Trucíos Maza, Carlos César & Hotta, Luiz Koodi & Pereira, Pedro L. Valls, 2018. "On the robustness of the principal volatility components," Textos para discussão 474, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2022. "Can Volatility Solve the Naive Portfolio Puzzle?," Villanova School of Business Department of Economics and Statistics Working Paper Series 52, Villanova School of Business Department of Economics and Statistics.
    15. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. 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).
    17. Evzen Kocenda & Michala Moravcova, 2017. "Exchange Rate Co-movements, Hedging and Volatility Spillovers in New EU Forex Markets," Working Papers IES 2017/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    18. Staer, Arsenio & Sottile, Pedro, 2018. "Equivalent volume and comovement," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 143-157.
    19. Ledoit, Olivier & Wolf, Michael, 2017. "Numerical implementation of the QuEST function," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 199-223.
    20. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    21. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    22. Baumohl, Eduard & Lyocsa, Stefan, 2013. "Volatility and dynamic conditional correlations of European emerging stock markets," MPRA Paper 49898, University Library of Munich, Germany.
    23. Saker Sabkha & Christian de Peretti, 2022. "On the performances of Dynamic Conditional Correlation models in the Sovereign CDS market and the corresponding bond market," Post-Print hal-01710398, HAL.
    24. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    25. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.
    26. Paola Leone & Pasqualina Porretta & Luca Riccetti, 2021. "European Significant Bank Stock Market Volatility: Is there a Bail-In Effect?," International Journal of Business and Management, Canadian Center of Science and Education, vol. 14(5), pages 1-32, July.
    27. M. Hakan Eratalay & Evgenii Vladimirov, 2017. "Mapping the Stocks in MICEX: Who Is Central in Moscow Stock Exchange?," EUSP Department of Economics Working Paper Series 2017/01, European University at St. Petersburg, Department of Economics.
    28. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    29. R. Ferreira, Alexandre & A. P. Santos, Andre, 2016. "On the choice of covariance specifications for portfolio selection problems," MPRA Paper 73259, University Library of Munich, Germany.
    30. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    31. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    32. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    33. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    34. Stavrakoudis, Athanassios & Panagiotou, Dimitrios, 2016. "Price dependence between coffee qualities: a copula model to evaluate asymmetric responses," MPRA Paper 75994, University Library of Munich, Germany.
    35. Robert F. Engle & Olivier Ledoit & Michael Wolf, 2016. "Large dynamic covariance matrices," ECON - Working Papers 231, Department of Economics - University of Zurich, revised Apr 2017.
    36. Sun, Xiaolin & Haralambides, Hercules & Liu, Hailong, 2019. "Dynamic spillover effects among derivative markets in tanker shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 384-409.
    37. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.
    38. Kei Nakagawa & Mitsuyoshi Imamura & Kenichi Yoshida, 2018. "Risk-Based Portfolios with Large Dynamic Covariance Matrices," IJFS, MDPI, vol. 6(2), pages 1-14, May.
    39. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    40. Heaney, Richard & Sriananthakumar, Sivagowry, 2012. "Time-varying correlation between stock market returns and real estate returns," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 583-594.
    41. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    42. Sriananthakumar, Sivagowry & Narayan, Seema, 2015. "Are prolonged conflict and tension deterrents for stock market integration? The case of Sri Lanka," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 504-520.
    43. Ali, Fahad & Bouri, Elie & Naifar, Nader & Shahzad, Syed Jawad Hussain & AlAhmad, Mohammad, 2022. "An examination of whether gold-backed Islamic cryptocurrencies are safe havens for international Islamic equity markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    44. Haishu Qiao & Yue Xia & Ying Li, 2016. "Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-25, June.

  35. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2011. "Multivariate Volatility Modeling of Electricity Futures," SFB 649 Discussion Papers SFB649DP2011-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    4. Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019. "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    5. Brenda López Cabrera, & Franziska Schulz,, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers SFB649DP2013-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. 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.
    7. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2011. "Multivariate Volatility Modeling of Electricity Futures," SFB 649 Discussion Papers SFB649DP2011-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    10. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    11. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    12. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    13. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016. "Semiparametric Estimation With Generated Covariates," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1140-1177, October.
    14. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    15. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    16. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    17. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    18. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Scholarly Articles 34650305, Harvard University Department of Economics.
    19. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    20. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2011. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2011-072, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    22. 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.
    23. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    24. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    26. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    27. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    28. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    29. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    30. 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.
    31. Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2013. "Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants," Energy Policy, Elsevier, vol. 59(C), pages 143-160.
    32. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    33. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    34. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    35. Escribano, Álvaro & Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    36. Francisco Ortiz Arango & Alma Nelly Montiel Guzmán, 2017. "Transmission of future prices of corn of the Chicago Board of Trade to the Mexican spot market," Contaduría y Administración, Accounting and Management, vol. 62(3), pages 941-957, Julio-Sep.
    37. 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.
    38. 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.
    39. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    40. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    41. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.

  36. Daniel , Betty C & Hafner, Christian & Manner, Hans & Simar, Leopold, 2011. "Asymmetries in Business Cycles and the Role of Oil Production," LIDAM Discussion Papers ISBA 2011032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Morana, Claudio, 2012. "The Oil Price-Macroeconomy Relationship since the Mid- 1980s: A Global Perspective," Energy: Resources and Markets 127423, Fondazione Eni Enrico Mattei (FEEM).

  37. Hafner, Christian & Manner, Hans, 2011. "Multivariate Time Series Models for Asset Prices," LIDAM Reprints ISBA 2011053, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.

  38. Motta, Giovanni & Hafner, Christian & von Sachs, Rainer, 2011. "Locally Stationary Factor Models: Identification And Nonparametric Estimation," LIDAM Reprints ISBA 2011007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    2. Zura Kakushadze, 2015. "Heterotic Risk Models," Papers 1508.04883, arXiv.org, revised Jan 2016.
    3. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    4. Eichler, Michael & Motta, Giovanni & von Sachs, Rainer, 2011. "Fitting dynamic factor models to non-stationary time series," Journal of Econometrics, Elsevier, vol. 163(1), pages 51-70, July.
    5. Giovanni Motta & Hernando Ombao, 2012. "Evolutionary Factor Analysis of Replicated Time Series," Biometrics, The International Biometric Society, vol. 68(3), pages 825-836, September.
    6. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2020. "Time-varying general dynamic factor models and the measurement of financial connectedness," LIDAM Reprints ISBA 2020015, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    7. Marc Hallin & Marco Lippi, 2013. "Factor Models in High-Dimensional Time Series: A Time-Domain Approach," Working Papers ECARES ECARES 2013-15, ULB -- Universite Libre de Bruxelles.
    8. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    9. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    10. Caro Navarro, Ángela & Peña, Daniel, 2018. "Estimation of the common component in Dynamic Factor Models," DES - Working Papers. Statistics and Econometrics. WS 27047, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    12. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    13. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    14. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    15. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.

  39. 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., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • 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).

    Cited by:

    1. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
    2. 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.
    3. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2011. "Multivariate Volatility Modeling of Electricity Futures," SFB 649 Discussion Papers SFB649DP2011-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    6. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    7. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    8. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    9. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    10. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    11. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016. "Semiparametric Estimation With Generated Covariates," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1140-1177, October.
    12. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    13. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    14. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    15. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2011. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2011-072, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    17. 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.
    18. Dorothee Schneider, 2011. "The Labor Share: A Review of Theory and Evidence," SFB 649 Discussion Papers SFB649DP2011-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Serge Darolles & Christian Francq & Sébastien Laurent, 2018. "Asymptotics of Cholesky GARCH Models and Time-Varying Conditional Betas," Working Papers halshs-01944656, HAL.
    20. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    21. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    23. Yaya, OlaOluwa S. & Tumala, Mohammed M. & Udomboso, Christopher G., 2016. "Volatility persistence and returns spillovers between oil and gold prices: Analysis before and after the global financial crisis," Resources Policy, Elsevier, vol. 49(C), pages 273-281.
    24. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "Intra-daily volatility spillovers between the US and German stock markets," Economics Working Papers 2012-06, Christian-Albrechts-University of Kiel, Department of Economics.
    25. 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.
    26. 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.

  40. BOCART, Fabian Y. R. P. & HAFNER, Christian, 2011. "Econometric analysis of volatile art markets," LIDAM Discussion Papers CORE 2011052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Raffaele Fiocco, 2012. "Competition and regulation with product differentiation," Journal of Regulatory Economics, Springer, vol. 42(3), pages 287-307, December.
    2. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    3. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 490-520.
    4. Kim Oosterlinck, 2017. "Art as a Wartime Investment: Conspicuous Consumption and Discretion," Economic Journal, Royal Economic Society, vol. 127(607), pages 2665-2701, December.
    5. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2011. "Financial Network Systemic Risk Contributions," SFB 649 Discussion Papers SFB649DP2011-072, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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. Fabian Y.R.P. Bocart & Christian M. Hafner, 2012. "Volatility of price indices for heterogeneous goods," SFB 649 Discussion Papers SFB649DP2012-039, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Bocart, F. & Hafner, C., 2013. "Fair re-valuation of wine as an investment," LIDAM Discussion Papers ISBA 2013003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. 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.
    10. Dominik Filipiak & Agata Filipowska, 2016. "Towards data oriented analysis of the art market: survey and outlook," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(1), pages 21-31, June.
    11. Vecco, Marilena & Zanola, Roberto, 2017. "Don’t let the easy be the enemy of the good. Returns from art investments: What is wrong with it?," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 120-129.
    12. 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.
    13. Shailendra Gurjar & Usha Ananthakumar, 2023. "The economics of art: price determinants and returns on investment in Indian paintings," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 50(6), pages 839-859, January.

  41. Aurélie Bertrand & Christian M. Hafner, 2011. "On heterogeneous latent class models with applications to the analysis of rating scores," SFB 649 Discussion Papers SFB649DP2011-062, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Sunil Kumar & Zakir Husain & Diganta Mukherjee, 2015. "Assessing Consistency of Consumer Confidence Data using Dynamic Latent Class Analysis," Papers 1509.01215, arXiv.org.
    2. Bart Neuts & João Romão & Peter Nijkamp & Asami Shikida, 2016. "Market segmentation and their potential economic impacts in an ecotourism destination," Tourism Economics, , vol. 22(4), pages 793-808, August.
    3. Kumar, Sunil & Husain, Zakir & Mukherjee, Diganta, 2017. "Assessing consistency of consumer confidence data using latent class analysis with time factor," Economic Analysis and Policy, Elsevier, vol. 55(C), pages 35-46.

  42. Hafner, Christian & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," LIDAM Reprints ISBA 2010033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
    2. Gong Jinguo & Shi Daimin & Wu Weiou & McMillan David, 2015. "Non-parametric estimation of copula parameters: testing for time-varying correlation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 93-106, February.
    3. 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).
    4. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    5. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
    6. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01821815, HAL.
    7. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2012. "Global Risk Evolution and Diversification: a Copula-DCC-GARCH Model Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(4), pages 529-550.
    8. 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).
    9. Yang, Bingduo & Cai, Zongwu & Hafner, Christian M. & Liu, Guannan, 2018. "Trending Mixture Copula Models with Copula Selection," IRTG 1792 Discussion Papers 2018-057, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    10. 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.
    11. Gijbels, Irène & Herrmann, Klaus, 2014. "On the distribution of sums of random variables with copula-induced dependence," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 27-44.
    12. 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.
    13. 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).
    14. Reboredo, Juan C., 2013. "Modeling EU allowances and oil market interdependence. Implications for portfolio management," Energy Economics, Elsevier, vol. 36(C), pages 471-480.
    15. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    16. Lei Hou & Wei Long & Qi Li, 2019. "Comovement of Home Prices: A Conditional Copula Approach," Annals of Economics and Finance, Society for AEF, vol. 20(1), pages 297-318, May.
    17. Manner, Hans & Segers, Johan, 2011. "Tails of correlation mixtures of elliptical copulas," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 153-160, January.
    18. 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).
    19. 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.
    20. Hernández-Lobato, José Miguel & Suárez, Alberto, 2011. "Semiparametric bivariate Archimedean copulas," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2038-2058, June.
    21. 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.
    22. Gijbels, Irène & Veraverbeke, Noël & Omelka, Marel, 2011. "Conditional copulas, association measures and their applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1919-1932, May.
    23. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    24. Abegaz, Fentaw & Gijbels, Irène & Veraverbeke, Noël, 2012. "Semiparametric estimation of conditional copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 43-73.
    25. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    26. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    27. 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.
    28. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    29. Acar, Elif F. & Czado, Claudia & Lysy, Martin, 2019. "Flexible dynamic vine copula models for multivariate time series data," Econometrics and Statistics, Elsevier, vol. 12(C), pages 181-197.
    30. Manner, Hans & Reznikova, Olga, 2010. "Forecasting international stock market correlations: does anything beat a CCC?," Discussion Papers in Econometrics and Statistics 7/10, University of Cologne, Institute of Econometrics and Statistics.

  43. Christian M. Hafner & Oliver Linton, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Post-Print hal-00732539, HAL.

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    3. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    4. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    5. Brenda López Cabrera, & Franziska Schulz,, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers SFB649DP2013-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2011. "Multivariate Volatility Modeling of Electricity Futures," SFB 649 Discussion Papers SFB649DP2011-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    9. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    11. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    12. Yulia Kotlyarova & Marcia Schafgans & Victoria Zinde-Walsh, 2011. "Adapting Kernel Estimation to Uncertain Smoothness," Working Papers daleconwp2011-01, Dalhousie University, Department of Economics.
    13. 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.
    14. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Janeway Institute Working Papers 2206, Faculty of Economics, University of Cambridge.
    15. 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.
    16. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    17. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    18. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    19. 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.
    20. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    21. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    22. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    23. 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.
    24. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    25. 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.
    26. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Valentin Patilea & Hamdi Raïssi, 2014. "Testing Second-Order Dynamics for Autoregressive Processes in Presence of Time-Varying Variance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1099-1111, September.
    28. Quentin Giai Gianetto & Hamdi Raïssi, 2015. "Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 46-53, January.
    29. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.
    30. 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.
    31. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    32. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2021. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 224(2), pages 306-329.
    33. Feiyu Jiang & Dong Li & Ke Zhu, 2019. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Papers 1907.04147, arXiv.org, revised Oct 2020.
    34. Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," CREATES Research Papers 2017-28, Department of Economics and Business Economics, Aarhus University.
    35. 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.
    36. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  44. Hafner, C.M. & Manner, H., 2008. "Dynamic stochastic copula models: estimation, inference and applications," Research Memorandum 043, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).

    Cited by:

    1. Marimoutou, Vêlayoudom & Soury, Manel, 2015. "Energy markets and CO2 emissions: Analysis by stochastic copula autoregressive model," Energy, Elsevier, vol. 88(C), pages 417-429.
    2. Pawel Janus & Siem Jan Koopman & André Lucas, 2011. "Long Memory Dynamics for Multivariate Dependence under Heavy Tails," Tinbergen Institute Discussion Papers 11-175/2/DSF28, Tinbergen Institute.
    3. Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
    4. Sama Haddad, 2023. "Global Financial Market Integration: A Literature Survey," JRFM, MDPI, vol. 16(12), pages 1-27, November.
    5. Jia Xu & Longbing Cao, 2023. "Copula Variational LSTM for High-dimensional Cross-market Multivariate Dependence Modeling," Papers 2305.08778, arXiv.org.
    6. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
    7. David Blake & Marco Morales & Wenjun Zhu & Ken Seng Tan & Chou-Wen Wang, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 477-493, April.
    8. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    9. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    10. Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
    11. Shi Yafeng & Tao Xiangxing & Shi Yanlong & Zhu Nenghui & Ying Tingting & Peng Xun, 2020. "Can Technical Indicators Provide Information for Future Volatility: International Evidence," Journal of Systems Science and Information, De Gruyter, vol. 8(1), pages 53-66, February.
    12. Anandadeep Mandal & Sunil S. Poshakwale & Gabriel J. Power, 2021. "Do investors gain from forecasting the asymmetric return co‐movements of financial and real assets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3246-3268, July.
    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. Irving Arturo De Lira Salvatierra & Andrew J. Patton, 2013. "Dynamic Copula Models and High Frequency Data," Working Papers 13-28, Duke University, Department of Economics.
    15. Creal, Drew D. & Tsay, Ruey S., 2015. "High dimensional dynamic stochastic copula models," Journal of Econometrics, Elsevier, vol. 189(2), pages 335-345.
    16. 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).
    17. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    18. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    19. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    20. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    21. Jacek Osiewalski & Krzysztof Osiewalski, 2016. "Hybrid MSV-MGARCH Models – General Remarks and the GMSF-SBEKK Specification," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(4), pages 241-271, December.
    22. 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.
    23. Michael Stanley Smith, 2021. "Implicit Copulas: An Overview," Papers 2109.04718, arXiv.org.
    24. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    25. David Zimmer, 2015. "Time-Varying Correlation in Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 51(1), pages 86-100, July.
    26. Kreuzer, Alexander & Czado, Claudia, 2021. "Bayesian inference for a single factor copula stochastic volatility model using Hamiltonian Monte Carlo," Econometrics and Statistics, Elsevier, vol. 19(C), pages 130-150.
    27. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Efficient variational approximations for state space models," Papers 2210.11010, arXiv.org, revised Jun 2023.
    28. Kreuzer, Alexander & Dalla Valle, Luciana & Czado, Claudia, 2023. "Bayesian multivariate nonlinear state space copula models," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    29. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01821815, HAL.
    30. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.
    31. Rutger Jan Lange, 2020. "Bellman filtering for state-space models," Tinbergen Institute Discussion Papers 20-052/III, Tinbergen Institute, revised 19 May 2021.
    32. 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.
    33. Boako, Gideon & Tiwari, Aviral Kumar & Ibrahim, Muazu & Ji, Qiang, 2019. "Analysing dynamic dependence between gold and stock returns: Evidence using stochastic and full-range tail dependence copula models," Finance Research Letters, Elsevier, vol. 31(C).
    34. Yang, Bingduo & Cai, Zongwu & Hafner, Christian M. & Liu, Guannan, 2018. "Trending Mixture Copula Models with Copula Selection," IRTG 1792 Discussion Papers 2018-057, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    35. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    36. 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.
    37. Mensi, Walid & Shahzad, Syed Jawad Hussain & Hammoudeh, Shawkat & Zeitun, Rami & Rehman, Mobeen Ur, 2017. "Diversification potential of Asian frontier, BRIC emerging and major developed stock markets: A wavelet-based value at risk approach," Emerging Markets Review, Elsevier, vol. 32(C), pages 130-147.
    38. 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.
    39. Rub'en Loaiza-Maya & Michael S. Smith & Worapree Maneesoonthorn, 2017. "Time Series Copulas for Heteroskedastic Data," Papers 1701.07152, arXiv.org.
    40. Zhang, Shulin & Okhrin, Ostap & Zhou, Qian M. & Song, Peter X.-K., 2016. "Goodness-of-fit test for specification of semiparametric copula dependence models," Journal of Econometrics, Elsevier, vol. 193(1), pages 215-233.
    41. Han, Yingwei & Li, Jie, 2022. "Should investors include green bonds in their portfolios? Evidence for the USA and Europe," International Review of Financial Analysis, Elsevier, vol. 80(C).
    42. Fengler, Matthias & Okhrin, Ostap, 2012. "Realized Copula," Economics Working Paper Series 1214, University of St. Gallen, School of Economics and Political Science.
    43. Reboredo, Juan C., 2013. "Modeling EU allowances and oil market interdependence. Implications for portfolio management," Energy Economics, Elsevier, vol. 36(C), pages 471-480.
    44. Lu Yang & Jason Z. Ma & Shigeyuki Hamori, 2018. "Dependence Structures and Systemic Risk of Government Securities Markets in Central and Eastern Europe: A CoVaR-Copula Approach," Sustainability, MDPI, vol. 10(2), pages 1-23, January.
    45. Gong, Yuting & Chen, Qiang & Liang, Jufang, 2018. "A mixed data sampling copula model for the return-liquidity dependence in stock index futures markets," Economic Modelling, Elsevier, vol. 68(C), pages 586-598.
    46. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-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.
    47. Javier Ojea Ferreiro, 2018. "Contagion spillovers between sovereign and financial European sector from a Delta CoVaR approach," Documentos de Trabajo del ICAE 2018-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    48. Yasukazu Yoshizawa & Naoyuki Ishimura, 2018. "Evolution of multivariate copulas in continuous and discrete processes," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 25(1), pages 44-59, January.
    49. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
    50. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    51. Atina Ahdika & Arum Handini Primandari & Falah Novayanda Adlin, 2023. "Considering the temporal interdependence of human mobility and COVID-19 concerning Indonesia’s large-scale social distancing policies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2791-2810, June.
    52. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.
    53. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
    54. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    55. Anubha Goel & Aparna Mehra, 2019. "Analyzing Contagion Effect in Markets During Financial Crisis Using Stochastic Autoregressive Canonical Vine Model," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 921-950, March.
    56. Francesco Calvori & Drew Creal & Siem Jan Koopman & Andre Lucas, 2014. "Testing for Parameter Instability in Competing Modeling Frameworks," Tinbergen Institute Discussion Papers 14-010/IV/DSF71, Tinbergen Institute.
    57. McCausland, William & Miller, Shirley & Pelletier, Denis, 2021. "Multivariate stochastic volatility using the HESSIAN method," Econometrics and Statistics, Elsevier, vol. 17(C), pages 76-94.
    58. Mohammad Nazeri-Tahroudi & Yousef Ramezani & Carlo Michele & Rasoul Mirabbasi, 2022. "Bivariate Simulation of Potential Evapotranspiration Using Copula-GARCH Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(3), pages 1007-1024, February.
    59. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    60. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    61. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
    62. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
    63. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    64. 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.
    65. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    66. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.
    67. 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.
    68. Ping Ai & Dingbo Yuan & Chuansheng Xiong, 2018. "Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China," Sustainability, MDPI, vol. 10(7), pages 1-18, June.
    69. Bucher, Axel & Jaschke, Stefan & Wied, Dominik, 2013. "Nonparametric tests for constant tail dependence with an application to energy and finance," LIDAM Discussion Papers ISBA 2013033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  45. PREMINGER, Arie & HAFNER, Christian, 2006. "Deciding between GARCH and stochastic volatility via strong decision rules," LIDAM Discussion Papers CORE 2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Fung, Ka Wai Terence & Lau, Chi Keung Marco & Chan, Kwok Ho, 2014. "The conditional equity premium, cross-sectional returns and stochastic volatility," Economic Modelling, Elsevier, vol. 38(C), pages 316-327.
    2. Krämer, Walter & Messow, Philip, 2012. "Structural Change and Spurious Persistence in Stochastic Volatility," Ruhr Economic Papers 310, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. 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).
    4. Andrei Rusu, 2020. "Multivariate VaR: A Romanian Market study," 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. 12(1), pages 79-95, June.
    5. Będowska-Sójka, Barbara & Kliber, Agata, 2021. "Is there one safe-haven for various turbulences? The evidence from gold, Bitcoin and Ether," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    6. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    7. Ender Demir & Ka Wai Terence Fung & Zhou Lu, 2016. "Capital Asset Pricing Model and Stochastic Volatility: A Case Study of India," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(1), pages 52-65, January.
    8. Fung, Ka Wai Terence & Lau, Chi Keung Marco & Chan, Kwok Ho, 2013. "The Conditional CAPM, Cross-Section Returns and Stochastic Volatility," MPRA Paper 52469, University Library of Munich, Germany.
    9. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Messow, Philip & Krämer, Walter, 2013. "Spurious persistence in stochastic volatility," Economics Letters, Elsevier, vol. 121(2), pages 221-223.

  46. Luc, BAUWENS & C.M., HAFNER & J.V.K., ROMBOUTS, 2006. "Multivariate mixed normal conditional heteroskedasticity," Discussion Papers (ECON - Département des Sciences Economiques) 2006007, Université catholique de Louvain, Département des Sciences Economiques.

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    3. 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.
    4. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    5. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    6. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    7. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    8. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    10. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    11. 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.
    12. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Mitica Pepi, 2022. "The Impact of the Global Pandemic Crisis on East and Central EU Stock Markets," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 963-968, September.
    15. Abdelhakim Aknouche & Nadia Rabehi, 2010. "On an independent and identically distributed mixture bilinear time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 113-131, March.
    16. Rombouts, Jeroen V.K. & Stentoft, Lars, 2011. "Multivariate option pricing with time varying volatility and correlations," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2267-2281, September.
    17. Rossi, E. & Spazzini, F., 2010. "Model and distribution uncertainty in multivariate GARCH estimation: A Monte Carlo analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2786-2800, November.
    18. 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.
    19. Bentarzi, M. & Hamdi, F., 2008. "Mixture periodic autoregressive conditional heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 1-16, September.
    20. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    21. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    22. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    23. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    24. Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    25. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.
    26. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    27. 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.
    28. Anghelache, Gabriela Victoria & Kralik, Lorand Istvan & Acatrinei, Marius & Pete, Stefan, 2014. "Influence of the EU Accession Process and the Global Crisis on the CEE Stock Markets: A Multivariate Correlation Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 35-52, June.
    29. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.

  47. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Alain Hecq & Franz C. Palm & Sébastien Laurent, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Post-Print hal-01440307, HAL.
    2. Yip, Iris W.H. & So, Mike K.P., 2009. "Simplified specifications of a multivariate generalized autoregressive conditional heteroscedasticity model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(2), pages 327-340.
    3. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    4. Bojan Basrak & Danijel Krizmanić, 2015. "A Multivariate Functional Limit Theorem in Weak $$M_{1}$$ M 1 Topology," Journal of Theoretical Probability, Springer, vol. 28(1), pages 119-136, March.
    5. Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
    6. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    7. Benjamin Poignard & Manabu Asai, 2023. "High‐dimensional sparse multivariate stochastic volatility models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 4-22, January.
    8. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.
    9. Jean-Claude Hessing & Rutger-Jan Lange & Daniel Ralph, 2022. "This article establishes the Poisson optional stopping times (POST) method by Lange et al. (2020) as a near-universal method for solving liquidity-constrained American options, or, equivalently, penal," Tinbergen Institute Discussion Papers 22-007/IV, Tinbergen Institute.
    10. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    11. Resende, Paulo Angelo Alves & Dorea, Chang Chung Yu, 2016. "Model identification using the Efficient Determination Criterion," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 229-244.
    12. Avarucci, Marco & Beutner, Eric & Zaffaroni, Paolo, 2013. "On Moment Conditions For Quasi-Maximum Likelihood Estimation Of Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 29(3), pages 545-566, June.
    13. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.
    14. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2022. "Regularized estimation of high‐dimensional vector autoregressions with weakly dependent innovations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 532-557, July.
    15. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).
    16. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    17. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  48. 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.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH model," SSE/EFI Working Paper Series in Economics and Finance 0652, Stockholm School of Economics.
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    3. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    4. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    5. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    6. Wasel Shadat & Chris Orme, 2011. "An investigation of parametric tests of CCC assumption," Economics Discussion Paper Series 1109, Economics, The University of Manchester.

  49. Dick van Dijk & Haris Munandar & Christian M. Hafner, 2005. "The Euro Introduction and Non-Euro Currencies," Tinbergen Institute Discussion Papers 05-044/4, Tinbergen Institute, revised 08 Jun 2006.

    Cited by:

    1. Marie Brière & Ombretta Signori, 2009. "Do Inflation‐Linked Bonds Still Diversify?," European Financial Management, European Financial Management Association, vol. 15(2), pages 279-297, March.
    2. Christos Savva & Denise R Osborn & Len Gill, 2005. "Volatility, spillover Effects and Correlations in US and Major European Markets," Money Macro and Finance (MMF) Research Group Conference 2005 23, Money Macro and Finance Research Group.
    3. Łukasz Goczek & Dagmara Mycielska, 2014. "Monetary policy and nominal convergence in CEE countries with inflation targeting," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 38.
    4. Christos S. Savva & Denise R. Osborn & Len Gill, 2006. "Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US," Centre for Growth and Business Cycle Research Discussion Paper Series 77, Economics, The University of Manchester.
    5. Saart, Patrick W. & Xia, Yingcun, 2022. "Functional time series approach to analyzing asset returns co-movements," Journal of Econometrics, Elsevier, vol. 229(1), pages 127-151.
    6. Dao, Thong M. & McGroarty, Frank & Urquhart, Andrew, 2019. "The Brexit vote and currency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 153-164.
    7. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    8. Christos S. Savva & Denise R. Osborn & Len Gill, 2005. "Spillovers and Correlations between US and Major European Stock Markets: The Role of the Euro," Economics Discussion Paper Series 0541, Economics, The University of Manchester.
    9. Kleinbrod, Vincent M. & Li, Xiao-Ming, 2017. "Order flow and exchange rate comovement," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 199-215.
    10. Gaetano, D'Adamo, 2009. "Measuring exchange rate flexibility in Europe," MPRA Paper 26612, University Library of Munich, Germany.
    11. Savva, Christos S., 2009. "International stock markets interactions and conditional correlations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(4), pages 645-661, October.
    12. Lean, Hooi Hooi & Teng, Kee Tuan, 2013. "Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach," Economic Modelling, Elsevier, vol. 32(C), pages 333-342.
    13. Mohini GUPTA & Purwa SRIVASTAVA & Amritkant MISHRA & Malayaranjan SAHOO, 2021. "Time-varying volatility spillover of foreign exchange rate in three Asian markets: Based on DCC-GARCH approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(629), W), pages 105-120, Winter.
    14. Łukasz Goczek & Dagmara Mycielska, 2019. "Actual monetary policy independence in a small open economy: the Polish perspective," Empirical Economics, Springer, vol. 56(2), pages 499-522, February.
    15. D'Adamo, Gaetano, 2010. "Estimating Central Bank preferences in a small open economy: Sweden 1995-2009," MPRA Paper 26575, University Library of Munich, Germany.
    16. Nektarios Aslanidis & Christos S. Savva, 2011. "Are There Still Portfolio Diversification Benefits In Eastern Europe? Aggregate Versus Sectoral Stock Market Data," Manchester School, University of Manchester, vol. 79(6), pages 1323-1352, December.
    17. Kühl, Michael, 2009. "Excess comovements between the Euro/US dollar and British pound/US dollar exchange rates," University of Göttingen Working Papers in Economics 89, University of Goettingen, Department of Economics.
    18. Jessica Leutert, 2018. "The Swiss franc safety premium," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-21, December.
    19. Nicolas Koch, 2014. "Dynamic linkages among carbon, energy and financial markets: a smooth transition approach," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 715-729, March.

  50. de Boer, P.M.C. & Hafner, C.M., 2005. "Ridge regression revisited," Econometric Institute Research Papers EI 2005-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Akiko Takeda & Mahesan Niranjan & Jun-ya Gotoh & Yoshinobu Kawahara, 2013. "Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios," Computational Management Science, Springer, vol. 10(1), pages 21-49, February.

  51. Hafner, Christian M. & Herwartz, Helmut, 2004. "Testing for Causality in Variance using Multivariate GARCH Models," Economics Working Papers 2004-03, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Kurecic Petar & Kokotovic Filip, 2018. "Empirical Analysis of the Impact of Brexit Referendum and Post-Referendum Events on Selected Stock Exchange Indexes," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 7-16, June.
    2. Massimo Peri, 2017. "Climate variability and the volatility of global maize and soybean prices," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(4), pages 673-683, August.
    3. Tanin, Tauhidul Islam & Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf Mohsen & Brooks, Robert, 2022. "Risk transmission from the oil market to Islamic and conventional banks in oil-exporting and oil-importing countries," Energy Economics, Elsevier, vol. 115(C).
    4. Grydaki, Maria & Bezemer, Dirk, 2013. "The role of credit in the Great Moderation: A multivariate GARCH approach," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4615-4626.
    5. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    6. Chia-Lin Chang & Michael McAleer, 2016. "A Simple Test for Causality in Volatility," Tinbergen Institute Discussion Papers 16-094/III, Tinbergen Institute.
    7. Peri, Massimo, 2015. "Cliamte Variability and Agricultural Price volatility: the case of corn and soybeans," 2015 Conference, August 9-14, 2015, Milan, Italy 212623, International Association of Agricultural Economists.
    8. Alain Hecq & Franz C. Palm & Sébastien Laurent, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Post-Print hal-01440307, HAL.
    9. Guglielmo Maria Caporale & John Hunter & Faek Menla Ali, 2013. "On the Linkages between Stock Prices and Exchange Rates: Evidence from the Banking Crisis of 2007-2010," Discussion Papers of DIW Berlin 1289, DIW Berlin, German Institute for Economic Research.
    10. Mario Reyna Cerecero & Diana Salazar Cavazos & Héctor Salgado Banda, 2009. "La curva de rendimiento y su relación con la actividad económica: una aplicación para México," Monetaria, CEMLA, vol. 0(3), pages 297-357, octubre-d.
    11. Rituparna Sen & Anandamayee Majumdar & Shubhangi Sikaria, 2022. "Bayesian Testing of Granger Causality in Functional Time Series," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 191-210, September.
    12. Paolo Guarda & Abdelaziz Rouabah, 2015. "Is the financial sector Luxembourg?s engine of growth?," BCL working papers 97, Central Bank of Luxembourg.
    13. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2016. "The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects," The Japanese Economic Review, Springer, vol. 67(3), pages 280-294, September.
    14. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    15. Belke, Ansgar & Dubova, Irina & Osowski, Thomas, 2016. "Policy uncertainty and international financial markets: The case of Brexit," Ruhr Economic Papers 657, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    16. Agata Kliber, 2014. "The Dynamics of Sovereign Credit Default Swaps and the Evolution of the Financial Crisis in Selected Central European Economies," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 330-350, September.
    17. Gebka, Bartosz & Serwa, Dobromil, 2007. "Intra- and inter-regional spillovers between emerging capital markets around the world," Research in International Business and Finance, Elsevier, vol. 21(2), pages 203-221, June.
    18. Camacho, Maximo & Romeu, Andres & Ruiz-Marin, Manuel, 2021. "Symbolic transfer entropy test for causality in longitudinal data," Economic Modelling, Elsevier, vol. 94(C), pages 649-661.
    19. Rituparna Sen & Anandamayee Majumdar & Shubhangi Sikaria, 2021. "Bayesian Testing Of Granger Causality In Functional Time Series," Papers 2112.15315, arXiv.org.
    20. Leonardo Chaves Borges Cardoso & Maurício Vaz Lobo Bittencourt, 2016. "Price Volatility Transmission From Oil To Energy And Non-Energy Agricultural Commodities," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 181, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    21. Pablo Mendieta Ossio & Sergio Cerezo Aguirre & Javier Cossío Medinacelli, 2009. "¿La inflación está de vuelta en Sudamérica?. Choques exógenos, expectativas y credibilidad de la política monetaria," Revista de Análisis del BCB, Banco Central de Bolivia, vol. 11(1), pages 111-146, December.
    22. Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
    23. Bezemer, Dirk J & Grydaki, Maria, 2012. "Mortgage Lending and the Great moderation: a multivariate GARCH Approach," MPRA Paper 36356, University Library of Munich, Germany.
    24. Chia-Lin Chang & Michael McALeer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Tinbergen Institute Discussion Papers 18-011/III, Tinbergen Institute.
    25. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.
    26. Guillermo Benavides & Carlos Capistrán, 2009. "Una nota sobre las volatilidades de la tasa de interés y del tipo de cambio según diferentes instrumentos de política monetaria: México 1998-2008," Monetaria, CEMLA, vol. 0(3), pages 391-412, octubre-d.
    27. Warshaw, Evan, 2020. "Asymmetric volatility spillover between European equity and foreign exchange markets: Evidence from the frequency domain," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 1-14.
    28. Yuki Toyoshima, 2018. "Testing for Causality-In-Mean and Variance between the UK Housing and Stock Markets," JRFM, MDPI, vol. 11(2), pages 1-10, April.
    29. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    30. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    31. Javier Pereda, 2009. "Estimación de la curva de rendimiento para el Perú y su uso para el análisis monetario," Monetaria, CEMLA, vol. 0(3), pages 413-450, octubre-d.
    32. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    33. Matthieu Droumaguet & Tomasz Wozniak, 2012. "Bayesian Testing of Granger Causality in Markov-Switching VARs," Economics Working Papers ECO2012/06, European University Institute.
    34. Bertrand Candelon & Sessi Tokpavi, 2016. "A Nonparametric Test for Granger Causality in Distribution With Application to Financial Contagion," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 240-253, April.
    35. Bouri, Elie & Awartani, Basel & Maghyereh, Aktham, 2016. "Crude oil prices and sectoral stock returns in Jordan around the Arab uprisings of 2010," Energy Economics, Elsevier, vol. 56(C), pages 205-214.
    36. Qiang Luo & Tian Ge & Fabian Grabenhorst & Jianfeng Feng & Edmund T Rolls, 2013. "Attention-Dependent Modulation of Cortical Taste Circuits Revealed by Granger Causality with Signal-Dependent Noise," PLOS Computational Biology, Public Library of Science, vol. 9(10), pages 1-15, October.
    37. van Dieijen, M.J. & Borah, A. & Tellis, G.J. & Franses, Ph.H.B.F., 2016. "Volatility Spillovers Across User-Generated Content and Stock Market Performance," ERIM Report Series Research in Management ERS-2016-008-MKT, 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.
    38. González, Mariano, 2016. "Asymmetric causality in-mean and in-variance among equity markets indexes," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 49-68.
    39. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    40. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    41. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    42. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Exchange rate uncertainty and international portfolio flows: A multivariate GARCH-in-mean approach," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 70-92.
    43. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.
    44. Benavides Guillermo & Capistrán Carlos, 2009. "A Note on the Volatilities of the Interest Rate and the Exchange Rate Under Different Monetary Policy Instruments: Mexico 1998-2008," Working Papers 2009-10, Banco de México.

  52. Rombouts, Jeroen V. K. & Hafner, Christian M., 2004. "Semiparametric multivariate volatility models," Papers 2004,14, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. Hafner, Christian M. & Herwartz, Helmut & Maxand, Simone, 2022. "Identification of structural multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 212-227.
    2. Francq, Christian & Jiménez Gamero, Maria Dolores & Meintanis, Simos, 2015. "Tests for sphericity in multivariate garch models," MPRA Paper 67411, University Library of Munich, Germany.
    3. Gabriele Fiorentini & Enrique Sentana, 2018. "Consistent non-Gaussian pseudo maximum likelihood estimators," Working Paper series 18-06, Rimini Centre for Economic Analysis.
    4. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    5. Christian Gouriéroux & Alain Monfort & Jean-Michel Zakoian, 2018. "Consistent Pseudo-Maximum Likelihood Estimators and Groups of Transformations," Working Papers 2018-08, Center for Research in Economics and Statistics.
    6. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    7. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    8. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    9. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    10. Jeroen V.K. Rombouts & Marno Verbeek, 2004. "Evaluating Portfolio Value-at-Risk using Semi-Parametric GARCH Models," Cahiers de recherche 04-14, HEC Montréal, Institut d'économie appliquée.
    11. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    12. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    13. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    14. 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".
    15. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    17. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    18. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests for Serial Dependence in Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.

  53. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.

    Cited by:

    1. Claudio Morana & Giacomo Sbrana, 2017. "Temperature Anomalies, Radiative Forcing and ENSO," Working Papers 2017.09, Fondazione Eni Enrico Mattei.
    2. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
    3. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    4. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    5. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    6. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    7. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    8. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    9. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    10. Morana, Claudio & Sbrana, Giacomo, 2019. "Climate change implications for the catastrophe bonds market: An empirical analysis," Economic Modelling, Elsevier, vol. 81(C), pages 274-294.
    11. Sbrana, Giacomo & Poloni, Federico, 2013. "A closed-form estimator for the multivariate GARCH(1,1) model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 152-162.
    12. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    13. Babai, M. Zied & Ali, Mohammad M. & Nikolopoulos, Konstantinos, 2012. "Impact of temporal aggregation on stock control performance of intermittent demand estimators: Empirical analysis," Omega, Elsevier, vol. 40(6), pages 713-721.
    14. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    15. Apostolos Serletis & Libo Xu, "undated". "Volatility and a Century of Energy Markets Dynamics," Working Papers 2016-29, Department of Economics, University of Calgary, revised 28 Jan 2016.
    16. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.
    17. Bernd Süssmuth, 2022. "The mutual predictability of Bitcoin and web search dynamics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 435-454, April.
    18. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  54. CHEN, Rong & YANG, Lijian & HAFNER, Christian, 2004. "Nonparametric multistep-ahead prediction in time series analysis," LIDAM Reprints CORE 1783, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Souhaib Ben Taieb & Rob J Hyndman, 2012. "Recursive and direct multi-step forecasting: the best of both worlds," Monash Econometrics and Business Statistics Working Papers 19/12, Monash University, Department of Econometrics and Business Statistics.
    2. Rolf Tschernig & Lijian Yang, 2000. "Nonparametric Estimation of Generalized Impulse Response Functions," Econometric Society World Congress 2000 Contributed Papers 1417, Econometric Society.
    3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2013. "Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models," Monash Econometrics and Business Statistics Working Papers 21/13, Monash University, Department of Econometrics and Business Statistics.
    5. Cao, Yanrong & Lin, Haiqun & Wu, Tracy Z. & Yu, Yan, 2010. "Penalized spline estimation for functional coefficient regression models," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 891-905, April.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    7. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    8. Bontempi, Gianluca & Ben Taieb, Souhaib, 2011. "Conditionally dependent strategies for multiple-step-ahead prediction in local learning," International Journal of Forecasting, Elsevier, vol. 27(3), pages 689-699, July.
    9. Tracy Wu & Haiqun Lin & Yan Yu, 2011. "Single-index coefficient models for nonlinear time series," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(1), pages 37-58.
    10. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2018. "Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 88-100, January.
    11. Dimitris N. Politis & Kejin Wu, 2023. "Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence," Stats, MDPI, vol. 6(3), pages 1-29, August.
    12. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.

  55. HAFNER, Christian & ROMBOUTS, Jeroen, 2003. "Semiparametric multivariate GARCH models," LIDAM Discussion Papers CORE 2003003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Hafner, C.M. & Rombouts, J.V.K., 2004. "Estimation of temporally aggregated multivariate GARCH models," Econometric Institute Research Papers EI 2004-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  56. HAFNER, Christian & ROMBOUTS, Jeroen, 2003. "Estimation of temporally aggregated multivariate GARCH models," LIDAM Discussion Papers CORE 2003073, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
    2. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    3. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    4. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.

  57. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Mugrabi, Farah Daniela, 2023. "Detecting and dating possibly distinct structural breaks in the covariance structure of financial assets," LIDAM Discussion Papers LFIN 2023001, Université catholique de Louvain, Louvain Finance (LFIN).
    2. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.
    3. Fengler, Matthias & Polivka, Jeannine, 2022. "Structural Volatility Impulse Response Analysis," Economics Working Paper Series 2211, University of St. Gallen, School of Economics and Political Science.
    4. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    5. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    6. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
    7. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    8. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    9. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    10. Chrétien, Stéphane & Ortega, Juan-Pablo, 2014. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 210-236.
    11. Walid Ben Omrane & Christian M. Hafner, 2009. "Information Spillover, Volatility and the Currency Markets for the Binary Choice Model," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 50-62, April.
    12. Vogler, Jan & Golosnoy, Vasyl, 2023. "Unrestricted maximum likelihood estimation of multivariate realized volatility models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1063-1074.
    13. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    14. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2023. "Networks in risk spillovers: A multivariate GARCH perspective," Econometrics and Statistics, Elsevier, vol. 28(C), pages 1-29.
    15. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    16. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    17. Ling, Kai & Deb, Prokash & Li, Wenying, 2023. "Global Food Price Volatility Spillover from International to Domestic Markets," 2023 Annual Meeting, July 23-25, Washington D.C. 335869, Agricultural and Applied Economics Association.
    18. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    20. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    21. Hafner, Christian M. & Herwartz, Helmut, 2004. "Testing for Causality in Variance using Multivariate GARCH Models," Economics Working Papers 2004-03, Christian-Albrechts-University of Kiel, Department of Economics.
    22. Burda Martin, 2015. "Constrained Hamiltonian Monte Carlo in BEKK GARCH with Targeting," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 1-19, January.
    23. Massimiliano Caporin & Riccardo (Jack) Lucchetti & Giulio Palomba, 2020. "Analytical Gradients of Dynamic Conditional Correlation Models," JRFM, MDPI, vol. 13(3), pages 1-21, March.
    24. Wasel Shadat & Chris Orme, 2011. "An investigation of parametric tests of CCC assumption," Economics Discussion Paper Series 1109, Economics, The University of Manchester.
    25. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    26. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.
    27. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.
    28. Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.
    29. Gatfaoui, Hayette, 2013. "Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets," Economic Modelling, Elsevier, vol. 30(C), pages 776-791.

  58. Hafner, C.M. & Franses, Ph.H.B.F., 2003. "A generalized dynamic conditional correlation model for many asset returns," Econometric Institute Research Papers EI 2003-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    3. Amine Lahiani & Khaled Guesmi, 2014. "Commodity Price Correlation and Time varying Hedge Ratios," Working Papers 2014-142, Department of Research, Ipag Business School.
    4. Christos Savva & Denise R Osborn & Len Gill, 2005. "Volatility, spillover Effects and Correlations in US and Major European Markets," Money Macro and Finance (MMF) Research Group Conference 2005 23, Money Macro and Finance Research Group.
    5. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
    7. Billio, Monica & Caporin, Massimiliano, 2009. "A generalized Dynamic Conditional Correlation model for portfolio risk evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2566-2578.
    8. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    9. Li, Leon, 2017. "Dynamic correlations and domestic-global diversification," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 280-290.
    10. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Vargas, Gregorio A., 2008. "What Drives the Dynamic Conditional Correlation of Foreign Exchange and Equity Returns?," MPRA Paper 7174, University Library of Munich, Germany.
    12. Christos S. Savva & Denise R. Osborn & Len Gill, 2005. "Spillovers and Correlations between US and Major European Stock Markets: The Role of the Euro," Economics Discussion Paper Series 0541, Economics, The University of Manchester.
    13. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Christodoulakis, George A., 2007. "Common volatility and correlation clustering in asset returns," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1263-1284, November.
    15. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
    16. 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.
    17. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    18. Jin Guo & Tetsuji Tanaka, 2020. "Examining the determinants of global and local price passthrough in cereal markets: evidence from DCC-GJR-GARCH and panel analyses," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-22, December.
    19. Samitas, Aristeidis & Tsakalos, Ioannis, 2013. "How can a small country affect the European economy? The Greek contagion phenomenon," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 18-32.
    20. Kosater, Peter, 2006. "Cross-city hedging with weather derivatives using bivariate DCC GARCH models," Discussion Papers in Econometrics and Statistics 2/06, University of Cologne, Institute of Econometrics and Statistics.
    21. Giulio Palomba, 2008. "Multivariate GARCH models and the Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 379-413.

  59. Hafner, Christian M. & Herwartz, Helmut, 2002. "Testing for vector autoregressive dynamics under heteroskedasticity," SFB 373 Discussion Papers 2003,4, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.
    2. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  60. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Schüler, Martin & Schröder, Michael, 2003. "Systemic Risk in European Banking: Evidence from Bivariate GARCH Models," ZEW Discussion Papers 03-11, ZEW - Leibniz Centre for European Economic Research.

  61. Christian M. Hafner, 2000. "Durations, Volume and the Prediction of Financial Returns in Transaction Time," Econometric Society World Congress 2000 Contributed Papers 0599, Econometric Society.

    Cited by:

    1. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    2. Zhi-Qiang Jiang & Wei Chen & Wei-Xing Zhou, 2008. "Detrended fluctuation analysis of intertrade durations," Papers 0806.2444, arXiv.org.
    3. Luc Bauwens & Nikolaus Hautsch, 2007. "Modelling Financial High Frequency Data Using Point Processes," SFB 649 Discussion Papers SFB649DP2007-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Zhang, Yaohua & Zou, Jian & Ravishanker, Nalini & Thavaneswaran, Aerambamoorthy, 2019. "Modeling financial durations using penalized estimating functions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 145-158.
    5. Stanislav Anatolyev & Dmitry Shakin, 2006. "Trade intensity in the Russian stock market:dynamics, distribution and determinants," Working Papers w0070, New Economic School (NES).
    6. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    7. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Hafner, Christian, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," LIDAM Reprints ISBA 2012027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  62. Hafner, Christian M. & Herwartz, Helmut, 1999. "Time-varying market price of risk in the CAPM: Approaches, empirical evidence and implications," SFB 373 Discussion Papers 1999,22, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Massimiliano Caporin & Michael McAleer, 2011. "Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
    2. Anton Andriyashin & Wolfgang Härdle & Roman Timofeev, 2008. "Recursive Portfolio Selection with Decision Trees," SFB 649 Discussion Papers SFB649DP2008-009, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    4. Park, Sung Y. & Ryu, Doojin & Song, Jeongseok, 2017. "The dynamic conditional relationship between stock market returns and implied volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 638-648.
    5. Schrimpf, Andreas & Schröder, Michael & Stehle, Richard, 2006. "Evaluating conditional asset pricing models for the German stock market," ZEW Discussion Papers 06-043, ZEW - Leibniz Centre for European Economic Research.

  63. Hafner, Christian M. & Herwartz, Helmut, 1999. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," SFB 373 Discussion Papers 1999,58, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. 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.
    2. Christian Hafner, 2003. "Simple approximations for option pricing under mean reversion and stochastic volatility," Computational Statistics, Springer, vol. 18(3), pages 339-353, September.
    3. Martin, G.M. & Forbes, C.S. & Martin, V.L., 2000. "Implicit Bayesian Inference Using Option Prices," Monash Econometrics and Business Statistics Working Papers 5/00, Monash University, Department of Econometrics and Business Statistics.
    4. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    5. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    6. G.C. Lim & G.M. Martin & V.L. Martin, 2002. "Parametric Pricing of Higher Order Moments in S&P500 Options," Monash Econometrics and Business Statistics Working Papers 1/02, Monash University, Department of Econometrics and Business Statistics.
    7. Bauwens, Luc & Lubrano, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 321-342, August.
    8. Qingshuo Song & Qing Zhang, 2013. "An Optimal Pairs-Trading Rule," Papers 1302.6120, arXiv.org.
    9. Herwartz, Helmut & Reimers, Hans-Eggert, 2001. "Empirical modeling of the DEM/USD and DEM/JPY foreign exchange rate: Structural shifts in GARCH-models and their implications," SFB 373 Discussion Papers 2001,83, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. 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.
    11. 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).
    12. Carmona, Julio & León, Angel & Vaello-Sebastià, Antoni, 2012. "Does stock return predictability affect ESO fair value?," European Journal of Operational Research, Elsevier, vol. 223(1), pages 188-202.
    13. Lim, G.C. & Martin, G.M. & Martin, V.L., 2006. "Pricing currency options in the presence of time-varying volatility and non-normalities," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 291-314, July.
    14. Phong Luu & Jingzhi Tie & Qing Zhang, 2018. "A Threshold Type Policy for Trading a Mean-Reverting Asset with Fixed Transaction Costs," Risks, MDPI, vol. 6(4), pages 1-15, September.
    15. Darsinos, T. & Satchell, S.E., 2001. "Bayesian Forecasting of Options Prices: A Natural Framework for Pooling Historical and Implied Volatiltiy Information," Cambridge Working Papers in Economics 0116, Faculty of Economics, University of Cambridge.
    16. 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.
    17. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.
    18. Duy Nguyen & Jingzhi Tie & Qing Zhang, 2014. "An Optimal Trading Rule Under a Switchable Mean-Reversion Model," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 145-163, April.
    19. Joanna Górka, 2014. "Option Pricing under Sign RCA-GARCH Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 145-160.

  64. HAFNER, Christian & HERWARTZ, Helmut, 1998. "Volatility impulse response functions for multivariate GARCH models," LIDAM Discussion Papers CORE 1998047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Manuel Carlos Nogueira & Mara Madaleno, 2022. "Are Sustainability Indices Infected by the Volatility of Stock Indices? Analysis before and after the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-13, November.
    3. Luis Fernando Melo Velandia & Oscar Reinaldo Becerra Camargo, 2006. "Una aproximación a la dinámica de las tasas de interés de corto plazo en Colombia a través de modelos GARCH multivariados," Borradores de Economia 366, Banco de la Republica de Colombia.
    4. Walid Ben Omrane & Christian M. Hafner, 2009. "Information Spillover, Volatility and the Currency Markets for the Binary Choice Model," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 50-62, April.
    5. Ólan T. Henry & Nilss Olekalns & Kalvinder K. Shields, 2013. "Quantifying time variation and asymmetry in measures of covariance risk: a simulation approach," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 18, pages 457-476, Edward Elgar Publishing.
    6. Kalvinder Shields & Nilss Olekalns & Ãlan T. Henry & Chris Brooks, 2005. "Measuring the Response of Macroeconomic Uncertainty to Shocks," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 362-370, May.
    7. Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Finance," Books, Edward Elgar Publishing, number 14545.
    8. Płuciennik Piotr, 2012. "Influence of the American Financial Market on Other Markets During the Subprime Crisis," Folia Oeconomica Stetinensia, Sciendo, vol. 12(2), pages 19-30, December.
    9. E.Panopoulou & T. Pantelidis, 2005. "Integration at a cost: Evidence from volatility impulse response functions," Economics Department Working Paper Series n1540305, Department of Economics, National University of Ireland - Maynooth.
    10. Rombouts, Jeroen V. K. & Hafner, Christian M., 2004. "Semiparametric multivariate volatility models," Papers 2004,14, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    11. Olan T. Henry & Nilss Olekalns & Kalvinder Shields, 2004. "Time Variation And Asymmetry In The World Price Of Covariance Risk: The Implications For International Diversification," Department of Economics - Working Papers Series 907, The University of Melbourne.

  65. Hafner, Christian M. & Herwartz, Helmut, 1998. "Testing for linear autoregressive dynamics under heteroskedasticity," SFB 373 Discussion Papers 1999,7, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Jianqing Fan & Mingjin Wang & Qiwei Yao, 2008. "Modelling multivariate volatilities via conditionally uncorrelated components," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 679-702, September.
    2. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    3. HAFNER, Christian & HERWARTZ, Helmut, 1998. "Volatility impulse response functions for multivariate GARCH models," LIDAM Discussion Papers CORE 1998047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.
    6. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.
    7. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    8. Hafner, C.M. & Herwartz, H., 2003. "Analytical quasi maximum likelihood inference in multivariate volatility models," Econometric Institute Research Papers EI 2003-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Ruiz Ortega, Esther & Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Hafner, Christian M. & Herwartz, Helmut, 2006. "Volatility impulse responses for multivariate GARCH models: An exchange rate illustration," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 719-740, August.
    11. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
    12. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. 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.
    14. Hafner, C.M. & Herwartz, H., 2002. "Testing for vector autoregressive dynamics under heteroskedasticity," Econometric Institute Research Papers EI 2002-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Nikos S. Thomaidis & Georgios D. Dounias, 2012. "A comparison of statistical tests for the adequacy of a neural network regression model," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 437-449, October.
    16. Herwartz, Helmut, 2015. "Are GARCH innovations independent - a long term assessment for the S&P 500," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113109, Verein für Socialpolitik / German Economic Association.
    17. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    18. Hafner, C.M. & Franses, Ph.H.B.F., 2003. "A generalized dynamic conditional correlation model for many asset returns," Econometric Institute Research Papers EI 2003-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  66. HÄRDLE, Wolfgang & HAFNER, Christian, 1997. "Discrete time option pricing with flexible volatility estimation," LIDAM Discussion Papers CORE 1997047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. 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.
    2. M, El Babsiri & Jean-Michel Zakoïan, 1997. "Contemporaneous Asymmetry in GARCH Processes," Working Papers 97-03, Center for Research in Economics and Statistics.
    3. Peter Christoffersen & Kris Jacobs, 2002. "Which Volatility Model for Option Valuation?," CIRANO Working Papers 2002s-33, CIRANO.
    4. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. 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.
    18. Papantonis, Ioannis, 2016. "Volatility risk premium implications of GARCH option pricing models," Economic Modelling, Elsevier, vol. 58(C), pages 104-115.
    19. 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.
    20. 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.

  67. Hafner, C., 1997. "Estimating High Frequency Foreign Exchange Rate Volatility with Nonparametric ARCH Models," SFB 373 Discussion Papers 1997,18, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Menelaos Karanasos & J. Kim, "undated". "Moments of the ARMA-EGARCH Model," Discussion Papers 00/29, Department of Economics, University of York.
    2. Christian M. Hafner & Wolfgang HÄrdle, 2000. "Discrete time option pricing with flexible volatility estimation," Finance and Stochastics, Springer, vol. 4(2), pages 189-207.
    3. GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," LIDAM Discussion Papers CORE 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  68. 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. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
    2. 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.
    3. Nour Meddahi & Eric Renault, 1998. "Quadratic M-Estimators for ARCH-Type Processes," CIRANO Working Papers 98s-29, CIRANO.
    4. 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.
    5. 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).
    6. Christian M. Hafner & Wolfgang HÄrdle, 2000. "Discrete time option pricing with flexible volatility estimation," Finance and Stochastics, Springer, vol. 4(2), pages 189-207.
    7. 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.
    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. 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.
    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.

  69. 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. 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.
    3. 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.
    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.

Articles

  1. Hafner, Christian M. & Herwartz, Helmut & Maxand, Simone, 2022. "Identification of structural multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 212-227.
    See citations under working paper version above.
  2. Bingduo Yang & Christian M. Hafner & Guannan Liu & Wei Long, 2021. "Semiparametric estimation and variable selection for single‐index copula models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 962-988, November.
    See citations under working paper version above.
  3. Christian M. Hafner & Dimitra Kyriakopoulou, 2021. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 589-603, March.
    See citations under working paper version above.
  4. Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
    See citations under working paper version above.
  5. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
    See citations under working paper version above.
  6. Christian M Hafner, 2020. "Testing for Bubbles in Cryptocurrencies with Time-Varying Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 233-249.
    See citations under working paper version above.
  7. Fabian Y.R.P. Bocart & Eric Ghysels & Christian M. Hafner, 2020. "Monthly Art Market Returns," JRFM, MDPI, vol. 13(5), pages 1-22, May.
    See citations under working paper version above.
  8. Zhengyuan Gao & Christian M. Hafner, 2019. "Looking Backward and Looking Forward," Econometrics, MDPI, vol. 7(2), pages 1-24, June.
    See citations under working paper version above.
  9. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    See citations under working paper version above.
  10. Christian M. Hafner & Hans Manner & Léopold Simar, 2018. "The “wrong skewness” problem in stochastic frontier models: A new approach," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 380-400, April.
    See citations under working paper version above.
  11. Christian M. Hafner & Alexandre R. Lauwers, 2017. "An augmented Taylor rule for the Federal Reserve's response to asset prices," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 7(1/2), pages 115-151.
    See citations under working paper version above.
  12. Hafner, Christian M. & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The Egarch Model," Econometric Theory, Cambridge University Press, vol. 33(4), pages 1013-1038, August.
    See citations under working paper version above.
  13. Christian M. Hafner & Arie Preminger, 2017. "On Asymptotic Theory for ARCH (∞) Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 865-879, November.

    Cited by:

    1. Royer, Julien, 2023. "Conditional asymmetry in Power ARCH(∞) models," Journal of Econometrics, Elsevier, vol. 234(1), pages 178-204.
    2. Royer, Julien, 2021. "Conditional asymmetry in Power ARCH($\infty$) models," MPRA Paper 109118, University Library of Munich, Germany.
    3. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  14. Hafner, Christian M. & Laurent, Sebastien & Violante, Francesco, 2017. "Weak Diffusion Limits Of Dynamic Conditional Correlation Models," Econometric Theory, Cambridge University Press, vol. 33(3), pages 691-716, June.
    See citations under working paper version above.
  15. Breitung, Jörg & Hafner, Christian M., 2016. "A simple model for now-casting volatility series," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1247-1255.
    See citations under working paper version above.
  16. Fabian Y. R. P. Bocart & Christian M. Hafner, 2015. "Volatility of Price Indices for Heterogeneous Goods with Applications to the Fine Art Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 291-312, March.
    See citations under working paper version above.
  17. Hafner, Christian M. & Preminger, Arie, 2015. "An ARCH model without intercept," Economics Letters, Elsevier, vol. 129(C), pages 13-17.
    See citations under working paper version above.
  18. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2015. "Fair Revaluation of Wine as an Investment," Journal of Wine Economics, Cambridge University Press, vol. 10(2), pages 190-203, November.
    See citations under working paper version above.
  19. Hafner, Christian M. & Preminger, Arie, 2015. "A note on the Tobit model in the presence of a duration variable," Economics Letters, Elsevier, vol. 126(C), pages 47-50.
    See citations under working paper version above.
  20. Walid Ben Omrane & Christian Hafner, 2015. "Macroeconomic news surprises and volatility spillover in foreign exchange markets," Empirical Economics, Springer, vol. 48(2), pages 577-607, March.
    See citations under working paper version above.
  21. El Mehdi, Rachida & Hafner, Christian M., 2014. "Inference in stochastic frontier analysis with dependent error terms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 102(C), pages 104-116.
    See citations under working paper version above.
  22. Rachida El Mehdi & Christian M. Hafner, 2014. "Local Government Efficiency: The Case of Moroccan Municipalities," African Development Review, African Development Bank, vol. 26(1), pages (88-101.
    See citations under working paper version above.
  23. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    See citations under working paper version above.
  24. Michael McAleer & Christian M. Hafner, 2014. "A One Line Derivation of EGARCH," Econometrics, MDPI, vol. 2(2), pages 1-6, June.
    See citations under working paper version above.
  25. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    See citations under working paper version above.
  26. Hafner, Christian M. & Reznikova, Olga, 2012. "On the estimation of dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3533-3545.
    See citations under working paper version above.
  27. Christian M. Hafner, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1363-1379, December.
    See citations under working paper version above.
  28. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.
    See citations under working paper version above.
  29. Christian M. Hafner & Hans Manner, 2012. "Dynamic stochastic copula models: estimation, inference and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(2), pages 269-295, March.
    See citations under working paper version above.
  30. Motta, Giovanni & Hafner, Christian M. & von Sachs, Rainer, 2011. "Locally Stationary Factor Models: Identification And Nonparametric Estimation," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1279-1319, December.
    See citations under working paper version above.
  31. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    See citations under working paper version above.
  32. Hafner, Christian M. & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2609-2627, November.
    See citations under working paper version above.
  33. Hafner, Christian M. & Preminger, Arie, 2009. "Asymptotic Theory For A Factor Garch Model," Econometric Theory, Cambridge University Press, vol. 25(2), pages 336-363, April.
    See citations under working paper version above.
  34. Christian M. Hafner, 2009. "Causality and forecasting in temporally aggregated multivariate GARCH processes," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 127-146, March.

    Cited by:

    1. Hui Jun ZHANG & Jean-Marie DUFOUR & John W. GALBRAITH, 2013. "Exchange Rates and Commodity Prices : Measuring Causality at Multiple Horizons," Cahiers de recherche 14-2013, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.
    3. Omar Alejandro González Rivas, 2016. "Causalidad en Segundos Momentos: Una aplicación a la volatilidad bursátil en México, Estados Unidos y Australia," Graduate theses (Spanish) TESG 006, CIDE, División de Economía.
    4. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    5. Alexander, Carol & Rauch, Johannes, 2021. "A general property for time aggregation," European Journal of Operational Research, Elsevier, vol. 291(2), pages 536-548.

  35. Walid Ben Omrane & Christian M. Hafner, 2009. "Information Spillover, Volatility and the Currency Markets for the Binary Choice Model," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 50-62, April.

    Cited by:

    1. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    2. Ben Omrane, Walid & Hussain, Syed Mujahid, 2016. "Foreign news and the structure of co-movement in European equity markets: An intraday analysis," Research in International Business and Finance, Elsevier, vol. 37(C), pages 572-582.
    3. Stephan Schwill, 2018. "Entropy Analysis of Financial Time Series," Papers 1807.09423, arXiv.org.

  36. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.

    Cited by:

    1. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    2. Thieu, Le Quyen, 2016. "Variance targeting estimation of the BEKK-X model," MPRA Paper 75572, University Library of Munich, Germany.
    3. Hafner, Christian M. & Herwartz, Helmut & Maxand, Simone, 2022. "Identification of structural multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 212-227.
    4. Massimiliano Caporin & Michael McAleer, 2011. "Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
    5. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    6. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    7. Massimiliano Caporin & Michael McAleer, 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," KIER Working Papers 738, Kyoto University, Institute of Economic Research.
    8. Asai Manabu & So Mike K. P., 2023. "Realized BEKK-CAW Models," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 49-77, January.
    9. Fengler, Matthias & Polivka, Jeannine, 2022. "Structural Volatility Impulse Response Analysis," Economics Working Paper Series 2211, University of St. Gallen, School of Economics and Political Science.
    10. 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.
    11. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    12. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    13. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    14. Manabu Asai & Massimiliano Caporin & Michael McAleer, 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Documentos de Trabajo del ICAE 2012-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    16. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    17. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    18. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    19. Michael McAleer, 2019. "What They Did Not Tell You About Algebraic (Non-)Existence, Mathematical (IR-)Regularity and (Non-)Asymptotic Properties of the Full BEKK Dynamic Conditional Covariance Model," Documentos de Trabajo del ICAE 2019-18, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    20. Christian M. Hafner & Oliver Linton, 2009. "Efficient Estimation of a Multivariate Multiplicative Volatility Model," STICERD - Econometrics Paper Series 541, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    21. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael & Pauwels, Laurent, 2019. "Asymptotic Theory for Rotated Multivariate GARCH Models," Working Papers BAWP-2019-03, University of Sydney Business School, Discipline of Business Analytics.
    22. Barassi, Marco & Horvath, Lajos & Zhao, Yuqian, 2018. "Change Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," MPRA Paper 87837, University Library of Munich, Germany.
    23. Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    24. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2023. "Networks in risk spillovers: A multivariate GARCH perspective," Econometrics and Statistics, Elsevier, vol. 28(C), pages 1-29.
    25. Herwartz, Helmut & Roestel, Jan, 2018. "A structural approach to identify financial transmission in distinguished scenarios of crises," Economics Working Papers 2018-08, Christian-Albrechts-University of Kiel, Department of Economics.
    26. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    27. Stefano Grassi & Francesco Violante, 2021. "Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas," Working Papers 2021-05, Center for Research in Economics and Statistics.
    28. Katsiampa, Paraskevi & Yarovaya, Larisa & Zięba, Damian, 2022. "High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    29. Cheng Yu & Dong Li & Feiyu Jiang & Ke Zhu, 2023. "Matrix GARCH Model: Inference and Application," Papers 2306.05169, arXiv.org.
    30. Hafner, Christian & Herwartz, Helmut, 2022. "Asymmetric volatility impulse response functions," LIDAM Discussion Papers ISBA 2022037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    31. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    32. Herwartz Helmut & Roestel Jan, 2018. "Local/import – and foreign currency prices: inflation, uncertainty and pass through endogeneity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(3), pages 1-17, June.
    33. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    34. Resende, Paulo Angelo Alves & Dorea, Chang Chung Yu, 2016. "Model identification using the Efficient Determination Criterion," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 229-244.
    35. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    36. Chang, Jinyuan & Zhang, Henry & Yang, Lin & Yao, Qiwei, 2023. "Modelling matrix time series via a tensor CP-decomposition," LSE Research Online Documents on Economics 117644, London School of Economics and Political Science, LSE Library.
    37. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    38. Chen, Xiaohong & Huang, Zhuo & Yi, Yanping, 2021. "Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models," Journal of Econometrics, Elsevier, vol. 222(1), pages 484-501.
    39. Serletis, Apostolos & Xu, Libo, 2019. "The ethanol mandate and crude oil and biofuel agricultural commodity price dynamics," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    40. Donghang Luo & Ke Zhu & Huan Gong & Dong Li, 2020. "Testing error distribution by kernelized Stein discrepancy in multivariate time series models," Papers 2008.00747, arXiv.org.
    41. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2022. "Regularized estimation of high‐dimensional vector autoregressions with weakly dependent innovations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 532-557, July.
    42. Hetland, Simon & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2023. "Dynamic conditional eigenvalue GARCH," Journal of Econometrics, Elsevier, vol. 237(2).
    43. Thieu, Le Quyen, 2016. "Equation by equation estimation of the semi-diagonal BEKK model with covariates," MPRA Paper 75582, University Library of Munich, Germany.
    44. Cavicchioli, Maddalena, 2023. "Statistical analysis of Markov switching vector autoregression models with endogenous explanatory variables," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    45. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    46. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.
    47. Xiaohong Chen & Zhuo Huang & Yanping Yi, 2019. "Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models," Cowles Foundation Discussion Papers 2215, Cowles Foundation for Research in Economics, Yale University.
    48. Asai, Manabu, 2023. "Feasible Panel GARCH Models: Variance-Targeting Estimation and Empirical Application," Econometrics and Statistics, Elsevier, vol. 25(C), pages 23-38.
    49. Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.
    50. Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
    51. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.
    52. Hafner, Christian M. & Herwartz, Helmut, 2023. "Asymmetric volatility impulse response functions," Economics Letters, Elsevier, vol. 222(C).

  37. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.

    Cited by:

    1. Helmut Herwartz & Helmut Lütkepohl, 2011. "Generalized least squares estimation for cointegration parameters under conditional heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 281-291, May.
    2. Motegi, Kaiji & Iitsuka, Yoshitaka, 2023. "Inter-regional dependence of J-REIT stock prices: A heteroscedasticity-robust time series approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    3. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2009. "Changes in International Business Cycle Affiliations," Centre for Growth and Business Cycle Research Discussion Paper Series 132, Economics, The University of Manchester.
    4. Umairah, Fatin & Masih, Mansur, 2017. "Should the Malaysian islamic stock market investors invest in regional and international equity markets to gain portfolio diversification benefits?," MPRA Paper 82117, University Library of Munich, Germany.
    5. Bleher, Johannes & Dimpfl, Thomas, 2022. "Knitting Multi-Annual High-Frequency Google Trends to Predict Inflation and Consumption," Econometrics and Statistics, Elsevier, vol. 24(C), pages 1-26.
    6. Gbadebo A. Oladosu & Keith L. Kline & Johannes W. A. Langeveld, 2021. "Structural Break and Causal Analyses of U.S. Corn Use for Ethanol and Other Corn Market Variables," Agriculture, MDPI, vol. 11(3), pages 1-15, March.
    7. Herwartz Helmut & Roestel Jan, 2009. "Monetary Independence under Floating Exchange Rates: Evidence Based on International Breakeven Inflation Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(4), pages 1-25, September.
    8. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    9. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    10. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    11. 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.
    12. Jianlin Wang & Jiajia Zhao & Hongzhou Li, 2018. "The Electricity Consumption and Economic Growth Nexus in China: A Bootstrap Seemingly Unrelated Regression Estimator Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(4), pages 1195-1211, December.
    13. Kim, Jae H., 2014. "Testing for parameter restrictions in a stationary VAR model: A bootstrap alternative," Economic Modelling, Elsevier, vol. 41(C), pages 267-273.
    14. Shamsuddin, Abul & Kim, Jae H., 2015. "Market sentiment and the Fama–French factor premia," Economics Letters, Elsevier, vol. 136(C), pages 129-132.
    15. Catani, P.S. & Ahlgren, N.J.C., 2017. "Combined Lagrange multiplier test for ARCH in vector autoregressive models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 62-84.
    16. Ajmi, Ahdi Noomen & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sarafrazi, Soodabeh, 2014. "How strong are the causal relationships between Islamic stock markets and conventional financial systems? Evidence from linear and nonlinear tests," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 213-227.
    17. French, Jordan, 2017. "Asset pricing with investor sentiment: On the use of investor group behavior to forecast ASEAN markets," Research in International Business and Finance, Elsevier, vol. 42(C), pages 124-148.
    18. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2009. "Structural Breaks in the International Transmission of Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 119, Economics, The University of Manchester.
    19. Kim, Jae H. & Shamsuddin, Abul, 2020. "A bootstrap test for predictability of asset returns," Finance Research Letters, Elsevier, vol. 35(C).
    20. Ajay Shah & Ila Patnaik & Matthieu Stigler, 2010. "Understanding the ADR premium under market segmentation," Working Papers id:2826, eSocialSciences.
    21. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    22. Dalheimer, Bernhard & Herwartz, Helmut & Lange, Alexander, 2021. "The threat of oil market turmoils to food price stability in Sub-Saharan Africa," Energy Economics, Elsevier, vol. 93(C).
    23. Amélie Charles & Olivier Darné & Jae H Kim, 2017. "International Stock Return Predictability: Evidence from New Statistical Tests," Post-Print hal-01626101, HAL.

  38. Christian Hafner & Philip Hans Franses, 2009. "A Generalized Dynamic Conditional Correlation Model: Simulation and Application to Many Assets," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 612-631.

    Cited by:

    1. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    2. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About the Dynamic Conditional Correlation Representation," Working Papers in Economics 13/21, University of Canterbury, Department of Economics and Finance.
    3. 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.
    4. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    5. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2011. "Multivariate Volatility Modeling of Electricity Futures," SFB 649 Discussion Papers SFB649DP2011-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    7. Irfan Akbar Kazi & Suzanne Salloy, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis - From the perspective of the Credit Default Swaps’ G14 dealers," Working Papers hal-04141216, HAL.
    8. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    9. Tetsuji Tanaka & Jin Guo, 2020. "How does the self-sufficiency rate affect international price volatility transmissions in the wheat sector? Evidence from wheat-exporting countries," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    10. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    11. Irfan Akbar Kazi & Suzanne Salloy, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis - From the perspective of the Credit Default Swaps’ G14 dealers," EconomiX Working Papers 2013-6, University of Paris Nanterre, EconomiX.
    12. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," "Marco Fanno" Working Papers 0124, Dipartimento di Scienze Economiche "Marco Fanno".
    13. Suzanne Salloy & Irfan Akbar Kazi, 2013. "Contagion effect due to Lehman Brothers’ bankruptcy and the global financial crisis: From the perspective of the Credit Default Swaps’ G14 dealers," Erudite Working Paper 2013-02, Erudite.
    14. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    15. Noureldin, Diaa & Shephard, Neil & Sheppard, Kevin, 2014. "Multivariate rotated ARCH models," Scholarly Articles 34650305, Harvard University Department of Economics.
    16. Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
    17. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Hafner, C. & Reznikova, O., 2010. "On the estimation of dynamic conditional correlation models," LIDAM Discussion Papers ISBA 2010006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    20. 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).
    21. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    22. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    23. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    24. S.T. Boris Choy & Cathy W.S. Chen & Edward M.H. Lin, 2014. "Bivariate asymmetric GARCH models with heavy tails and dynamic conditional correlations," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1297-1313, July.
    25. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    26. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    27. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    28. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    29. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    30. Caporin, M. & McAleer, M.J., 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Econometric Institute Research Papers EI 2011-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    31. 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.
    32. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    33. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    34. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.
    35. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    36. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "An Alternative Approach to Measure Co-Movement between Two Time Series," Mathematics, MDPI, vol. 8(2), pages 1-24, February.
    37. Gian Piero Aielli & Massimiliano Caporin, 2015. "Dynamic Principal Components: a New Class of Multivariate GARCH Models," "Marco Fanno" Working Papers 0193, Dipartimento di Scienze Economiche "Marco Fanno".
    38. Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo, 2016. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 17-36.
    39. Saranya, K. & Prasanna, P. Krishna, 2018. "Estimating stochastic volatility with jumps and asymmetry in Asian markets," Finance Research Letters, Elsevier, vol. 25(C), pages 145-153.
    40. Irfan Akbar Kazi & Suzanne Salloy, 2014. "Dynamics in the correlations of the Credit Default Swaps’ G14 dealers: Are there any contagion effects due to Lehman Brothers’ bankruptcy and the global financial crisis?," Working Papers 2014-237, Department of Research, Ipag Business School.
    41. Mahan Tahvildari, 2021. "Forward indifference valuation and hedging of basis risk under partial information," Papers 2101.00251, arXiv.org.
    42. Adam E Clements & Ayesha Scott & Annastiina Silvennoinen, 2012. "Forecasting multivariate volatility in larger dimensions: some practical issues," NCER Working Paper Series 80, National Centre for Econometric Research.
    43. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.

  39. Christian Hafner & Helmut Herwartz, 2008. "Analytical quasi maximum likelihood inference in multivariate volatility models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(2), pages 219-239, March.
    See citations under working paper version above.
  40. Christian M. Hafner & Helmut Herwartz, 2008. "Testing for Causality in Variance Usinf Multivariate GARCH Models," Annals of Economics and Statistics, GENES, issue 89, pages 215-241.
    See citations under working paper version above.
  41. Hafner, Christian M., 2008. "Temporal aggregation of multivariate GARCH processes," Journal of Econometrics, Elsevier, vol. 142(1), pages 467-483, January.
    See citations under working paper version above.
  42. Hafner, Christian M. & Rombouts, Jeroen V.K., 2007. "Semiparametric Multivariate Volatility Models," Econometric Theory, Cambridge University Press, vol. 23(2), pages 251-280, April.
    See citations under working paper version above.
  43. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    See citations under working paper version above.
  44. Hafner, Christian M. & Herwartz, Helmut, 2006. "Volatility impulse responses for multivariate GARCH models: An exchange rate illustration," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 719-740, August.

    Cited by:

    1. Massimo Peri, 2017. "Climate variability and the volatility of global maize and soybean prices," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(4), pages 673-683, August.
    2. Quentin LAJAUNIE, 2021. "Nonlinear Impulse Response Function for Dichotomous Models," LEO Working Papers / DR LEO 2852, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    3. Yannick LE PEN & Benoît SEVI, 2008. "Volatility transmission and volatility impulse response functions in European electricity forward markets," Cahiers du CREDEN (CREDEN Working Papers) 08.09.77, CREDEN (Centre de Recherche en Economie et Droit de l'Energie), Faculty of Economics, University of Montpellier 1.
    4. Hafner, Christian M. & Herwartz, Helmut, 2022. "Dynamic score driven independent component analysis," LIDAM Reprints ISBA 2022010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Hafner, Christian M. & Herwartz, Helmut & Maxand, Simone, 2022. "Identification of structural multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 212-227.
    6. David Gabauer, 2020. "Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 788-796, August.
    7. Ahdi N. Ajmi & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2014. "Real Estate Markets and Uncertainty Shocks: A Variance Causality Approach," Working Papers 201436, University of Pretoria, Department of Economics.
    8. John Francis Diaz & Peh Ying Qian & Genevieve Liao Tan, 2018. "Variance Persistence in the Greater China Region: A Multivariate GARCH Approach," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 23(2), pages 49-68, July-Dec.
    9. Kawakatsu Hiroyuki, 2021. "Simple Multivariate Conditional Covariance Dynamics Using Hyperbolically Weighted Moving Averages," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 33-52, January.
    10. Gökhan Cebiroğlu & Kujtim Avdiu & Stephan Unger, 2022. "On the dynamic price pass-through effect of commodities to CPI constituents," SN Business & Economics, Springer, vol. 2(3), pages 1-12, March.
    11. Balcilar, Mehmet & Hammoudeh, Shawkat & Toparli, Elif Akay, 2018. "On the risk spillover across the oil market, stock market, and the oil related CDS sectors: A volatility impulse response approach," Energy Economics, Elsevier, vol. 74(C), pages 813-827.
    12. Peri, Massimo, 2015. "Cliamte Variability and Agricultural Price volatility: the case of corn and soybeans," 2015 Conference, August 9-14, 2015, Milan, Italy 212623, International Association of Agricultural Economists.
    13. Fengler, Matthias & Polivka, Jeannine, 2022. "Structural Volatility Impulse Response Analysis," Economics Working Paper Series 2211, University of St. Gallen, School of Economics and Political Science.
    14. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    15. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
    16. Funke, Michael & Loermann, Julius & Tsang, Andrew, 2020. "Volatility transmission and volatility impulse response functions in the main and the satellite Renminbi exchange rate markets," BOFIT Discussion Papers 22/2020, Bank of Finland Institute for Emerging Economies (BOFIT).
    17. Massimiliano Marzo & Paolo Zagaglia, 2010. "Gold and the U.S. Dollar: Tales from the Turmoil," Working Paper series 08_10, Rimini Centre for Economic Analysis.
    18. Nikos Nomikos & Enrique Salvador, 2014. "The role of volatility regimes on volatility transmission patterns," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 1-13, January.
    19. David E. Allen & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2015. "Multivariate Volatility Impulse Response Analysis of GFC News Events," Documentos de Trabajo del ICAE 2015-10, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    20. Spargoli, Fabrizio & Zagaglia, Paolo, 2008. "The co-movements along the forward curve of natural gas futures: a structural view," Bank of Finland Research Discussion Papers 26/2008, Bank of Finland.
    21. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
    22. Herwartz, Helmut & Roestel, Jan, 2022. "Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    23. Belke, Ansgar & Dubova, Irina & Osowski, Thomas, 2016. "Policy uncertainty and international financial markets: The case of Brexit," Ruhr Economic Papers 657, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    24. Li, Hong, 2020. "Volatility spillovers across European stock markets under the uncertainty of Brexit," Economic Modelling, Elsevier, vol. 84(C), pages 1-12.
    25. Pilar Gargallo & Luis Lample & Jesús A. Miguel & Manuel Salvador, 2021. "Co-Movements between Eu Ets and the Energy Markets: A Var-Dcc-Garch Approach," Mathematics, MDPI, vol. 9(15), pages 1-36, July.
    26. Yan, Guan & Trück, Stefan, 2020. "A dynamic network analysis of spot electricity prices in the Australian national electricity market," Energy Economics, Elsevier, vol. 92(C).
    27. Oscar Becerra & Luis Fernando Melo, 2008. "Transmisión de tasas de interés bajo el esquema de metas de inflación: evidencia para Colombia," Borradores de Economia 519, Banco de la Republica de Colombia.
    28. Jin, Xiaoye & An, Ximeng, 2016. "Global financial crisis and emerging stock market contagion: A volatility impulse response function approach," Research in International Business and Finance, Elsevier, vol. 36(C), pages 179-195.
    29. Ginny ju-ann Yang & Koyin Chang & Yung-Hsiang Ying & Chen-hsun Lee, 2014. "Spillover Effects of Chinese Stock Markets," Economics Bulletin, AccessEcon, vol. 34(1), pages 200-205.
    30. Jin, Xiaoye & Xiaowen Lin, Sharon & Tamvakis, Michael, 2012. "Volatility transmission and volatility impulse response functions in crude oil markets," Energy Economics, Elsevier, vol. 34(6), pages 2125-2134.
    31. Andreas Masuhr, 2019. "Big in Japan: Global Volatility Transmission between Assets and Trading Places," CQE Working Papers 8119, Center for Quantitative Economics (CQE), University of Muenster.
    32. Teterin, Pavel & Brooks, Robert & Enders, Walter, 2016. "Smooth volatility shifts and spillovers in U.S. crude oil and corn futures markets," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 22-36.
    33. Makushkin, Mikhail & Lapshin, Victor, 2020. "Modelling tail dependencies between Russian and foreign stock markets: Application for market risk valuation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 30-52.
    34. Henry, Ólan & Olekalns, Nilss & Shields, Kalvinder, 2010. "Sign and phase asymmetry: News, economic activity and the stock market," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 1083-1100, December.
    35. Baldi, Lucia & Peri, Massimo & Vandone, Daniela, 2016. "Stock markets’ bubbles burst and volatility spillovers in agricultural commodity markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 277-285.
    36. Assefa, Tsion & Meuwissen, Miranda & Lansink, Alfons G.J.M., 2015. "Food scares and price volatility: the case of German and Spanish pig chains," 2015 Conference, August 9-14, 2015, Milan, Italy 210966, International Association of Agricultural Economists.
    37. BenSaïda, Ahmed & Litimi, Houda & Abdallah, Oussama, 2018. "Volatility spillover shifts in global financial markets," Economic Modelling, Elsevier, vol. 73(C), pages 343-353.
    38. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
    39. Herwartz, Helmut & Roestel, Jan, 2018. "A structural approach to identify financial transmission in distinguished scenarios of crises," Economics Working Papers 2018-08, Christian-Albrechts-University of Kiel, Department of Economics.
    40. Olson, Eric & J. Vivian, Andrew & Wohar, Mark E., 2014. "The relationship between energy and equity markets: Evidence from volatility impulse response functions," Energy Economics, Elsevier, vol. 43(C), pages 297-305.
    41. Alessandra Amendola & Marinella Boccia & Vincenzo Candila & Giampiero M. Gallo, 2020. "Energy and non–energy Commodities: Spillover Effects on African Stock Markets," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-7.
    42. Vincenzo Candila & Salvatore Farace, 2018. "On the Volatility Spillover between Agricultural Commodities and Latin American Stock Markets," Risks, MDPI, vol. 6(4), pages 1-16, October.
    43. Gustavo Cabrera González & Adrián de León Arias, 2021. "Dinámica anticipada del PIB trimestral en México ante shocks negativos derivados de factores debidos a la crisis sanitaria del covid-19," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(1), pages 1-15, Enero - M.
    44. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    45. BenSaïda, Ahmed, 2019. "Good and bad volatility spillovers: An asymmetric connectedness," Journal of Financial Markets, Elsevier, vol. 43(C), pages 78-95.
    46. Gormus, N. Alper & Atinc, Guclu, 2016. "Volatile oil and the U.S. economy," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 62-73.
    47. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2021. "Political uncertainty, COVID-19 pandemic and stock market volatility transmission," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    48. I-Chun Tsai & Shu-Hen Chiang, 2018. "Risk Transfer among Housing Markets in Major Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
    49. Anthony N. Rezitis & Shaikh Mostak Ahammad, 2016. "Investigating The Interdependency Of Agricultural Production Volatility Spillovers Between Bangladesh, India, And Pakistan," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 28(1), pages 32-54, March.
    50. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    51. Hafner, Christian & Herwartz, Helmut, 2022. "Asymmetric volatility impulse response functions," LIDAM Discussion Papers ISBA 2022037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    52. Hiroyuki Kawakatsu, 2022. "Local projection variance impulse response," Empirical Economics, Springer, vol. 62(3), pages 1219-1244, March.
    53. Pami Dua & Ritu Suri, 2019. "Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1_suppl), pages 102-136, April.
    54. Herwartz Helmut & Roestel Jan, 2018. "Local/import – and foreign currency prices: inflation, uncertainty and pass through endogeneity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(3), pages 1-17, June.
    55. Liu, Xiaochun, 2021. "On fiscal and monetary policy-induced macroeconomic volatility dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    56. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    57. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    58. Liu, Pan & Power, Gabriel J. & Vedenov, Dmitry, 2021. "Fair-weather Friends? Sector-specific volatility connectedness and transmission," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 712-736.
    59. Ahmed H. Elsayed & Gareth Downing & Chi Keung Marco Lau & Xin Sheng, 2024. "Exploring the role of oil shocks on the financial stability of Gulf Cooperation Council countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1804-1819, April.
    60. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    61. Luca Barbaglia & Christophe Croux & Ines Wilms, 2017. "Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach," Papers 1708.02073, arXiv.org.
    62. Ceballos, Francisco & Hernandez, Manuel A. & Minot, Nicholas & Robles, Miguel, 2017. "Grain Price and Volatility Transmission from International to Domestic Markets in Developing Countries," World Development, Elsevier, vol. 94(C), pages 305-320.
    63. Yu, Mengyan & Umair, Muhammad & Oskenbayev, Yessengali & Karabayeva, Zhаnsaya, 2023. "Exploring the nexus between monetary uncertainty and volatility in global crude oil: A contemporary approach of regime-switching," Resources Policy, Elsevier, vol. 85(PB).
    64. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    65. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    66. Yang, Yao & Karali, Berna, 2022. "How far is too far for volatility transmission?," Journal of Commodity Markets, Elsevier, vol. 26(C).
    67. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    68. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    69. Tunahan Yilmaz, 2021. "Optimal Dynamic Hedging in Selected Markets," International Econometric Review (IER), Econometric Research Association, vol. 13(4), pages 89-117, December.
    70. Surathkal, Prasanna & Omana Sudhakaran, Pratheesh & Dey, Madan M., 2021. "Dynamics of Price Volatility Spillover in the U.S. Cat_x001C_fish Market," 2021 Annual Meeting, August 1-3, Austin, Texas 314069, Agricultural and Applied Economics Association.
    71. van Dieijen, M.J. & Borah, A. & Tellis, G.J. & Franses, Ph.H.B.F., 2016. "Volatility Spillovers Across User-Generated Content and Stock Market Performance," ERIM Report Series Research in Management ERS-2016-008-MKT, 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.
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    1. Alper Gormus & Saban Nazlioglu & Steven L. Beach, 2023. "Environmental, Social, and Governance Considerations in WTI Financialization through Energy Funds," JRFM, MDPI, vol. 16(4), pages 1-17, April.
    2. Jianqing Fan & Mingjin Wang & Qiwei Yao, 2008. "Modelling multivariate volatilities via conditionally uncorrelated components," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 679-702, September.
    3. Elsayed, Ahmed H. & Gozgor, Giray & Lau, Chi Keung Marco, 2022. "Risk transmissions between bitcoin and traditional financial assets during the COVID-19 era: The role of global uncertainties," International Review of Financial Analysis, Elsevier, vol. 81(C).
    4. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Tinbergen Institute Discussion Papers 17-051/III, Tinbergen Institute.
    5. Ahdi N. Ajmi & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2014. "Real Estate Markets and Uncertainty Shocks: A Variance Causality Approach," Working Papers 201436, University of Pretoria, Department of Economics.
    6. Chia-Lin Chang & Michael McAleer, 2016. "A Simple Test for Causality in Volatility," Tinbergen Institute Discussion Papers 16-094/III, Tinbergen Institute.
    7. Krzysztof Drachal, 2018. "Exchange Rate and Oil Price Interactions in Selected CEE Countries," Economies, MDPI, vol. 6(2), pages 1-21, May.
    8. Dennis Bergmann & Declan O’Connor & Andreas Thümmel, 2016. "An analysis of price and volatility transmission in butter, palm oil and crude oil markets," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 4(1), pages 1-23, December.
    9. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2015. "Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4996-5011, October.
    10. Gülin Vardar & Yener Coşkun & Tezer Yelkenci, 2018. "Shock transmission and volatility spillover in stock and commodity markets: evidence from advanced and emerging markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 8(2), pages 231-288, August.
    11. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    12. Nouira, Ridha & Hadj Amor, Thouraya & Rault, Christophe, 2019. "Oil price fluctuations and exchange rate dynamics in the MENA region: Evidence from non-causality-in-variance and asymmetric non-causality tests," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 159-171.
    13. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    14. Vo, D.H. & Vu, T.N. & Vo, A.T. & McAleer, M.J., 2018. "Modelling the Relationship between Crude Oil and Agricultural Commodity Prices," Econometric Institute Research Papers EI2019-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Ordu-Akkaya, Beyza Mina & Soytas, Ugur, 2020. "Does foreign portfolio investment strengthen stock-commodity markets connection?," Resources Policy, Elsevier, vol. 65(C).
    16. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    17. Monia Ben Latifa & Walid Khoufi, 2018. "Contagion between Islamic and Conventional Banks in Malaysia: Empirical Investigation using a DCC-GARCH Model العدوى بين البنوك الإسلامية والتقليدية في ماليزيا: تحقيق تجريبي بواسطة نموذج (DCC-GARCH)," Journal of King Abdulaziz University: Islamic Economics, King Abdulaziz University, Islamic Economics Institute., vol. 31(1), pages 167-178, January.
    18. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    19. Belke, Ansgar & Dubova, Irina & Osowski, Thomas, 2016. "Policy uncertainty and international financial markets: The case of Brexit," Ruhr Economic Papers 657, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    20. Mensi, Walid & Rehman, Mobeen Ur & Maitra, Debasish & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2023. "Frequency spillovers and portfolio risk implications between Sukuk, Islamic stock and emerging stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 91(C), pages 139-157.
    21. Yıldırım, Durmuş Çağrı & Esen, Ömer & Ertuğrul, Hasan Murat, 2022. "Impact of the COVID-19 pandemic on return and risk transmission between oil and precious metals: Evidence from DCC-GARCH model," Resources Policy, Elsevier, vol. 79(C).
    22. Korkmaz, Turhan & Çevik, Emrah İ. & Atukeren, Erdal, 2012. "Return and volatility spillovers among CIVETS stock markets," Emerging Markets Review, Elsevier, vol. 13(2), pages 230-252.
    23. Hkiri, Besma & Hammoudeh, Shawkat & Aloui, Chaker & Yarovaya, Larisa, 2017. "Are Islamic indexes a safe haven for investors? An analysis of total, directional and net volatility spillovers between conventional and Islamic indexes and importance of crisis periods," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 124-150.
    24. Yıldırım, Durmuş Çağrı & Cevik, Emrah Ismail & Esen, Ömer, 2020. "Time-varying volatility spillovers between oil prices and precious metal prices," Resources Policy, Elsevier, vol. 68(C).
    25. Tiwari, Aviral Kumar & Cunado, Juncal & Gupta, Rangan & Wohar, Mark E., 2018. "Volatility spillovers across global asset classes: Evidence from time and frequency domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 194-202.
    26. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Econometric Institute Research Papers EI2016-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    27. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn," Documentos de Trabajo del ICAE 2016-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    28. Kassouri, Yacouba & Altıntaş, Halil, 2020. "Commodity terms of trade shocks and real effective exchange rate dynamics in Africa's commodity-exporting countries," Resources Policy, Elsevier, vol. 68(C).
    29. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    30. Bouri, Elie & de Boyrie, Maria E. & Pavlova, Ivelina, 2017. "Volatility transmission from commodity markets to sovereign CDS spreads in emerging and frontier countries," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 155-165.
    31. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    32. Dibooglu, Sel & Cevik, Emrah I. & Gillman, Max, 2022. "Gold, silver, and the US dollar as harbingers of financial calm and distress," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 200-210.
    33. Saban Nazlioglu & Rangan Gupta & Elie Bouri, 2019. "Movements in International Bond Markets: The Role of Oil Prices," Working Papers 201935, University of Pretoria, Department of Economics.
    34. Nazlioglu, Saban & Soytas, Ugur & Gupta, Rangan, 2015. "Oil prices and financial stress: A volatility spillover analysis," Energy Policy, Elsevier, vol. 82(C), pages 278-288.
    35. Alper Gormus, N., 2016. "Do different time-horizons in volatility have any significance for the emerging markets?," Economics Letters, Elsevier, vol. 145(C), pages 29-32.
    36. Aromi, Daniel & Clements, Adam, 2019. "Spillovers between the oil sector and the S&P500: The impact of information flow about crude oil," Energy Economics, Elsevier, vol. 81(C), pages 187-196.
    37. Saban Nazlioglu & Rangan Gupta & Alper Gormus & Ugur Soytas, 2019. "Price and Volatility Linkages between International REITs and Oil Markets," Working Papers 201954, University of Pretoria, Department of Economics.
    38. Walid Mensi & Shawkat Hammoudeh & Duc Khuong Nguyen & Seong-Min Yoon, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Working Papers 2014-160, Department of Research, Ipag Business School.
    39. Mehmet Balcilar & Riza Demirer & Rangan Gupta, 2016. "Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations," Working Papers 201609, University of Pretoria, Department of Economics.
    40. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2020. "Time-Varying Causality between Bond and Oil Markets of the United States: Evidence from Over One and Half Centuries of Data," Working Papers 202006, University of Pretoria, Department of Economics.
    41. Nazlioglu, Saban & Gormus, N. Alper & Soytas, Uğur, 2016. "Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis," Energy Economics, Elsevier, vol. 60(C), pages 168-175.
    42. Jian Zhang & Dongxiang Zhang & Juan Wang & Yue Zhang, 2013. "Volatility Spillovers between Equity and Bond Markets: Evidence from G7 and BRICS," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 205-217, December.
    43. Ahmed H. Elsayed & Gareth Downing & Chi Keung Marco Lau & Xin Sheng, 2024. "Exploring the role of oil shocks on the financial stability of Gulf Cooperation Council countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1804-1819, April.
    44. Olson, Eric & Miller, Scott & Wohar, Mark E., 2012. "“Black Swans” before the “Black Swan” evidence from international LIBOR–OIS spreads," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1339-1357.
    45. Soylu, Pınar Kaya & Güloğlu, Bülent, 2019. "Financial contagion and flight to quality between emerging markets and U.S. bond market," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    46. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    47. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2015. "A Wavelet-based MRA-EDCC-GARCH Methodology for the Detection of News and Volatility Spillover across Sectoral Indices—Evidence from the Indian Financial Market," Global Business Review, International Management Institute, vol. 16(1), pages 35-49, February.
    48. Bouri, Elie, 2015. "Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis," Energy Economics, Elsevier, vol. 51(C), pages 590-598.
    49. Muhammad Irfan Malik & Abdul Rashid, 2017. "Return And Volatility Spillover Between Sectoral Stock And Oil Price: Evidence From Pakistan Stock Exchange," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-22, June.
    50. Belasen, Ariel R. & Demirer, Rıza, 2019. "Commodity-currencies or currency-commodities: Evidence from causality tests," Resources Policy, Elsevier, vol. 60(C), pages 162-168.
    51. Elie Bouri & Riza Demirer, 2016. "On the volatility transmission between oil and stock markets: a comparison of emerging importers and exporters," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(1), pages 63-82, April.
    52. Bouri, Elie, 2015. "A broadened causality in variance approach to assess the risk dynamics between crude oil prices and the Jordanian stock market," Energy Policy, Elsevier, vol. 85(C), pages 271-279.
    53. Alper Gormus & Ugur Soytas, 2023. "Financial Sector Troubles and Energy Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 357-363, March.
    54. Mustafa Okur & Emrah Cevik, 2013. "Testing Intraday Volatility Spillovers in Turkish Capital Markets: Evidence from Ise," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 26(3), pages 99-116, January.
    55. Siami-Namini, Sima & Hudson, Darren, 2017. "Volatility Spillover Between Oil Prices, Us Dollar Exchange Rates And International Agricultural Commodities Prices," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252845, Southern Agricultural Economics Association.
    56. Adekunle, Salami Saheed & Masih, Mansur, 2017. "Assessing the viability of Sukuk for portfolio diversification using MS-DCC-GARCH," MPRA Paper 79443, University Library of Munich, Germany.
    57. Cevik, Nuket Kirci & Cevik, Emrah I. & Dibooglu, Sel, 2020. "Oil prices, stock market returns and volatility spillovers: Evidence from Turkey," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 597-614.
    58. Guo, Shaojun & Ling, Shiqing & Zhu, Ke, 2013. "Factor double autoregressive models with application to simultaneous causality testing," MPRA Paper 51570, University Library of Munich, Germany.
    59. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    60. Jahan-Parvar, Mohammad R. & Mohammadi, Hassan, 2013. "Risk and return in the Tehran stock exchange," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(3), pages 238-256.
    61. Sinem Derindere KOSEOGLU & Emrah Ismail CEVIK, 2013. "Testing for Causality in Mean and Variance between the Stock Market and the Foreign Exchange Market: An Application to the Major Central and Eastern European Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(1), pages 65-86, March.
    62. Wilson Donzwa & Rangan Gupta & Mark E. Wohar, 2017. "Volatility Spillovers between Interest Rates and Equity Markets of Developed Economies: A Note," Working Papers 201764, University of Pretoria, Department of Economics.
    63. Ho, Liang-Chun & Huang, Chia-Hsing, 2015. "The nonlinear relationships between stock indexes and exchange rates," Japan and the World Economy, Elsevier, vol. 33(C), pages 20-27.
    64. Gormus, N. Alper & Soytas, Ugur & Diltz, J. David, 2014. "Volatility transmission between energy-related asset classes," Global Finance Journal, Elsevier, vol. 25(3), pages 246-259.
    65. Güloğlu, Bülent & Kaya, Pınar & Aydemir, Resul, 2016. "Volatility transmission among Latin American stock markets under structural breaks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 330-340.
    66. Gormus, Alper & Nazlioglu, Saban & Soytas, Ugur, 2018. "High-yield bond and energy markets," Energy Economics, Elsevier, vol. 69(C), pages 101-110.

  46. 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.
    See citations under working paper version above.
  47. Paul M. C. de Boer & Christian M. Hafner, 2005. "Ridge regression revisited," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 498-505, November.
    See citations under working paper version above.
  48. Rong Chen & Lijian Yang & Christian Hafner, 2004. "Nonparametric multistep‐ahead prediction in time series analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 669-686, August.
    See citations under working paper version above.
  49. Christian M. Hafner, 2003. "Fourth Moment Structure of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 26-54.

    Cited by:

    1. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    2. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    3. Boussama, Farid & Fuchs, Florian & Stelzer, Robert, 2011. "Stationarity and geometric ergodicity of BEKK multivariate GARCH models," Stochastic Processes and their Applications, Elsevier, vol. 121(10), pages 2331-2360, October.
    4. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.
    5. Christian M. Hafner & Sébastien Laurent & Francesco Violante, 2017. "Weak Diffusion Limits of Dynamic Conditional Correlation Models," Post-Print hal-01590010, HAL.
    6. Todd, Prono, 2010. "Simple GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 20034, University Library of Munich, Germany.
    7. Hafner, C.M. & Rombouts, J.V.K., 2004. "Estimation of temporally aggregated multivariate GARCH models," Econometric Institute Research Papers EI 2004-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    9. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    10. Todd Prono, 2009. "Market proxies, correlation, and relative mean-variance efficiency: still living with the roll critique," Supervisory Research and Analysis Working Papers QAU09-3, Federal Reserve Bank of Boston.
    11. Manabu Asai & Chia-Lin Chang & Michael McAleer & Laurent Pauwels, 2021. "Asymptotic and Finite Sample Properties for Multivariate Rotated GARCH Models," Econometrics, MDPI, vol. 9(2), pages 1-21, May.
    12. Theologos Pantelidis & Nikitas Pittis, 2009. "Estimation and forecasting in first-order vector autoregressions with near to unit roots and conditional heteroscedasticity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 612-630.
    13. Hafner, Christian M. & Herwartz, Helmut, 2006. "Volatility impulse responses for multivariate GARCH models: An exchange rate illustration," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 719-740, August.
    14. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    15. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    16. Pape, Katharina & Wied, Dominik & Galeano, Pedro, 2016. "Monitoring multivariate variance changes," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 54-68.
    17. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    18. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    19. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    20. Todd Prono, 2008. "GARCH-based identification and estimation of triangular systems," Supervisory Research and Analysis Working Papers QAU08-4, Federal Reserve Bank of Boston.
    21. E.Panopoulou & T. Pantelidis, 2005. "Integration at a cost: Evidence from volatility impulse response functions," Economics Department Working Paper Series n1540305, Department of Economics, National University of Ireland - Maynooth.
    22. Yongning Wang & Ruey S. Tsay, 2013. "On Diagnostic Checking of Vector ARMA-GARCH Models with Gaussian and Student-t Innovations," Econometrics, MDPI, vol. 1(1), pages 1-31, April.
    23. Billio, Monica & Caporin, Massimiliano & Frattarolo, Lorenzo & Pelizzon, Loriana, 2023. "Networks in risk spillovers: A multivariate GARCH perspective," Econometrics and Statistics, Elsevier, vol. 28(C), pages 1-29.
    24. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
    25. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    26. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    27. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.
    28. Sbrana, Giacomo & Poloni, Federico, 2013. "A closed-form estimator for the multivariate GARCH(1,1) model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 152-162.
    29. Giovanni Calice & Christos Ioannidis & Julian Williams, 2012. "Credit Derivatives and the Default Risk of Large Complex Financial Institutions," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 85-107, October.
    30. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    31. Peter A. Zadrozny, 2005. "Necessary and Sufficient Restrictions for Existence of a Unique Fourth Moment of a Univariate GARCH(p,q) Process," CESifo Working Paper Series 1505, CESifo.
    32. Hafner, Christian M. & Herwartz, Helmut, 2004. "Testing for Causality in Variance using Multivariate GARCH Models," Economics Working Papers 2004-03, Christian-Albrechts-University of Kiel, Department of Economics.
    33. Massimiliano Caporin, 2007. "Variance (Non) Causality in Multivariate GARCH," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 1-24.
    34. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    36. Arismendi, J.C., 2013. "Multivariate truncated moments," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 41-75.
    37. Anatolyev Stanislav, 2019. "Volatility filtering in estimation of kurtosis (and variance)," Dependence Modeling, De Gruyter, vol. 7(1), pages 1-23, February.
    38. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    39. Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.
    40. Quatto, Piero & Vacca, Gianmarco & Zoia, Maria Grazia, 2021. "A new copula for modeling portfolios with skewed, leptokurtic and high-order dependent risk factors," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    41. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    42. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto Calogero, 2017. "Estimation and model-based combination of causality networks," SAFE Working Paper Series 165, Leibniz Institute for Financial Research SAFE.

  50. 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.
    See citations under working paper version above.
  51. Christian M. Hafner & Helmut Herwartz, 2000. "Testing for linear autoregressive dynamics under heteroskedasticity," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 177-197.
    See citations under working paper version above.
  52. Christian M. Hafner & Wolfgang HÄrdle, 2000. "Discrete time option pricing with flexible volatility estimation," Finance and Stochastics, Springer, vol. 4(2), pages 189-207.
    See citations under working paper version above.
  53. C. M. Hafner & H. Herwartz, 1998. "Structural analysis of portfolio risk using beta impulse response functions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(3), pages 336-355, November.

    Cited by:

    1. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Wolfgang Haerdle & Helmut Herwartz & Volodia Spokoiny, 2000. "Time Inhomogeneous Multiple Volatility Modelling," Econometric Society World Congress 2000 Contributed Papers 1429, Econometric Society.
    3. Herwartz, H. & Lütkepohl, H., 1998. "Multivariate Volatility Analysis of VW Stock Prices," SFB 373 Discussion Papers 1998,32, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. 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.
    5. Hafner, Christian M. & Herwartz, Helmut, 2004. "Testing for Causality in Variance using Multivariate GARCH Models," Economics Working Papers 2004-03, Christian-Albrechts-University of Kiel, Department of Economics.
    6. Jelena Z. Minović & Boško R. Živković, 2010. "Open Issues In Testing Liquidity In Frontier Financial Markets: The Case Of Serbia," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 55(185), pages 33-62, April - J.
    7. Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020. "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 387-414, September.

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