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Robert Jung

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Roman Liesenfeld & Robert C. Jung, 2000. "Stochastic volatility models: conditional normality versus heavy-tailed distributions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 137-160.

    Mentioned in:

    1. Stochastic volatility models: conditional normality versus heavy-tailed distributions (Journal of Applied Econometrics 2000) in ReplicationWiki ()

Working papers

  1. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tübingen Working Papers in Business and Economics 24, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.

    Cited by:

    1. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    2. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    3. Wen-Yuan Lin & I-Chun Tsai, 2016. "Asymmetric Fluctuating Behavior of China's Housing Prices," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 24(2), pages 107-126, March.
    4. Alexander Blasberg & Rüdiger Kiesel & Luca Taschini, 2022. "Carbon Default Swap - Disentangling the Exposure to Carbon Risk through CDS," CESifo Working Paper Series 10016, CESifo.
    5. Katarzyna Bien-Barkowska, 2012. ""Does it take volume to move fx rates?" Evidence from quantile regressions," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 35-52.
    6. Jenq-Tzong Shiau & Jia-Wei Lin, 2016. "Clustering Quantile Regression-Based Drought Trends in Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1053-1069, February.
    7. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis," Emerging Markets Review, Elsevier, vol. 31(C), pages 32-46.
    8. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    9. Adelina Gschwandtner & Michael Hauser, 2016. "Profit persistence and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3538-3549, August.
    10. Blasberg, Alexander & Kiesel, Rüdiger & Taschini, Luca, 2023. "Carbon default swap – disentangling the exposure to carbon risk through CDS," LSE Research Online Documents on Economics 118096, London School of Economics and Political Science, LSE Library.
    11. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    12. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    13. Gębka, Bartosz & Wohar, Mark E., 2013. "The determinants of quantile autocorrelations: Evidence from the UK," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 51-61.
    14. Jasman Tuyon & Zamri Ahmad, 2021. "Dynamic risk attributes in Malaysia stock markets: Behavioural finance insights," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5793-5814, October.
    15. Jin, Chenglu & Lu, Xingyu & Zhang, Yihan, 2022. "Market reaction, COVID-19 pandemic and return distribution," Finance Research Letters, Elsevier, vol. 47(PB).
    16. Hautsch, Nikolaus & Herrera, Rodrigo, 2015. "Multivariate dynamic intensity peaks-over-threshold models," CFS Working Paper Series 516, Center for Financial Studies (CFS).
    17. Long, Huaigang & Zaremba, Adam & Zhou, Wenyu & Bouri, Elie, 2022. "Macroeconomics matter: Leading economic indicators and the cross-section of global stock returns," Journal of Financial Markets, Elsevier, vol. 61(C).
    18. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.
    19. Xiaoning Li & Mulati Tuerde & Xijian Hu, 2023. "Variational Bayesian Inference for Quantile Regression Models with Nonignorable Missing Data," Mathematics, MDPI, vol. 11(18), pages 1-31, September.
    20. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    21. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2015. "A real-time quantile-regression approach to forecasting gold returns under asymmetric loss," Resources Policy, Elsevier, vol. 45(C), pages 299-306.
    22. Mensi, Walid & Hammoudeh, Shawkat & Reboredo, Juan Carlos & Nguyen, Duc Khuong, 2014. "Do global factors impact BRICS stock markets? A quantile regression approach," Emerging Markets Review, Elsevier, vol. 19(C), pages 1-17.
    23. Paulo Sergio Ceretta & Marcelo Brutti Righi & Alexandre Silva Da costa & Fernanda Maria Muller, 2012. "Quantiles autocorrelation in stock markets returns," Economics Bulletin, AccessEcon, vol. 32(3), pages 2065-2075.
    24. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2022. "Testing Granger Non-Causality in Expectiles," Working Papers 202207, University of Liverpool, Department of Economics.
    25. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    26. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2020. "Asymmetric dependence structures for regional stock markets: An unconditional quantile regression approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    27. Bianchi, Robert J. & Fan, John Hua & Todorova, Neda, 2020. "Financialization and de-financialization of commodity futures: A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    28. Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
    29. Roman Horváth & Štefan Lyócsa & Eduard Baumöhl, 2018. "Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance," The European Journal of Finance, Taylor & Francis Journals, vol. 24(5), pages 391-412, March.
    30. Sunil K. Mohanty & Roar Aadland & Sjur Westgaard & Stein Frydenberg & Hilde Lillienskiold & Cecilie Kristensen, 2021. "Modelling Stock Returns and Risk Management in the Shipping Industry," JRFM, MDPI, vol. 14(4), pages 1-25, April.
    31. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    32. Laura Ferrando & Román Ferrer & Francisco Jareño, 2017. "Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach," Manchester School, University of Manchester, vol. 85(2), pages 212-242, March.
    33. A. Malliaris & Mary Malliaris, 2014. "N-tuple S&P patterns across decades, 1950–2011," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 339-353, June.
    34. Huang, MeiChi & Wu, Chih-Chiang & Liu, Shih-Min & Wu, Chang-Che, 2016. "Facts or fates of investors' losses during crises? Evidence from REIT-stock volatility and tail dependence structures," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 54-71.
    35. 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.
    36. Stelios Bekiros & Amanda Dahlström & Gazi Salah Uddin & Oskar Ege & Ranadeva Jayasekera, 2020. "A tale of two shocks: The dynamics of international real estate markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(1), pages 3-27, January.
    37. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    38. Mohamed S. Ahmed & John A. Doukas, 2021. "Revisiting disposition effect and momentum: a quantile regression perspective," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 1087-1128, April.
    39. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    40. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    41. Sun, Jie & Zhao, Xiaojun & Xu, Chao, 2021. "Crude oil market autocorrelation: Evidence from multiscale quantile regression analysis," Energy Economics, Elsevier, vol. 98(C).
    42. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    43. Lee, Chien-Chiang & Chen, Mei-Ping, 2021. "The effects of investor attention and policy uncertainties on cross-border country exchange-traded fund returns," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 830-852.
    44. Piccoli, Pedro & de Castro, Jessica, 2021. "Attention-return relation in the gold market and market states," Resources Policy, Elsevier, vol. 74(C).
    45. Dirk G Baur & Thomas Dimpfl, 2012. "State-dependent Momentum in International Stock Markets," Working Paper Series 169, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    46. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    47. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
    48. Guo, Peng & Zhu, Huiming & You, Wanhai, 2018. "Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: A quantile regression approach," Finance Research Letters, Elsevier, vol. 25(C), pages 251-258.
    49. Chien-Chiang Lee & Mei-Ping Chen, 2022. "The impact of COVID-19 on the travel and leisure industry returns: Some international evidence," Tourism Economics, , vol. 28(2), pages 451-472, March.
    50. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    51. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    52. Yang, Ann Shawing, 2020. "Misinformation corrections of corporate news: Corporate clarification announcements," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    53. Zhu, Huiming & Peng, Cheng & You, Wanhai, 2016. "Quantile behaviour of cointegration between silver and gold prices," Finance Research Letters, Elsevier, vol. 19(C), pages 119-125.
    54. Ando, Tomohiro & Bai, Jushan, 2018. "Quantile co-movement in financial markets: A panel quantile model with unobserved heterogeneity," MPRA Paper 88765, University Library of Munich, Germany.
    55. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    56. Lee, Chien-Chiang & Lee, Cheng-Feng & Lee, Chi-Chuan, 2014. "Asymmetric dynamics in REIT prices: Further evidence based on quantile regression analysis," Economic Modelling, Elsevier, vol. 42(C), pages 29-37.
    57. Shen, Yifan & Shi, Xunpeng & Variam, Hari Malamakkavu Padinjare, 2018. "Risk transmission mechanism between energy markets: A VAR for VaR approach," Energy Economics, Elsevier, vol. 75(C), pages 377-388.
    58. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    59. Robert Maderitsch, 2015. "Spillovers from the USA to stock markets in Asia: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 47(44), pages 4714-4727, September.
    60. Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Happiness sentiments and the prediction of cross-border country exchange-traded fund returns," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    61. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    62. Naeem, Muhammad Abubakr & Mbarki, Imen & Shahzad, Syed Jawad Hussain, 2021. "Predictive role of online investor sentiment for cryptocurrency market: Evidence from happiness and fears," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 496-514.
    63. Dooyeon Cho & Seunghwa Rho, 2022. "On asymmetric volatility effects in currency markets," Empirical Economics, Springer, vol. 62(5), pages 2149-2177, May.
    64. Chien-Chiang Lee & Mei-Ping Chen & Yi-Ting Peng, 2021. "Tourism development and happiness: International evidence," Tourism Economics, , vol. 27(5), pages 1101-1136, August.
    65. Chevapatrakul, Thanaset & Mascia, Danilo V., 2019. "Detecting overreaction in the Bitcoin market: A quantile autoregression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 371-377.
    66. Livingston, Miles & Yao, Ping & Zhou, Lei, 2019. "The volatility of mutual fund performance," Journal of Economics and Business, Elsevier, vol. 104(C), pages 1-1.
    67. Lili Li & Shan Leng & Jun Yang & Mei Yu, 2016. "Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-15, September.
    68. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    69. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    70. Ngene, Geoffrey M., 2021. "What drives dynamic connectedness of the U.S equity sectors during different business cycles?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    71. Vithessonthi, Chaiporn, 2014. "Financial markets development and bank risk: Experience from Thailand during 1990–2012," Journal of Multinational Financial Management, Elsevier, vol. 27(C), pages 67-88.
    72. Shen, Yifan, 2018. "International risk transmission of stock market movements," Economic Modelling, Elsevier, vol. 69(C), pages 220-236.
    73. 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.
    74. Pieter Jan Trinks & Bert Scholtens, 2017. "The Opportunity Cost of Negative Screening in Socially Responsible Investing," Journal of Business Ethics, Springer, vol. 140(2), pages 193-208, January.
    75. Guodong Li & Yang Li & Chih-Ling Tsai, 2015. "Quantile Correlations and Quantile Autoregressive Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 246-261, March.
    76. Fan, John Hua & Todorova, Neda, 2021. "A note on the behavior of Chinese commodity markets," Finance Research Letters, Elsevier, vol. 38(C).
    77. Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Do natural disasters and geopolitical risks matter for cross-border country exchange-traded fund returns?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    78. Vithessonthi, Chaiporn, 2014. "The effect of financial market development on bank risk: evidence from Southeast Asian countries," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 249-260.
    79. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Black swan events in China's stock markets: Intraday price behaviors on days of volatility," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 395-411.
    80. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    81. I-Chun Tsai, 2015. "Monetary policy and bubbles in the national and regional UK housing markets," Urban Studies, Urban Studies Journal Limited, vol. 52(8), pages 1471-1488, June.
    82. Geoffrey M. Ngene & Catherine Anitha Manohar & Ivan F. Julio, 2020. "Overreaction in the REITs Market: New Evidence from Quantile Autoregression Approach," JRFM, MDPI, vol. 13(11), pages 1-28, November.
    83. Jan Jakub Szczygielski & Chimwemwe Chipeta, 2023. "Properties of returns and variance and the implications for time series modelling: Evidence from South Africa," Modern Finance, Modern Finance Institute, vol. 1(1), pages 35-55.
    84. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    85. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    86. Jasman Tuyon & Zamri Ahmad, 2018. "Behavioural Asset Pricing Determinants in a Factor and Style Investing Framework," Capital Markets Review, Malaysian Finance Association, vol. 26(2), pages 32-52.
    87. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    88. Kenneth Högholm & Johan Knif & Gregory Koutmos & Seppo Pynnönen, 2021. "Financial crises and the asymmetric relation between returns on banks, risk factors, and other industry portfolio returns," The Financial Review, Eastern Finance Association, vol. 56(1), pages 179-198, February.
    89. Blasberg, Alexander & Kiesel, Rüdiger & Taschini, Luca, 2023. "Carbon default swap – disentangling the exposure to carbon risk through CDS," LSE Research Online Documents on Economics 118092, London School of Economics and Political Science, LSE Library.
    90. Cepoi, Cosmin-Octavian, 2020. "Asymmetric dependence between stock market returns and news during COVID-19 financial turmoil," Finance Research Letters, Elsevier, vol. 36(C).
    91. Zhu, Huiming & Huang, Hui & Peng, Cheng & Yang, Yan, 2016. "Extreme dependence between crude oil and stock markets in Asia-Pacific regions: Evidence from quantile regression," Economics Discussion Papers 2016-46, Kiel Institute for the World Economy (IfW Kiel).

  2. Thomas Dimpfl & Robert Jung, 2011. "Financial market spillovers around the globe," Global Financial Markets Working Paper Series 20-2011, Friedrich-Schiller-University Jena.

    Cited by:

    1. Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    2. Ovidiu Stoica & Mark J. Perry & Seyed Mehdian, 2015. "An Empirical Analysis of the Diffusion of Information across Stock Markets of Central and Eastern Europe," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(2), pages 192-210.
    3. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    4. Harald Schmidbauer & Angi Rösch & Erhan Uluceviz & Narod Erkol, 2016. "The Russian Stock Market during the Ukrainian Crisis: A Network Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 478-509, December.
    5. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    6. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    7. 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.
    8. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2015. "Intra-daily volatility spillovers in international stock markets," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 95-114.
    9. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    10. Robert Maderitsch, 2015. "Spillovers from the USA to stock markets in Asia: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 47(44), pages 4714-4727, September.
    11. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    12. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    13. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    14. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    15. Gagan Sharma & Parthajit Kayal & Piyush Pandey, 2019. "Information Linkages Among BRICS Countries: Empirical Evidence from Implied Volatility Indices," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(3), pages 263-289, December.
    16. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.
    17. Vo, Xuan Vinh & Ellis, Craig, 2018. "International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 19-27.

  3. Jung, Robert & Liesenfeld, Roman & Richard, Jean-François, 2008. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Economics Working Papers 2008-12, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. 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.
    2. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    3. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    4. Falk Bräuning & Siem Jan Koopman, 2016. "The dynamic factor network model with an application to global credit risk," Working Papers 16-13, Federal Reserve Bank of Boston.
    5. Dimpfl, Thomas, 2014. "A note on cointegration of international stock market indices," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 10-16.
    6. Catania, Leopoldo & Di Mari, Roberto, 2021. "Hierarchical Markov-switching models for multivariate integer-valued time-series," Journal of Econometrics, Elsevier, vol. 221(1), pages 118-137.
    7. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    8. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    9. Alessio Farcomeni & Monia Ranalli & Sara Viviani, 2021. "Dimension reduction for longitudinal multivariate data by optimizing class separation of projected latent Markov models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 462-480, June.
    10. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011-11, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
    12. Serda S. Öztürk & Thanasis Stengos, 2017. "A Multivariate Stochastic Volatility Model Applied to a Panel of S&P500 Stocks in Different Industries," International Review of Finance, International Review of Finance Ltd., vol. 17(3), pages 479-490, September.
    13. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    14. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    15. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
    16. Norets, Andriy & Pelenis, Justinas, 2022. "Adaptive Bayesian estimation of conditional discrete-continuous distributions with an application to stock market trading activity," Journal of Econometrics, Elsevier, vol. 230(1), pages 62-82.
    17. Bräuning, Falk & Koopman, Siem Jan, 2020. "The dynamic factor network model with an application to international trade," Journal of Econometrics, Elsevier, vol. 216(2), pages 494-515.
    18. Younghoon Kim & Zachary F. Fisher & Vladas Pipiras, 2023. "Latent Gaussian dynamic factor modeling and forecasting for multivariate count time series," Papers 2307.10454, arXiv.org.

  4. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Hager, Svenja & Schöbel, Rainer, 2006. "Deriving the dependence structure of portfolio credit derivatives using evolutionary algorithms," Tübinger Diskussionsbeiträge 300, University of Tübingen, School of Business and Economics.
    2. Zaby, Alexandra K., 2009. "The propensity to patent in oligopolistic markets," Tübinger Diskussionsbeiträge 323, University of Tübingen, School of Business and Economics.
    3. Yalcin, Erdal, 2007. "The proximity-concentration trade-off in a dynamic framework," Tübinger Diskussionsbeiträge 312, University of Tübingen, School of Business and Economics.
    4. Gabriel Felbermayr & Farid Toubal, 2010. "Cultural Proximity and Trade," Post-Print halshs-00641280, HAL.
    5. Heger, Diana & Zaby, Alexandra K., 2009. "The propensity to patent with vertically differentiated products: An empirical investigation," Tübinger Diskussionsbeiträge 325, University of Tübingen, School of Business and Economics.
    6. Schüle, Tobias, 2006. "Creditor coordination with social learning and endogenous timing of credit decisions," Tübinger Diskussionsbeiträge 307, University of Tübingen, School of Business and Economics.
    7. Frontczak, Robert & Schöbel, Rainer, 2008. "Pricing American options with Mellin transforms," Tübinger Diskussionsbeiträge 319, University of Tübingen, School of Business and Economics.
    8. Dymke, Björn M. & Walter, Andreas, 2006. "Insider trading in Germany: Do corporate insiders exploit inside information?," Tübinger Diskussionsbeiträge 309, University of Tübingen, School of Business and Economics.
    9. Rostek, Stefan & Schöbel, Rainer, 2006. "Risk preference based option pricing in a fractional Brownian market," Tübinger Diskussionsbeiträge 299, University of Tübingen, School of Business and Economics.
    10. Andres Pereyra & Elías Rubinstein & Marcelo Pérez, 2008. "Tasa generadora de viajes para el puerto de Montevideo. Una propuesta metodológica," Documentos de Trabajo (working papers) 2108, Department of Economics - dECON.
    11. Brandes, Julia & Schüle, Tobias, 2007. "IMF's assistance: Devil's kiss or guardian angel?," Tübinger Diskussionsbeiträge 310, University of Tübingen, School of Business and Economics.
    12. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    13. Heger, Diana & Zaby, Alexandra K., 2009. "The propensity to patent with horizontally differentiated products: An empirical investigation," Tübinger Diskussionsbeiträge 324, University of Tübingen, School of Business and Economics.
    14. Frontczak, Robert, 2009. "Valuing options in Heston's stochastic volatility model: Another analytical approach," Tübinger Diskussionsbeiträge 326, University of Tübingen, School of Business and Economics.
    15. Frontczak, Robert & Schöbel, Rainer, 2009. "On modified Mellin transforms, Gauss-Laguerre quadrature, and the valuation of American call options," Tübinger Diskussionsbeiträge 320, University of Tübingen, School of Business and Economics.
    16. Carvalho, Alexandre X. & Tanner, Martin A., 2007. "Modelling nonlinear count time series with local mixtures of Poisson autoregressions," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5266-5294, July.
    17. Mailu, Stephen & Lukibisi, Barasa & Waithaka, Michael, 2011. "Application of various count models: Sahiwal demand from Naivasha," MPRA Paper 32074, University Library of Munich, Germany, revised 06 Jul 2011.
    18. Maier, Ramona & Merz, Michael, 2008. "Credibility theory and filter theory in discrete and continuous time," Tübinger Diskussionsbeiträge 318, University of Tübingen, School of Business and Economics.

  5. Jung, Robert & Tremayne, Andrew R., 2001. "Testing serial dependence in time series models of counts against some INARMA alternatives," Tübinger Diskussionsbeiträge 204, University of Tübingen, School of Business and Economics.

    Cited by:

    1. Stadler, Manfred & Wapler, Rüdiger, 2001. "Endogenous skilled-biased technological change and matching unemployment," Tübinger Diskussionsbeiträge 220, University of Tübingen, School of Business and Economics.
    2. Pitterle, Ingo & Steffen, Dirk, 2004. "Welfare Effects of Fiscal Policy under Alternative Exchange Rate Regimes : The Role of the Scale Variable of Money Demand," Tübinger Diskussionsbeiträge 284, University of Tübingen, School of Business and Economics.
    3. Köpke, Nikola & Baten, Jörg, 2003. "The biological standard of living in Europe during the last two millennia," Tübinger Diskussionsbeiträge 265, University of Tübingen, School of Business and Economics.
    4. Stadler, Manfred, 2003. "Innovation and growth: The role of labor-force qualification," Tübinger Diskussionsbeiträge 255, University of Tübingen, School of Business and Economics.
    5. Baten, Jörg & Wallusch, Jacek, 2003. "Market integration and disintegration of Poland and Gemany [Germany] in the 18th century," Tübinger Diskussionsbeiträge 268, University of Tübingen, School of Business and Economics.

  6. Liesenfeld, Roman & Jung, Robert C., 1997. "Stochastic volatility models: Conditional normality versus heavy tailed distributions," Tübinger Diskussionsbeiträge 103, University of Tübingen, School of Business and Economics.

    Cited by:

    1. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    2. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    3. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    4. Bruno Feunou & Roméo Tedongap, 2011. "A Stochastic Volatility Model with Conditional Skewness," Staff Working Papers 11-20, Bank of Canada.
    5. Xi, Yanhui & Peng, Hui & Qin, Yemei & Xie, Wenbiao & Chen, Xiaohong, 2015. "Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 117(C), pages 141-153.
    6. Carlos A. Abanto-Valle & Gabriel Rodríguez & Hernán B. Garrafa-Aragón, 2020. "Stochastic Volatility in Mean: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers 2020-481, Departamento de Economía - Pontificia Universidad Católica del Perú.
    7. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
    8. 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.
    9. Casas, Isabel & Lopes Moreira Da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. 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).
    11. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    12. Asai, M. & Chang, C-L. & McAleer, M.J., 2017. "Realized Stochastic Volatility with General Asymmetry and Long Memory," Econometric Institute Research Papers TI 2017-038/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Jonathan Wright, 2002. "Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
    14. John Randal & Peter Thomson & Martin Lally, 2004. "Non-parametric estimation of historical volatility," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 427-440.
    15. Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
    16. P. de Zea Bermudez & J. Miguel Marín & Helena Veiga, 2020. "Data cloning estimation for asymmetric stochastic volatility models," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 1057-1074, November.
    17. Arie Preminger & Christian M. Hafner, 2006. "Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules," Working Papers 0603, Ben-Gurion University of the Negev, Department of Economics.
    18. Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
    19. 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.
    20. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
    21. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2023. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," MPRA Paper 118459, University Library of Munich, Germany.
    22. Asai, M. & Caporin, M. & McAleer, M.J., 2012. "Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models," Econometric Institute Research Papers EI 2012-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    23. Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.
    24. Manabu Asai & Michael McAleer, 2005. "Asymmetric Multivariate Stochastic Volatility," DEA Working Papers 12, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    25. Asai, Manabu, 2009. "Bayesian analysis of stochastic volatility models with mixture-of-normal distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2579-2596.
    26. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    27. Carlos A. Abanto‐Valle & Helio S. Migon & Hedibert F. Lopes, 2010. "Bayesian modeling of financial returns: A relationship between volatility and trading volume," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(2), pages 172-193, March.
    28. Fulvia Focker & Umberto Triacca, 2006. "A new proxy of the average volatility of a basket of returns: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-14.
    29. Nikolaus Hautsch & Yangguoyi Ou, 2008. "Discrete-Time Stochastic Volatility Models and MCMC-Based Statistical Inference," SFB 649 Discussion Papers SFB649DP2008-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    30. Wang, Joanna J.J., 2012. "On asymmetric generalised t stochastic volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(11), pages 2079-2095.
    31. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    32. Adam Clements & Stan Hurn & Scott White, 2006. "Estimating Stochastic Volatility Models Using a Discrete Non-linear Filter. Working paper #3," NCER Working Paper Series 3, National Centre for Econometric Research.
    33. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    34. Josu Arteche & Javier García‐Enríquez, 2022. "Singular spectrum analysis for value at risk in stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 3-16, January.
    35. Bruno Ebner & Bernhard Klar & Simos G. Meintanis, 2018. "Fourier inference for stochastic volatility models with heavy-tailed innovations," Statistical Papers, Springer, vol. 59(3), pages 1043-1060, September.
    36. C. A. Abanto-Valle & V. H. Lachos & Dipak K. Dey, 2015. "Bayesian Estimation of a Skew-Student-t Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 721-738, September.
    37. Kawakatsu, Hiroyuki, 2007. "Specification and estimation of discrete time quadratic stochastic volatility models," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 424-442, June.
    38. Mendoza-Velázquez, Alfonso & Galvanovskis, Evalds, 2009. "Introducing the GED-Copula with an application to Financial Contagion in Latin America," MPRA Paper 46669, University Library of Munich, Germany, revised 01 Feb 2010.
    39. 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).
    40. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    41. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    42. N. Balakrishna & Bovas Abraham & Ranjini Sivakumar, 2006. "Gamma stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(3), pages 153-171.
    43. Saralees Nadarajah, 2012. "Models for stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 411-424, February.
    44. 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.
    45. M. Hakan Eratalay, 2016. "Estimation of Multivariate Stochastic Volatility Models: A Comparative Monte Carlo Study," International Econometric Review (IER), Econometric Research Association, vol. 8(2), pages 19-52, September.
    46. P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    47. Robert C. Jung & Roman Liesenfeld & Jean-François Richard, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 73-85, January.
    48. Carlos A. Abanto‐Valle & Roland Langrock & Ming‐Hui Chen & Michel V. Cardoso, 2017. "Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 394-408, August.
    49. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    50. Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
    51. Mendoza, Alfonso. & Galvanovskis, Evalds., 2014. "La cópula GED bivariada. Una aplicación en entornos de crisis," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .721-746, julio-sep.
    52. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    53. Abanto-Valle, C.A. & Bandyopadhyay, D. & Lachos, V.H. & Enriquez, I., 2010. "Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2883-2898, December.
    54. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
    55. Umberto Triacca & Fulvia Focker, 2014. "Estimating overnight volatility of asset returns by using the generalized dynamic factor model approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 235-254, October.
    56. Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
    57. Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 01 Aug 2007.
    58. Mohammed Bouaddi & Khouzeima Moutanabbir, 2022. "Systematic extreme potential gain and loss spillover across countries," Risk Management, Palgrave Macmillan, vol. 24(4), pages 327-366, December.
    59. Asai, Manabu, 2008. "Autoregressive stochastic volatility models with heavy-tailed distributions: A comparison with multifactor volatility models," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 332-341, March.
    60. Carlos A. Abanto-Valle & Hernán B. Garrafa-Aragón, 2019. "Threshold Stochastic Volatility Models with Heavy Tails:A Bayesian Approach," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(83), pages 32-53.
    61. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.
    62. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.

Articles

  1. Dimpfl, Thomas & Flad, Michael & Jung, Robert C., 2017. "Price discovery in agricultural commodity markets in the presence of futures speculation," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 50-62.

    Cited by:

    1. Pagnottoni, Paolo & Baur, Dirk G. & Dimpfl, Thomas, 2018. "Price Discovery on Bitcoin Markets," IRTG 1792 Discussion Papers 2018-014, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Lin Xie & Jiahua Liao & Haiting Chen & Xuefei Yan & Xinyan Hu, 2021. "Is Futurization the Culprit for the Violent Fluctuation in China’s Apple Spot Price?," Agriculture, MDPI, vol. 11(4), pages 1-14, April.
    3. Marc J. M. Bohmann & David Michayluk & Vinay Patel, 2019. "Price discovery in commodity derivatives: Speculation or hedging?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1107-1121, September.
    4. Indriawan, Ivan & Martinez, Valeria & Tse, Yiuman, 2021. "The impact of the change in USDA announcement release procedures on agricultural commodity futures," Journal of Commodity Markets, Elsevier, vol. 23(C).
    5. Prashant Sharma & Prashant Gupta & Dinesh Kumar Sharma & Gaurav Agarwal, 2022. "Investigating the Efficiency of Bitcoin Futures in Price Discovery," International Journal of Economics and Financial Issues, Econjournals, vol. 12(3), pages 104-109, May.
    6. Dai, Yun-Shi & Huynh, Ngoc Quang Anh & Zheng, Qing-Huan & Zhou, Wei-Xing, 2022. "Correlation structure analysis of the global agricultural futures market," Research in International Business and Finance, Elsevier, vol. 61(C).
    7. Moses M. Kupabado & Juergen Kaehler, 2021. "Financialization, common stochastic trends, and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1988-2008, December.
    8. Oliver Entrop & Bart Frijns & Marco Seruset, 2020. "The determinants of price discovery on bitcoin markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 816-837, May.
    9. Carlotta Penone & Elisa Giampietri & Samuele Trestini, 2022. "Futures–spot price transmission in EU corn markets," Agribusiness, John Wiley & Sons, Ltd., vol. 38(3), pages 679-709, July.
    10. Fassas, Athanasios P., 2021. "Price discovery in US money market benchmarks: LIBOR vs. SOFR," Economics Letters, Elsevier, vol. 204(C).
    11. Čermák, Michal & Ligocká, Marie, 2022. "Could Exist a Causality Between the Most Traded Commodities and Futures Commodity Prices in the Agricultural Market?," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 14(4), December.
    12. Baur, Dirk G. & Dimpfl, Thomas, 2018. "The asymmetric return-volatility relationship of commodity prices," Energy Economics, Elsevier, vol. 76(C), pages 378-387.
    13. Fassas, Athanasios P. & Papadamou, Stephanos & Koulis, Alexandros, 2020. "Price discovery in bitcoin futures," Research in International Business and Finance, Elsevier, vol. 52(C).
    14. Muneer Shaik & Abhiram Kartik Lanka & Gurmeet Singh, 2021. "Analysis of lead-lag relationship and volatility spillover: evidence from Indian agriculture commodity markets," International Journal of Bonds and Derivatives, Inderscience Enterprises Ltd, vol. 4(3), pages 258-279.
    15. Jean-François Carpantier, 2021. "Commodity Prices in Empirical Research," Dynamic Modeling and Econometrics in Economics and Finance, in: Gilles Dufrénot & Takashi Matsuki (ed.), Recent Econometric Techniques for Macroeconomic and Financial Data, pages 199-227, Springer.
    16. Hung, Jui-Cheng & Liu, Hung-Chun & Yang, J. Jimmy, 2021. "Trading activity and price discovery in Bitcoin futures markets," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 107-120.
    17. Marc Bohmann, 2020. "Price Discovery and Information Asymmetry in Equity and Commodity Futures Options Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2020.
    18. Zhuo Chen & Bo Yan & Hanwen Kang & Liyu Liu, 2023. "Asymmetric price adjustment and price discovery in spot and futures markets of agricultural commodities," Review of Economic Design, Springer;Society for Economic Design, vol. 27(1), pages 139-162, February.
    19. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
    20. Christian Koziol & Tilo Treuter, 2019. "How do speculators in agricultural commodity markets impact production decisions and commodity prices? A theoretical analysis," European Financial Management, European Financial Management Association, vol. 25(3), pages 718-743, June.
    21. Kuck, Konstantin & Schweikert, Karsten, 2023. "Price discovery in equity markets: A state-dependent analysis of spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 149(C).
    22. Qianqian Mao & Jens-Peter Loy & Thomas Glauben & Yanjun Ren, 2023. "Are futures markets functioning well for agricultural perishables? Evidence from China's apple futures market," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(12), pages 471-484.
    23. Martin T. Bohl & Pierre L. Siklos & Martin Stefan & Claudia Wellenreuther, 2018. "Price Discovery in Agricultural Commodity Markets: Do Speculators Contribute?," CQE Working Papers 7518, Center for Quantitative Economics (CQE), University of Muenster.
    24. Salisu, Afees A. & Adediran, Idris A. & Oloko, Tirimisiyu O. & Ohemeng, William, 2020. "The heterogeneous behaviour of the inflation hedging property of cocoa," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    25. Scott, Ayesha & Schoen, Tilman & Fernandez-Perez, Adrian, 2020. "The Predictive Power of NZX Dairy Futures," 2020 Conference (64th), February 12-14, 2020, Perth, Western Australia 305230, Australian Agricultural and Resource Economics Society.
    26. Fernandez-Perez, Adrian & Miffre, Joëlle & Schoen, Tilman & Scott, Ayesha, 2023. "Do spot market auction data help price discovery?," Journal of Commodity Markets, Elsevier, vol. 31(C).
    27. Don Bredin & Valerio Potì & Enrique Salvador, 2022. "Food Prices, Ethics and Forms of Speculation," Journal of Business Ethics, Springer, vol. 179(2), pages 495-509, August.
    28. Narjiss Araba & Alain François-Heude, 2019. "Price discovery and volatility spillovers in the French wheat market," Post-Print hal-03088859, HAL.
    29. Pradita Nareswari & Sigit S. Wibowo, 2020. "Global and Local Commodity Prices: A Further Look at the Indonesian Agricultural Commodities," Capital Markets Review, Malaysian Finance Association, vol. 28(1), pages 65-76.
    30. Alexander, Carol & Heck, Daniel F., 2020. "Price discovery in Bitcoin: The impact of unregulated markets," Journal of Financial Stability, Elsevier, vol. 50(C).
    31. Dragan Miljkovic & Cole Goetz, 2020. "Destabilizing role of futures markets on North American hard red spring wheat spot prices," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 887-897, November.
    32. Adrian Fernandez-Perez & Joëlle Miffre & Tilman Schoen & Ayesha Scott, 2023. "Do spot market auction data help price discovery?," Post-Print hal-04121327, HAL.
    33. Prashant Sharma & Gaurav Agrawal & Geetika Arora & Dinesh Kumar Sharma & Varun Chotia, 2023. "Research on Price Discovery in Financial Securities: Trends and Directions for Future Research," JRFM, MDPI, vol. 16(9), pages 1-19, September.
    34. Dirk G. Baur & Thomas Dimpfl, 2019. "Price discovery in bitcoin spot or futures?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 803-817, July.
    35. Teresa Vollmer & Helmut Herwartz & Stephan von Cramon-Taubadel, 2020. "Measuring price discovery in the European wheat market using the partial cointegration approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1173-1200.
    36. Xiaochun Liu, 2018. "Structural Volatility Impulse Response Function and Asymptotic Inference," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 316-339.
    37. Dimpfl, Thomas & Peter, Franziska J., 2021. "Nothing but noise? Price discovery across cryptocurrency exchanges," Journal of Financial Markets, Elsevier, vol. 54(C).
    38. Dragan Miljkovic & Cole Goetz, 2023. "Futures markets and price stabilisation: An analysis of soybeans markets in North America," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(1), pages 104-117, January.
    39. Phiri, Isaac, 2020. "The effect of access to finance on commercialisation of smallholder maize farmers in Eswatini," Research Theses 334755, Collaborative Masters Program in Agricultural and Applied Economics.
    40. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2021. "An analysis of investor behaviour and information flows surrounding the negative WTI oil price futures event," Energy Economics, Elsevier, vol. 104(C).
    41. Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B., 2019. "Adaptive learning forecasting, with applications in forecasting agricultural prices," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1356-1369.

  2. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.

    Cited by:

    1. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    2. Thilker, Christian Ankerstjerne & Madsen, Henrik & Jørgensen, John Bagterp, 2021. "Advanced forecasting and disturbance modelling for model predictive control of smart energy systems," Applied Energy, Elsevier, vol. 292(C).
    3. Benjamin Hippert & André Uhde & Sascha Tobias Wengerek, 2019. "Portfolio benefits of adding corporate credit default swap indices: evidence from North America and Europe," Review of Derivatives Research, Springer, vol. 22(2), pages 203-259, July.
    4. Gustavo Peralta, 2016. "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
    5. Cipollini, Andrea & Cascio, Iolanda Lo & Muzzioli, Silvia, 2015. "Volatility co-movements: A time-scale decomposition analysis," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 34-44.
    6. Yang, Lu & Yang, Lei & Ho, Kung-Cheng & Hamori, Shigeyuki, 2020. "Dependence structures and risk spillover in China’s credit bond market: A copula and CoVaR approach," Journal of Asian Economics, Elsevier, vol. 68(C).
    7. Dungey, Mardi & Gajurel, Dinesh, 2014. "Contagion and banking crisis — internatonal evidence for 2007-2009," Working Papers 2014-10, University of Tasmania, Tasmanian School of Business and Economics.
    8. Tam Hoang-Nhat Dang & Nhan Thien Nguyen & Duc Hong Vo, 2023. "Sectoral volatility spillovers and their determinants in Vietnam," Economic Change and Restructuring, Springer, vol. 56(1), pages 681-700, February.
    9. Wei-Zhen Li & Jin-Rui Zhai & Zhi-Qiang Jiang & Gang-Jin Wang & Wei-Xing Zhou, 2020. "Predicting tail events in a RIA-EVT-Copula framework," Papers 2004.03190, arXiv.org, revised Apr 2020.
    10. Georgios Magkonis & Andreas Tsopanakis, 2018. "The Financial Connectedness between Eurozone Core and Periphery: A Disaggregated View," Working Papers in Economics & Finance 2018-03, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    11. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    12. Noureddine Benlagha & Wael Hemrit, 2022. "Does economic policy uncertainty matter to explain connectedness within the international sovereign bond yields?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 1-21, January.
    13. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    14. Vo, Xuan Vinh, 2016. "Does institutional ownership increase stock return volatility? Evidence from Vietnam," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 54-61.
    15. Iqbal, Najaf & Naeem, Muhammad Abubakr & Suleman, Muhammed Tahir, 2022. "Quantifying the asymmetric spillovers in sustainable investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    16. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2017. "Asymmetry in spillover effects: Evidence for international stock index futures markets," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 94-111.
    17. Alexey Yurievich Mikhaylov, 2018. "Volatility Spillover Effect between Stock and Exchange Rate in Oil Exporting Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 321-326.
    18. Jarosław Duda & Henryk Gurgul & Robert Syrek, 2022. "Multi-feature evaluation of financial contagion," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1167-1194, December.
    19. Dungey, Mardi & Milunovich, George & Thorp, Susan & Yang, Minxian, 2012. "Endogenous crisis dating and contagion using smooth transition structural GARCH," Working Papers 15030, University of Tasmania, Tasmanian School of Business and Economics, revised 29 Aug 2012.
    20. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    21. Withanage, Yeshan & Jayasinghe, Prabhath, 2017. "Volatility Spillovers between South Asian Stock Markets: Evidence from Sri Lanka, India and Pakistan," MPRA Paper 82782, University Library of Munich, Germany, revised Nov 2017.
    22. Mingbo Zheng & Gen-Fu Feng & Xinxin Zhao & Chun-Ping Chang, 2023. "The transaction behavior of cryptocurrency and electricity consumption," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-18, December.
    23. Liu, Junlin & Chen, Feier, 2018. "Asymmetric volatility varies in different dry bulk freight rate markets under structure breaks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 316-327.
    24. Krzysztof Brania & Henryk Gurgul, 2021. "Contagion effects on capital and forex markets around GFC and COVID-19 crises. A comparative study," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 59-92.
    25. Elsayed, Ahmed H. & Ahmed, Habib & Husam Helmi, Mohamad, 2023. "Determinants of financial stability and risk transmission in dual financial system: Evidence from the COVID pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    26. 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.
    27. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
    28. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    29. Walid Abass Mohammed, 2021. "Volatility Spillovers among Developed and Developing Countries: The Global Foreign Exchange Markets," JRFM, MDPI, vol. 14(6), pages 1-30, June.
    30. Neha Seth & Monica Sighania, 2017. "Financial market contagion: selective review of reviews," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 9(4), pages 391-408, November.
    31. Ciarreta, Aitor & Zarraga, Ainhoa, 2016. "Modeling realized volatility on the Spanish intra-day electricity market," Energy Economics, Elsevier, vol. 58(C), pages 152-163.
    32. 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.
    33. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    34. Aloui, Riadh & Ben Jabeur, Sami & Mefteh-Wali, Salma, 2022. "Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis," Research in International Business and Finance, Elsevier, vol. 62(C).
    35. Yin, Kedong & Liu, Zhe & Jin, Xue, 2020. "Interindustry volatility spillover effects in China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    36. 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.
    37. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    38. Dejan ŽIVKOV & Jovan NJEGIĆ & Ivan MILENKOVIĆ, 2018. "Interrelationship between DAX Index and Four Largest Eastern European Stock Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-103, September.
    39. Aristeidis Samitas & Elias Kampouris & Zaghum Umar, 2022. "Financial contagion in real economy: The key role of policy uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1633-1682, April.
    40. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    41. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.
    42. Sandoval Paucar, Giovanny, 2018. "Efectos de desbordamiento sobre los mercados financieros de Colombia. Identificación a través de la heterocedasticidad [Spillovers effects on financial markets of Colombia. Identification through h," MPRA Paper 90422, University Library of Munich, Germany.
    43. Yang, Lu & Cai, Xiao Jing & Zhang, Huimin & Hamori, Shigeyuki, 2016. "Interdependence of foreign exchange markets: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 55(C), pages 6-14.
    44. Ying-Ying Shen & Zhi-Qiang Jiang & Jun-Chao Ma & Gang-Jin Wang & Wei-Xing Zhou, 2022. "Sector connectedness in the Chinese stock markets," Empirical Economics, Springer, vol. 62(2), pages 825-852, February.
    45. Man Wang & Yihan Cheng, 2022. "Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1595-1607, December.
    46. Al-Shboul, Mohammad & Anwar, Sajid, 2016. "Fractional integration in daily stock market indices at Jordan's Amman stock exchange," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 16-37.
    47. Anthony Msafiri Nyangarika & Alexey Yurievich Mikhaylov & Bao-jun Tang, 2018. "Correlation of Oil Prices and Gross Domestic Product in Oil Producing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 42-48.
    48. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    49. Ana Escribano & Cristina Íñiguez, 2021. "The contagion phenomena of the Brexit process on main stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4462-4481, July.
    50. Bajaj, Vimmy & Kumar, Pawan & Singh, Vipul Kumar, 2022. "Linkage dynamics of sovereign credit risk and financial markets: A bibliometric analysis," Research in International Business and Finance, Elsevier, vol. 59(C).
    51. Sevda Kuşkaya & Nurhan Toğuç & Faik Bilgili, 2022. "Wavelet coherence analysis and exchange rate movements," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4675-4692, December.
    52. Liu, Guangqiang & Wei, Yu & Chen, Yongfei & Yu, Jiang & Hu, Yang, 2018. "Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 288-297.
    53. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    54. Aristeidis, Samitas & Elias, Kampouris, 2018. "Empirical analysis of market reactions to the UK’s referendum results – How strong will Brexit be?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 263-286.
    55. Vo, Xuan Vinh & Ellis, Craig, 2018. "International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 19-27.
    56. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.
    57. Mateus, Cesario & Chinthalapati, Raju & Mateus, Irina B., 2017. "Intraday industry-specific spillover effect in European equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 278-298.

  3. Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
    See citations under working paper version above.
  4. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.

    Cited by:

    1. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
    2. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    3. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2017. "Tests for Structural Changes in Time Series of Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 843-865, December.
    4. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    5. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    6. Jiwon Kang & Sangyeol Lee, 2014. "Parameter Change Test for Poisson Autoregressive Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1136-1152, December.
    7. Veraart, Almut E.D., 2019. "Modeling, simulation and inference for multivariate time series of counts using trawl processes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 110-129.
    8. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. Chen, Zezhun Chen & Dassios, Angelos & Tzougas, George, 2023. "A first order binomial mixed poisson integer-valued autoregressive model with serially dependent innovations," LSE Research Online Documents on Economics 112222, London School of Economics and Political Science, LSE Library.
    10. Christian H. Weiß, 2018. "Goodness-of-fit testing of a count time series’ marginal distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(6), pages 619-651, August.
    11. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    12. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    13. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    14. Robert C. Jung & Stephanie Glaser, 2022. "Modelling and Diagnostics of Spatially Autocorrelated Counts," Econometrics, MDPI, vol. 10(3), pages 1-17, September.
    15. Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022. "Spatial panel count data: modeling and forecasting of urban crimes," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-29, December.
    16. Annika Homburg & Christian H. Weiß & Gabriel Frahm & Layth C. Alwan & Rainer Göb, 2021. "Analysis and Forecasting of Risk in Count Processes," JRFM, MDPI, vol. 14(4), pages 1-25, April.
    17. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    18. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    19. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    20. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    21. Wooi Chen Khoo & Seng Huat Ong & Atanu Biswas, 2017. "Modeling time series of counts with a new class of INAR(1) model," Statistical Papers, Springer, vol. 58(2), pages 393-416, June.
    22. Lívio Tito & Bourguignon Marcelo & Nascimento Fernando, 2020. "INAR(1) Processes with Inflated-parameter Generalized Power Series Innovations," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-27, July.
    23. Moizes Melo & Airlane Alencar, 2020. "Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 830-857, November.
    24. Shengqi Tian & Dehui Wang & Shuai Cui, 2020. "A seasonal geometric INAR process based on negative binomial thinning operator," Statistical Papers, Springer, vol. 61(6), pages 2561-2581, December.
    25. Scotto, Manuel G. & Weiß, Christian H. & Silva, Maria Eduarda & Pereira, Isabel, 2014. "Bivariate binomial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 233-251.
    26. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.

  5. Flad, Michael & Jung, Robert C., 2008. "A common factor analysis for the US and the German stock markets during overlapping trading hours," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 498-512, December.

    Cited by:

    1. Peresetsky, Anatoly & Yakubov, Ruslan, 2015. "Autocorrelation in an unobservable global trend: Does it help to forecast market returns?," MPRA Paper 64579, University Library of Munich, Germany.
    2. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," University of Tübingen Working Papers in Business and Economics 70, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    3. Gkillas, Konstantinos & Konstantatos, Christoforos & Floros, Christos & Tsagkanos, Athanasios, 2021. "Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis," International Review of Financial Analysis, Elsevier, vol. 74(C).
    4. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
    5. Kuck, Konstantin & Schweikert, Karsten, 2023. "Price discovery in equity markets: A state-dependent analysis of spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 149(C).
    6. Vollmer, Teresa & Von Cramon-Taubadel, Stephan, 2017. "Price discovery in the European wheat market," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261135, European Association of Agricultural Economists.
    7. Vollmer, T. & Von Cramon-Taubadel, S., 2018. "Dynamic price discovery in the European wheat market based on the concept of partial cointegration," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276031, International Association of Agricultural Economists.
    8. Teresa Vollmer & Helmut Herwartz & Stephan von Cramon-Taubadel, 2020. "Measuring price discovery in the European wheat market using the partial cointegration approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1173-1200.
    9. Kao, Erin H. & Ho, Tsung-wu & Fung, Hung-Gay, 2015. "Price linkage between the US and Japanese futures across different time zones: An analysis of the minute-by-minute data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 321-336.
    10. Buckle, Mike & Chen, Jing & Guo, Qian & Tong, Chen, 2018. "Do ETFs lead the price moves? Evidence from the major US markets," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 91-103.

  6. Baur, Dirk & Jung, Robert C., 2006. "Return and volatility linkages between the US and the German stock market," Journal of International Money and Finance, Elsevier, vol. 25(4), pages 598-613, June.

    Cited by:

    1. Avdoulas, Christos & Bekiros, Stelios & Boubaker, Sabri, 2016. "Detecting nonlinear dependencies in eurozone peripheral equity markets: A multistep filtering approach," Economic Modelling, Elsevier, vol. 58(C), pages 580-587.
    2. Payal Jain & Sanjay Sehgal, 2019. "An examination of return and volatility spillovers between mature equity markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 43(1), pages 180-210, January.
    3. Maghyereh, Aktham I. & Awartani, Basel & Hilu, Khalil Al, 2015. "Dynamic transmissions between the U.S. and equity markets in the MENA countries: New evidence from pre- and post-global financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 123-138.
    4. Dirk G. Baur, 2010. "Financial Contagion and the Real Economy," CAMA Working Papers 2010-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Rahmali, Atiqah & Masih, Mansur, 2017. "Discerning the effect of international stock markets before and after the subprime crisis," MPRA Paper 110700, University Library of Munich, Germany.
    6. Sarwar, Ghulam, 2012. "Is VIX an investor fear gauge in BRIC equity markets?," Journal of Multinational Financial Management, Elsevier, vol. 22(3), pages 55-65.
    7. Mohamed Shikh Albaity & Hamdia Mudor, 2012. "Return performance, Cointegration and short run dynamics of Islamic and non-Islamic indices: evidence from the US and Malaysia during the subprime crisis," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 1, pages 1-1, June.
    8. Miralles-Quirós, José Luis & Daza-Izquierdo, Julio, 2015. "Do DOW returns really influence the intraday Spanish stock market behavior?," Research in International Business and Finance, Elsevier, vol. 33(C), pages 99-126.
    9. Finta, Marinela Adriana & Aboura, Sofiane, 2020. "Risk premium spillovers among stock markets: Evidence from higher-order moments," Journal of Financial Markets, Elsevier, vol. 49(C).
    10. Thomas Dimpfl & Robert Jung, 2011. "Financial market spillovers around the globe," Global Financial Markets Working Paper Series 20-2011, Friedrich-Schiller-University Jena.
    11. Mukherjee, Dr. Kedar nath & Mishra, Dr. R. K., 2008. "Stock Market Integration and Volatility Spillover:India and its Major Asian Counterparts," MPRA Paper 12788, University Library of Munich, Germany.
    12. Bekiros, Stelios, 2014. "Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 336-348.
    13. Enzo Weber, 2007. "Correlation vs. Causality in Stock Market Comovement," SFB 649 Discussion Papers SFB649DP2007-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Chen, Bin-xia & Sun, Yan-lin, 2022. "The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    15. Hou, Yang (Greg) & Li, Steven, 2020. "Volatility and skewness spillover between stock index and stock index futures markets during a crash period: New evidence from China," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 166-188.
    16. Harald Schmidbauer & Angi Rösch & Erhan Uluceviz & Narod Erkol, 2016. "The Russian Stock Market during the Ukrainian Crisis: A Network Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 478-509, December.
    17. Dimpfl, Thomas, 2011. "The impact of US news on the German stock market—An event study analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 389-398.
    18. Gkillas, Konstantinos & Konstantatos, Christoforos & Floros, Christos & Tsagkanos, Athanasios, 2021. "Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis," International Review of Financial Analysis, Elsevier, vol. 74(C).
    19. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
    20. Jianxin Wang, 2007. "Foreign Ownership and Volatility Dynamics of Indonesian Stocks," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 201-210, September.
    21. Trang Nha Le & Makoto Kakinaka, 2010. "International Transmission Of Stock Returns: Mean And Volatility Spillover Effects In Indonesia And Malaysia," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(1), pages 115-131.
    22. Raddant, Matthias & Kenett, Dror, 2016. "Interconnectedness in the global financial market," VfS Annual Conference 2016 (Augsburg): Demographic Change 145560, Verein für Socialpolitik / German Economic Association.
    23. Herrera, Rodrigo & Schipp, Bernhard, 2014. "Statistics of extreme events in risk management: The impact of the subprime and global financial crisis on the German stock market," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 218-238.
    24. Galin Todorov & Prasad Bidarkota, 2013. "On international financial spillovers to frontier markets," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 5(4), pages 433-452.
    25. Sinha, Pankaj & Sinha, Gyanesh, 2010. "Volatility Spillover in India, USA and Japan Investigation of Recession Effects," MPRA Paper 21873, University Library of Munich, Germany.
    26. Jing Chen & David G. McMillan & Mike Buckle, 2018. "Information Transmission across European Equity Markets During Crisis Periods," Manchester School, University of Manchester, vol. 86(6), pages 770-788, December.
    27. Bekiros, Stelios D., 2014. "Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 58-69.
    28. Galin Todorov & Prasad Bidarkota, 2014. "Time-varying financial spillovers from the US to frontier markets," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 7(2), pages 246-283, September.
    29. Ani Stoykova & Mariya Paskaleva, 2018. "Correlation Dynamics between Southeast European Capital Markets," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 49-82.
    30. Bhuyan, Rafiqul & Robbani, Mohammad G. & Talukdar, Bakhtear & Jain, Ajeet, 2016. "Information transmission and dynamics of stock price movements: An empirical analysis of BRICS and US stock markets," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 180-195.
    31. Ahmad, Wasim & Prakash, Ravi & Uddin, Gazi Salah & Chahal, Rishman Jot Kaur & Rahman, Md. Lutfur & Dutta, Anupam, 2020. "On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?," Energy Economics, Elsevier, vol. 91(C).
    32. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2017. "Do International Investors Cause Stock Market Comovements? Comparing Responses of Cross-Listed Stocks between Accessible and Inaccessible Markets," Discussion Papers in Economics and Business 17-01, Osaka University, Graduate School of Economics.
    33. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2018. "Do international investors cause stock market spillovers? Comparing responses of cross-listed stocks between accessible and inaccessible markets," Economic Modelling, Elsevier, vol. 69(C), pages 237-248.
    34. Raza, Naveed & Ali, Sajid & Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur & Salman, Aneel, 2019. "Can alternative hedging assets add value to Islamic-conventional portfolio mix: Evidence from MGARCH models," Resources Policy, Elsevier, vol. 61(C), pages 210-230.
    35. Fredj Jawadi & Wael Louhichi & Hachmi Ben Ameur & Abdoulkarim Idi Cheffou, 2017. "On Oil-US Exchange Rate Volatility Relationships: an Intradaily Analysis," Working Papers hal-04141662, HAL.
    36. Doseong Kim & Yoon-Goo Lee & Isabel Ruiz, 2010. "Common Volatility: An Empirical Investigation of Closed-End Country Funds," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(2), pages 116-132, March.
    37. Chris Heaton & George Milunovich & Anthony Passé‐De Silva, 2011. "International Commodity Prices and the Australian Stock Market," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 37-44, March.
    38. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    39. Milunovich, George & Thorp, Susan, 2007. "Measuring equity market integration using uncorrelated information flows: Tokyo, London and New York," Journal of Multinational Financial Management, Elsevier, vol. 17(4), pages 275-289, October.
    40. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2014. "Intraday Return and Volatility Spillover Mechanism from Chinese to Japanese Stock Market," Discussion Papers in Economics and Business 14-01, Osaka University, Graduate School of Economics.
    41. 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.
    42. Sarwar, Ghulam, 2014. "U.S. stock market uncertainty and cross-market European stock returns," Journal of Multinational Financial Management, Elsevier, vol. 28(C), pages 1-14.
    43. Fredj Jawadi & Waël Louhichi & Hachmi Ben Ameur & Abdoulkarim Idi Cheffou, 2017. "On Oil-US Exchange Rate Volatility Relationships: an Intradaily Analysis," EconomiX Working Papers 2017-11, University of Paris Nanterre, EconomiX.
    44. Sinha, Pankaj & Mathur, Kritika, 2013. "International Linkages of Agri-Processed and Energy commodities traded in India," MPRA Paper 50214, University Library of Munich, Germany, revised 26 Sep 2013.
    45. Montes, Gabriel Caldas & Tiberto, Bruno Pires, 2012. "Macroeconomic environment, country risk and stock market performance: Evidence for Brazil," Economic Modelling, Elsevier, vol. 29(5), pages 1666-1678.
    46. Robert Maderitsch, 2015. "Spillovers from the USA to stock markets in Asia: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 47(44), pages 4714-4727, September.
    47. Awartani, Basel & Maghyereh, Aktham I. & Shiab, Mohammad Al, 2013. "Directional spillovers from the U.S. and the Saudi market to equities in the Gulf Cooperation Council countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 224-242.
    48. Sinha, Pankaj & Mathur, Kritika, 2013. "Price, Return and Volatility Linkages of Base Metal Futures traded in India," MPRA Paper 47864, University Library of Munich, Germany.
    49. Saffet Akdag & Ömer İskenderoglu & Andrew Adewale Alola, 2020. "The volatility spillover effects among risk appetite indexes: insight from the VIX and the rise," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 49-65, April.
    50. Köpke, Nikola & Baten, Jörg, 2003. "The biological standard of living in Europe during the last two millennia," Tübinger Diskussionsbeiträge 265, University of Tübingen, School of Business and Economics.
    51. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
    52. Flad, Michael & Jung, Robert C., 2008. "A common factor analysis for the US and the German stock markets during overlapping trading hours," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 498-512, December.
    53. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    54. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    55. Mukherjee, Kedar nath & Mishra, Ram Kumar, 2010. "Stock market integration and volatility spillover: India and its major Asian counterparts," Research in International Business and Finance, Elsevier, vol. 24(2), pages 235-251, June.
    56. Stadler, Manfred, 2003. "Innovation and growth: The role of labor-force qualification," Tübinger Diskussionsbeiträge 255, University of Tübingen, School of Business and Economics.
    57. Weber, Enzo, 2007. "Who Leads Financial Markets?," MPRA Paper 5099, University Library of Munich, Germany, revised Oct 2007.
    58. Baten, Jörg & Wallusch, Jacek, 2003. "Market integration and disintegration of Poland and Gemany [Germany] in the 18th century," Tübinger Diskussionsbeiträge 268, University of Tübingen, School of Business and Economics.
    59. Audi, Marc & Sadiq, Azhar & Ali, Amjad, 2021. "Performance Evaluation of Islamic and Non-Islamic Equity and Bonds Indices: Evidence from selected Emerging and Developed Countries," MPRA Paper 109866, University Library of Munich, Germany.
    60. Jung, R.C. & Maderitsch, R., 2014. "Structural breaks in volatility spillovers between international financial markets: Contagion or mere interdependence?," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 331-342.
    61. Seyed Alireza Athari & Dervis Kirikkaleli & Tomiwa Sunday Adebayo, 2023. "World pandemic uncertainty and German stock market: evidence from Markov regime-switching and Fourier based approaches," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1923-1936, April.
    62. Jose Luis Miralles-Marcelo & Jose Luis Miralles-Quiros & Maria del Mar Miralles-Quiros, 2010. "Intraday linkages between the Spanish and the US stock markets: evidence of an overreaction effect," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 223-235.
    63. Stelios D. Bekiros, 2013. "Decoupling and the Spillover Effects of the US Financial Crisis: Evidence from the BRIC Markets," Working Paper series 21_13, Rimini Centre for Economic Analysis.
    64. Haykir, Ozkan & Yagli, Ibrahim & Aktekin Gok, Emine Dilara & Budak, Hilal, 2022. "Oil price explosivity and stock return: Do sector and firm size matter?," Resources Policy, Elsevier, vol. 78(C).
    65. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).

  7. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.

    Cited by:

    1. Wooi Chen Khoo & Seng Huat Ong & Biswas Atanu, 2022. "Coherent Forecasting for a Mixed Integer-Valued Time Series Model," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    2. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2019. "Evaluating Approximate Point Forecasting of Count Processes," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    3. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • 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.
    5. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    6. Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
    7. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    8. Simon Nik & Christian H. Weiß, 2020. "CLAR(1) point forecasting under estimation uncertainty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 489-516, November.
    9. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.
    10. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    11. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.
    12. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    13. Christian H. Weiß, 2013. "Integer-valued autoregressive models for counts showing underdispersion," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1931-1948, September.
    14. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.
    15. Dungey Mardi & Martin Vance L. & Tang Chrismin & Tremayne Andrew, 2020. "A threshold mixed count time series model: estimation and application," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-18, April.
    16. Ruijun Bu & Kaddour Hadri & Brendan McCabe, 2006. "Conditional Maximum Likelihood Estimation of Higher-Order Integer-Valued Autoregressive Processes," Working Papers 200619, University of Liverpool, Department of Economics.
    17. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    18. Xinyang Wang & Dehui Wang & Kai Yang, 2021. "Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 713-750, July.
    19. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    20. Víctor Enciso‐Mora & Peter Neal & T. Subba Rao, 2009. "Efficient order selection algorithms for integer‐valued ARMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 1-18, January.
    21. Raju Maiti & Atanu Biswas, 2015. "Coherent forecasting for stationary time series of discrete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 337-365, July.
    22. Maia, Gisele de Oliveira & Barreto-Souza, Wagner & Bastos, Fernando de Souza & Ombao, Hernando, 2021. "Semiparametric time series models driven by latent factor," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1463-1479.
    23. Hee-Young Kim & Yousung Park, 2008. "A non-stationary integer-valued autoregressive model," Statistical Papers, Springer, vol. 49(3), pages 485-502, July.
    24. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    25. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    26. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
    27. Luisa Bisaglia & Margherita Gerolimetto, 2015. "Forecasting integer autoregressive processes of order 1: are simple AR competitive?," Economics Bulletin, AccessEcon, vol. 35(3), pages 1652-1660.
    28. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  8. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.

    Cited by:

    1. Konstantinos Fokianos & Anders Rahbek & Dag Tjøstheim, 2008. "Poisson Autoregression," Discussion Papers 08-35, University of Copenhagen. Department of Economics, revised Dec 2008.
    2. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    3. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    4. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    5. Tobias A. Möller & Christian H. Weiß & Hee-Young Kim & Andrei Sirchenko, 2018. "Modeling Zero Inflation in Count Data Time Series with Bounded Support," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 589-609, June.
    6. Weiß, Christian H., 2010. "INARCH(1) processes: Higher-order moments and jumps," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1771-1780, December.
    7. Cathy W. S. Chen & Sangyeol Lee, 2017. "Bayesian causality test for integer-valued time series models with applications to climate and crime data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 797-814, August.
    8. Cathy W. S. Chen & Sangyeol Lee & K. Khamthong, 2021. "Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts," Computational Statistics, Springer, vol. 36(1), pages 261-281, March.
    9. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    10. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    11. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    12. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    13. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    14. Jiwon Kang & Sangyeol Lee, 2014. "Parameter Change Test for Poisson Autoregressive Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1136-1152, December.
    15. Siem Jan Koopman & Rutger Lit & André Lucas, 2017. "Intraday Stochastic Volatility in Discrete Price Changes: The Dynamic Skellam Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1490-1503, October.
    16. Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
    17. Jung, Robert C. & Liesenfeld, Roman & Richard, Jean-François, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 73-85.
    18. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    19. Kai Yang & Qingqing Zhang & Xinyang Yu & Xiaogang Dong, 2023. "Bayesian inference for a mixture double autoregressive model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 188-207, May.
    20. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    21. Jean-François Richard, 2015. "Likelihood Based Inference and Prediction in Spatio-temporal Panel Count Models for Urban Crimes," Working Paper 5657, Department of Economics, University of Pittsburgh.
    22. Fokianos, Konstantinos & Tjøstheim, Dag, 2011. "Log-linear Poisson autoregression," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 563-578, March.
    23. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    24. Vasiliki Christou & Konstantinos Fokianos, 2014. "Quasi-Likelihood Inference For Negative Binomial Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(1), pages 55-78, January.
    25. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    26. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos & Touche, Nassim, 2019. "Integer-valued stochastic volatility," MPRA Paper 91962, University Library of Munich, Germany, revised 04 Feb 2019.
    27. Christian Weiß, 2009. "Modelling time series of counts with overdispersion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 507-519, November.
    28. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    29. Kharin, Yuriy & Voloshko, Valeriy, 2021. "Robust estimation for Binomial conditionally nonlinear autoregressive time series based on multivariate conditional frequencies," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    30. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    31. Igor Kheifets & Carlos Velasco, 2013. "New Goodness-of-fit Diagnostics for Conditional Discrete Response Models," Cowles Foundation Discussion Papers 1924, Cowles Foundation for Research in Economics, Yale University.
    32. Juan Dolado, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 442-446, September.
    33. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    34. Klingenberg, Bernhard, 2008. "Regression models for binary time series with gaps," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4076-4090, April.
    35. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    36. Fokianos, Konstantions & Fried, Roland, 2009. "Interventions in ingarch processes," Technical Reports 2009,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    37. Roman Liesenfeld & Jean‐François Richard & Jan Vogler, 2017. "Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 600-620, April.
    38. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    39. Robert C. Jung & Roman Liesenfeld & Jean-François Richard, 2011. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 73-85, January.
    40. Konstantinos Fokianos & Dag Tjøstheim, 2012. "Nonlinear Poisson autoregression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(6), pages 1205-1225, December.
    41. Kang, Jiwon & Lee, Sangyeol, 2014. "Minimum density power divergence estimator for Poisson autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 44-56.
    42. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    43. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    44. Guy P. Nason & Daniel Bailey, 2008. "Estimating the intensity of conflict in Iraq," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 899-914, October.
    45. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    46. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    47. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    48. Chen, Cathy W.S. & Chen, Chun-Shu & Hsiung, Mo-Hua, 2023. "Bayesian modeling of spatial integer-valued time series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    49. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.
    50. José M. R. Murteira & Mário A. G. Augusto, 2017. "Hurdle models of repayment behaviour in personal loan contracts," Empirical Economics, Springer, vol. 53(2), pages 641-667, September.

  9. Robert Jung & Gerd Ronning & A. Tremayne, 2005. "Estimation in conditional first order autoregression with discrete support," Statistical Papers, Springer, vol. 46(2), pages 195-224, April.

    Cited by:

    1. Christian H. Weiß, 2012. "Fully observed INAR(1) processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 581-598, July.
    2. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    3. Vladica S. Stojanović & Hassan S. Bakouch & Eugen Ljajko & Najla Qarmalah, 2023. "Zero-and-One Integer-Valued AR(1) Time Series with Power Series Innovations and Probability Generating Function Estimation Approach," Mathematics, MDPI, vol. 11(8), pages 1-25, April.
    4. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    5. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
    6. Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
    7. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    8. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    9. Jonas Andersson & Dimitris Karlis, 2010. "Treating missing values in INAR(1) models: An application to syndromic surveillance data," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(1), pages 12-19, January.
    10. Christian H. Weiß, 2013. "Integer-valued autoregressive models for counts showing underdispersion," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1931-1948, September.
    11. Sebastian Schweer & Christian H. Weiß, 2016. "Testing for Poisson arrivals in INAR(1) processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 503-524, September.
    12. Christian H. Weiß & Annika Homburg & Pedro Puig, 2019. "Testing for zero inflation and overdispersion in INAR(1) models," Statistical Papers, Springer, vol. 60(3), pages 823-848, June.
    13. Dungey Mardi & Martin Vance L. & Tang Chrismin & Tremayne Andrew, 2020. "A threshold mixed count time series model: estimation and application," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-18, April.
    14. Kai Yang & Dehui Wang & Boting Jia & Han Li, 2018. "An integer-valued threshold autoregressive process based on negative binomial thinning," Statistical Papers, Springer, vol. 59(3), pages 1131-1160, September.
    15. Schweer, Sebastian & Weiß, Christian H., 2014. "Compound Poisson INAR(1) processes: Stochastic properties and testing for overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 267-284.
    16. Sebastian Schweer, 2016. "A Goodness-of-Fit Test for Integer-Valued Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 77-98, January.
    17. Han Li & Kai Yang & Shishun Zhao & Dehui Wang, 2018. "First-order random coefficients integer-valued threshold autoregressive processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 305-331, July.
    18. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    19. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    20. Maxime Faymonville & Carsten Jentsch & Christian H. Weiß & Boris Aleksandrov, 2023. "Semiparametric estimation of INAR models using roughness penalization," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 365-400, June.
    21. Lucio Palazzo & Riccardo Ievoli, 2022. "A Semiparametric Approach to Test for the Presence of INAR: Simulations and Empirical Applications," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    22. Predrag M. Popović & Miroslav M. Ristić & Aleksandar S. Nastić, 2016. "A geometric bivariate time series with different marginal parameters," Statistical Papers, Springer, vol. 57(3), pages 731-753, September.
    23. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2022. "Bias-correction of some estimators in the INAR(1) process," Statistics & Probability Letters, Elsevier, vol. 187(C).
    24. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    25. Christian H. Weiß, 2011. "Detecting mean increases in Poisson INAR(1) processes with EWMA control charts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 383-398, September.
    26. Andersson, Jonas & Karlis, Dimitris, 2008. "Treating missing values in INAR(1) models," Discussion Papers 2008/14, Norwegian School of Economics, Department of Business and Management Science.
    27. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
    28. Luisa Bisaglia & Margherita Gerolimetto, 2015. "Forecasting integer autoregressive processes of order 1: are simple AR competitive?," Economics Bulletin, AccessEcon, vol. 35(3), pages 1652-1660.
    29. José M. R. Murteira & Mário A. G. Augusto, 2017. "Hurdle models of repayment behaviour in personal loan contracts," Empirical Economics, Springer, vol. 53(2), pages 641-667, September.

  10. Robert C. Jung & A. R. Tremayne, 2003. "Testing for serial dependence in time series models of counts," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 65-84, January.

    Cited by:

    1. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
    2. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    3. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    4. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
    5. Christian Weiß, 2015. "A Poisson INAR(1) model with serially dependent innovations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 829-851, October.
    6. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    7. Alfredo García-Hiernaux, 2009. "Diagnostic checking using subspace methods," Documentos de Trabajo del ICAE 2009-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    8. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    9. Khan Naushad Mamode & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Analyzing the Full BINMA Time Series Process Using a Robust GQL Approach," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-12, July.
    10. Franklin E. Zimring & Jeffrey Fagan & David T. Johnson, 2010. "Executions, Deterrence, and Homicide: A Tale of Two Cities," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 7(1), pages 1-29, March.
    11. Lucio Palazzo & Riccardo Ievoli, 2022. "A Semiparametric Approach to Test for the Presence of INAR: Simulations and Empirical Applications," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    12. R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 701-722, September.
    13. Masoomeh Forughi & Zohreh Shishebor & Atefeh Zamani, 2022. "Portmanteau tests for generalized integer-valued autoregressive time series models," Statistical Papers, Springer, vol. 63(4), pages 1163-1185, August.
    14. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
    15. Robert Jung & Gerd Ronning & A. Tremayne, 2005. "Estimation in conditional first order autoregression with discrete support," Statistical Papers, Springer, vol. 46(2), pages 195-224, April.

  11. Roman Liesenfeld & Robert C. Jung, 2000. "Stochastic volatility models: conditional normality versus heavy-tailed distributions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 137-160.
    See citations under working paper version above.
  12. Jung, Robert C & Winkelmann, Rainer, 1993. "Two Aspects of Labor Mobility: A Bivariate Poisson Regression Approach," Empirical Economics, Springer, vol. 18(3), pages 543-556.

    Cited by:

    1. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    2. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    3. FOUARGE Didier & MUFFELS Ruud & PAVLOPOULOS Dimitris & VERMUNT Jeroen K., 2007. "Who benefits from a job change: The dwarfs or the giants?," IRISS Working Paper Series 2007-16, IRISS at CEPS/INSTEAD.
    4. Caparros, A. & Navarro, M.L., 2005. "Factors Affecting Quits and Layoffs in Spanish Labour Market," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 5(4).
    5. M Ataharul Islam & Rafiqul I Chowdhury, 2017. "A generalized right truncated bivariate Poisson regression model with applications to health data," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
    6. Antonio Caparrós Ruiz & Mª. Lucía Navarro Gómez, 2002. "Factors affecting quits and layoffs in Spain," Economic Working Papers at Centro de Estudios Andaluces E2002/16, Centro de Estudios Andaluces.
    7. Bermúdez i Morata, Lluís, 2009. "A priori ratemaking using bivariate Poisson regression models," Insurance: Mathematics and Economics, Elsevier, vol. 44(1), pages 135-141, February.
    8. Lluis Bermúdez i Morata, 2008. "A priori ratemaking using bivariate poisson regression models," Working Papers XREAP2008-09, Xarxa de Referència en Economia Aplicada (XREAP), revised Jul 2008.
    9. Bauer, Thomas K. & Million, Andreas & Rotte, Ralph & Zimmermann, Klaus F., 1998. "Immigration Labor and Workplace Safety," IZA Discussion Papers 16, Institute of Labor Economics (IZA).
    10. Najla Qarmalah & Abdulhamid A. Alzaid, 2023. "Zero-Dependent Bivariate Poisson Distribution with Applications," Mathematics, MDPI, vol. 11(5), pages 1-16, February.
    11. Su Pei-Fang & Mau Yu-Lin & Li Chung-I & Guo Yan & Liu Qi & Shyr Yu & Boice John D., 2017. "Bivariate Poisson models with varying offsets: an application to the paired mitochondrial DNA dataset," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(1), pages 47-58, March.
    12. Rajib Dey & M. Ataharul Islam, 2017. "A conditional count model for repeated count data and its application to GEE approach," Statistical Papers, Springer, vol. 58(2), pages 485-504, June.
    13. Tzougas, George & Makariou, Despoina, 2022. "The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," LSE Research Online Documents on Economics 117197, London School of Economics and Political Science, LSE Library.
    14. Begona Alvarez & Daniel Miles, "undated". "Gender Effect on Housework Allocation: Evidence from Spanish Two-Earner Couples," Studies on the Spanish Economy 114, FEDEA.
    15. Marco Alfò & Giovanni Trovato, 2004. "Semiparametric Mixture Models for Multivariate Count Data, with Application," CEIS Research Paper 51, Tor Vergata University, CEIS.
    16. Atella, Vincenzo & Deb, Partha, 2008. "Are primary care physicians, public and private sector specialists substitutes or complements? Evidence from a simultaneous equations model for count data," Journal of Health Economics, Elsevier, vol. 27(3), pages 770-785, May.
    17. William Greene, 2007. "Correlation in Bivariate Poisson Regression Model," Working Papers 07-14, New York University, Leonard N. Stern School of Business, Department of Economics.
    18. Chen, Yulong & Ma, Liyuan & Orazem, Peter F., 2023. "The heterogeneous role of broadband access on establishment entry and exit by sector and urban and rural markets," Telecommunications Policy, Elsevier, vol. 47(3).
    19. George Tzougas & Despoina Makariou, 2022. "The multivariate Poisson‐Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 25(4), pages 401-417, December.
    20. Miravete, Eugenio, 2009. "Multivariate Sarmanov Count Data Models," CEPR Discussion Papers 7463, C.E.P.R. Discussion Papers.

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