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Tim Bollerslev

Citations

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

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.

    Mentioned in:

    1. On Forecasting Variation and Covariation
      by Francis Diebold in No Hesitations on 2016-05-02 06:01:00
  2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2002. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange?," Center for Financial Institutions Working Papers 02-23, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Mentioned in:

    1. Trading on Leaked Macroeconomic Data
      by noreply@blogger.com (Carola) in Quantitative Ease on 2015-07-08 22:14:00
    2. 'Trading on Leaked Macroeconomic Data'
      by Mark Thoma in Economist's View on 2015-07-08 15:39:09

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2010. "Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 233-261.

    Mentioned in:

    1. Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns (Journal of Applied Econometrics 2010) in ReplicationWiki ()
  2. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.

    Mentioned in:

    1. Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model (Journal of Applied Econometrics 2002) in ReplicationWiki ()
  3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.

    Mentioned in:

    1. Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange (AER 2003) in ReplicationWiki ()

Working papers

  1. Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.

    Cited by:

    1. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    2. Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
    3. Chiah, Mardy & Long, Huaigang & Zaremba, Adam & Umar, Zaghum, 2023. "Trade competitiveness and the aggregate returns in global stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    4. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    5. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    6. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    7. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    8. Zhang, Lixia & Luo, Qin & Guo, Xiaozhu & Umar, Muhammad, 2022. "Medium-term and long-term volatility forecasts for EUA futures with country-specific economic policy uncertainty indices," Resources Policy, Elsevier, vol. 77(C).
    9. Fei Su & Lei Wang, 2020. "Conditional Volatility Persistence and Realized Volatility Asymmetry: Evidence from the Chinese Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(14), pages 3252-3269, November.
    10. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Wang, Jianqiong, 2020. "Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models," Energy, Elsevier, vol. 212(C).
    11. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    12. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    13. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    15. Wang, Jiqian & Li, Liang, 2023. "Climate risk and Chinese stock volatility forecasting: Evidence from ESG index," Finance Research Letters, Elsevier, vol. 55(PA).
    16. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    17. Li, Xiafei & Liao, Yin & Lu, Xinjie & Ma, Feng, 2022. "An oil futures volatility forecast perspective on the selection of high-frequency jump tests," Energy Economics, Elsevier, vol. 116(C).
    18. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    20. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    21. Guo, Xiaozhu & Huang, Dengshi & Li, Xiafei & Liang, Chao, 2023. "Are categorical EPU indices predictable for carbon futures volatility? Evidence from the machine learning method," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 672-693.
    22. Lu, Fei & Ma, Feng, 2023. "Cross-sectional uncertainty and stock market volatility: New evidence," Finance Research Letters, Elsevier, vol. 57(C).
    23. Yusui Tang & Feng Ma & Yaojie Zhang & Yu Wei, 2022. "Forecasting the oil price realized volatility: A multivariate heterogeneous autoregressive model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4770-4783, October.
    24. Schmeling, Maik & Medhat, Mamdouh, 2021. "Short-term Momentum," CEPR Discussion Papers 15857, C.E.P.R. Discussion Papers.
    25. Hu, Junjie & Kuo, Weiyu & Härdle, Wolfgang Karl, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," IRTG 1792 Discussion Papers 2019-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    26. Liu, Zhichao & Liu, Jing & Zeng, Qing & Wu, Lan, 2022. "VIX and stock market volatility predictability: A new approach," Finance Research Letters, Elsevier, vol. 48(C).
    27. Jiqian Wang & Rangan Gupta & Oğuzhan Çepni & Feng Ma, 2023. "Forecasting international REITs volatility: the role of oil-price uncertainty," The European Journal of Finance, Taylor & Francis Journals, vol. 29(14), pages 1579-1597, September.
    28. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    29. 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).
    30. Wang, Jianxin, 2022. "Market distraction and near-zero daily volatility persistence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    31. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    32. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    33. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    34. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
    35. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    36. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    37. Su, Fei & Wang, Xinyi & Yuan, Yulin, 2022. "The intraday dynamics and intraday price discovery of bitcoin," Research in International Business and Finance, Elsevier, vol. 60(C).
    38. Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
    39. Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
    40. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    41. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    42. Lyócsa, Štefan & Plíhal, Tomáš, 2022. "Russia’s ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Finance Research Letters, Elsevier, vol. 48(C).
    43. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    44. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "A novel cluster HAR-type model for forecasting realized volatility," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1318-1331.
    45. Tong, Chen & Huang, Zhuo & Wang, Tianyi & Zhang, Cong, 2023. "The effects of economic uncertainty on financial volatility: A comprehensive investigation," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 369-389.
    46. Jiqian Wang & Feng Ma & Chao Liang & Zhonglu Chen, 2022. "Volatility forecasting revisited using Markov‐switching with time‐varying probability transition," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1387-1400, January.
    47. Yaojie Zhang & Mengxi He & Yuqi Zhao & Xianfeng Hao, 2023. "Predicting stock realized variance based on an asymmetric robust regression approach," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1022-1047, October.
    48. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
    49. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
    50. Chen, Zhonglu & Ye, Yong & Li, Xiafei, 2022. "Forecasting China's crude oil futures volatility: New evidence from the MIDAS-RV model and COVID-19 pandemic," Resources Policy, Elsevier, vol. 75(C).
    51. Demirovic, Amer & Kabiri, Ali & Tuckett, David & Nyman, Rickard, 2020. "A common risk factor and the correlation between equity and corporate bond returns," LSE Research Online Documents on Economics 116902, London School of Economics and Political Science, LSE Library.
    52. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    53. Martin Tegnér & Rolf Poulsen, 2018. "Volatility Is Log-Normal—But Not for the Reason You Think," Risks, MDPI, vol. 6(2), pages 1-16, April.
    54. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    55. Enrique Sentana, 2018. "Volatility, Diversification and Contagion," Working Papers wp2018_1803, CEMFI.
    56. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    57. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    58. Jifei Wang & Lingjing Wang, 2019. "Residual Switching Network for Portfolio Optimization," Papers 1910.07564, arXiv.org.
    59. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    60. Li Liu & Yudong Wang, 2021. "Forecasting aggregate market volatility: The role of good and bad uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 40-61, January.
    61. Amer Demirovic & Ali Kabiri & David Tuckett & Rickard Nyman, 2020. "A common risk factor and the correlation between equity and corporate bond returns," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 119-134, March.
    62. 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.
    63. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    64. Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org.
    65. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
    66. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.
    67. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    68. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    69. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    70. Ran Xiao, 2019. "Essays on Price Discovery and Volatility Dynamics in Emerging Market Currencies," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2019.
    71. Chao Liang & Yan Li & Feng Ma & Yaojie Zhang, 2022. "Forecasting international equity market volatility: A new approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1433-1457, November.
    72. Jorge M. Uribe, 2018. "“Scaling Down Downside Risk with Inter-Quantile Semivariances”," IREA Working Papers 201826, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    73. Schmeling, Maik & Wagner, Christian, 2019. "Does Central Bank Tone Move Asset Prices?," CEPR Discussion Papers 13490, C.E.P.R. Discussion Papers.
    74. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
    75. Imene Ben El Hadj Said & Skander Slim, 2022. "The Dynamic Relationship between Investor Attention and Stock Market Volatility: International Evidence," JRFM, MDPI, vol. 15(2), pages 1-25, February.
    76. Niu, Zibo & Ma, Feng & Zhang, Hongwei, 2022. "The role of uncertainty measures in volatility forecasting of the crude oil futures market before and during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 112(C).
    77. Wang, Jiqian & Ma, Feng & Bouri, Elie & Zhong, Juandan, 2022. "Volatility of clean energy and natural gas, uncertainty indices, and global economic conditions," Energy Economics, Elsevier, vol. 108(C).
    78. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    79. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    80. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    81. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    82. Xianfeng Hao & Yudong Wang, 2023. "Cloud cover and expected oil returns," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    83. Christina Sklibosios Nikitopoulos & Alice Carole Thomas & Jianxin Wang, 2024. "Hedging pressure and oil volatility: Insurance versus liquidity demands," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 252-280, February.
    84. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    85. Deev, Oleg & Plíhal, Tomáš, 2022. "How to calm down the markets? The effects of COVID-19 economic policy responses on financial market uncertainty," Research in International Business and Finance, Elsevier, vol. 60(C).
    86. 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.
    87. Wolfgang Drobetz & Rebekka Haller & Christian Jasperneite & Tizian Otto, 2019. "Predictability and the cross section of expected returns: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 508-533, December.
    88. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    89. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    90. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    91. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    92. Goodell, John W. & Alon, Ilan & Chiaramonte, Laura & Dreassi, Alberto & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Risk substitution in cryptocurrencies: Evidence from BRICS announcements," Emerging Markets Review, Elsevier, vol. 54(C).
    93. Angelidis, Timotheos & Tessaromatis, Nikolaos, 2023. "The disappearing profitability of volatility-managed equity factors," Journal of Financial Markets, Elsevier, vol. 65(C).
    94. Mohammad Jahan-Parvar & Filip Zikes, 2019. "When do low-frequency measures really measure transaction costs?," Finance and Economics Discussion Series 2019-051, Board of Governors of the Federal Reserve System (U.S.).
    95. Su, Fei, 2021. "Conditional volatility persistence and volatility spillovers in the foreign exchange market," Research in International Business and Finance, Elsevier, vol. 55(C).
    96. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).
    97. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).
    98. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    99. Qian, Lihua & Wang, Jiqian & Ma, Feng & Li, Ziyang, 2022. "Bitcoin volatility predictability–The role of jumps and regimes," Finance Research Letters, Elsevier, vol. 47(PB).
    100. v{S}tefan Ly'ocsa & Tom'av{s} Pl'ihal, 2022. "Russia's Ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Papers 2205.09179, arXiv.org.
    101. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
    102. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    103. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    104. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    105. Lu, Botao & Ma, Feng & Wang, Jiqian & Ding, Hui & Wahab, M.I.M., 2021. "Harnessing the decomposed realized measures for volatility forecasting: Evidence from the US stock market," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 672-689.
    106. Wang, Jiqian & Ma, Feng & Wang, Tianyang & Wu, Lan, 2023. "International stock volatility predictability: New evidence from uncertainties," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    107. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    108. 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).
    109. Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
    110. Wang, Jiqian & Huang, Yisu & Ma, Feng & Chevallier, Julien, 2020. "Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? New evidence," Energy Economics, Elsevier, vol. 91(C).
    111. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.
    112. Baltussen, Guido & Da, Zhi & Lammers, Sten & Martens, Martin, 2021. "Hedging demand and market intraday momentum," Journal of Financial Economics, Elsevier, vol. 142(1), pages 377-403.
    113. Grønborg, Niels S. & Lunde, Asger & Olesen, Kasper V. & Vander Elst, Harry, 2022. "Realizing correlations across asset classes," Journal of Financial Markets, Elsevier, vol. 59(PA).
    114. Lu, Xinjie & Lang, Qiaoqi, 2023. "Categorial economic policy uncertainty indices or Twitter-based uncertainty indices? Evidence from Chinese stock market," Finance Research Letters, Elsevier, vol. 55(PB).
    115. Loïc Maréchal, 2021. "Do economic variables forecast commodity futures volatility?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1735-1774, November.
    116. Hammadi Zouari, 2022. "On the Effectiveness of Stock Index Futures for Tail Risk Protection," International Journal of Economics and Financial Issues, Econjournals, vol. 12(3), pages 38-52, May.

  2. Tim Bollerslev & Jia Li & Yuan Xue, 2016. "Volume, Volatility and Public News Announcements," CREATES Research Papers 2016-19, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Schmeling, Maik & Schrimpf, Paul & Kroencke, Tim, 2019. "The FOMC Risk Shift," CEPR Discussion Papers 14037, C.E.P.R. Discussion Papers.
    2. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    3. Bianchi, Francesco & Gómez-Cram, Roberto & Kind, Thilo & Kung, Howard, 2023. "Threats to central bank independence: High-frequency identification with twitter," Journal of Monetary Economics, Elsevier, vol. 135(C), pages 37-54.
    4. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2022. "Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    5. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    6. McMahon, Michael & Ahrens, Maximilian & Erdemlioglu, Deniz & Neely, Christopher J & Yang, Xiye, 2023. "Mind Your Language: Market Responses to Central Bank Speeches," CEPR Discussion Papers 18191, C.E.P.R. Discussion Papers.
    7. Monaco, Eleonora & Murgia, Lucia Milena, 2023. "Retail attention and the FOMC equity premium," Finance Research Letters, Elsevier, vol. 53(C).
    8. Jia Li & Peter C. B. Phillips & Shuping Shi & Jun Yu, 2022. "Weak Identification of Long Memory with Implications for Inference," Cowles Foundation Discussion Papers 2334, Cowles Foundation for Research in Economics, Yale University.
    9. Bodilsen, Simon & Eriksen, Jonas N. & Grønborg, Niels S., 2021. "Asset pricing and FOMC press conferences," Journal of Banking & Finance, Elsevier, vol. 128(C).
    10. Bertelsen, Kristoffer Pons & Borup, Daniel & Jakobsen, Johan Stax, 2021. "Stock market volatility and public information flow: A non-linear perspective," Economics Letters, Elsevier, vol. 204(C).
    11. Guo, Feng & Lin, Zhiyuan & Lyu, Xiaoliang & Shi, Qingling, 2023. "Does air pollution influence music sentiment? Measuring music sentiment by machine learning," Journal of Asian Economics, Elsevier, vol. 87(C).
    12. Tim Bollerslev & Jia Li & Leonardo Salim Saker Chaves, 2021. "Generalized Jump Regressions for Local Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1015-1025, October.
    13. Meirowitz, Adam & Pi, Shaoting, 2022. "Voting and trading: The shareholder’s dilemma," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1073-1096.
    14. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    15. Wang, Cindy S.H. & Chen, Yi-Chi & Lo, Hsin-Yu, 2021. "A fresh look at the risk-return tradeoff," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    16. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Oct 2022.
    17. Crego, Julio A., 2020. "Why does public news augment information asymmetries?," Journal of Financial Economics, Elsevier, vol. 137(1), pages 72-89.
    18. Fengler, Matthias & Polivka, Jeannine, 2021. "Identifying structural shocks to volatility through a proxy-MGARCH model," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised May 2021.
    19. Laurent Bouton & Aniol Llorente-Saguer & Antonin Macé & Adam Meirowitz & Shaoting Pi & Dimitrios Xefteris, 2023. "Public Information as a Source of Disagreement Among Shareholders," Working Papers halshs-04075483, HAL.
    20. Caporin, Massimiliano & Poli, Francesco, 2022. "News and intraday jumps: Evidence from regularization and class imbalance," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    21. Federico A. Bugni & Jia Li & Qiyuan Li, 2023. "Permutation‐based tests for discontinuities in event studies," Quantitative Economics, Econometric Society, vol. 14(1), pages 37-70, January.
    22. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    23. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2021. "How does the financial market update beliefs about the real economy? Evidence from the oil market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 938-961, November.
    24. Angelo Ranaldo & Paolo Santucci de Magistris, 2018. "Trading Volume, Illiquidity and Commonalities in FX Markets," Working Papers on Finance 1823, University of St. Gallen, School of Finance, revised Oct 2019.
    25. Jian, Zhihong & Wu, Shuai & Zhu, Zhican, 2018. "Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach," Emerging Markets Review, Elsevier, vol. 37(C), pages 98-113.
    26. Doojin Ryu & Doowon Ryu & Heejin Yang, 2021. "The impact of net buying pressure on index options prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(1), pages 27-45, January.
    27. Sonya Zhu, 2023. "Volume dynamics around FOMC announcements," BIS Working Papers 1079, Bank for International Settlements.
    28. Ai, Hengjie & Han, Leyla Jianyu & Pan, Xuhui Nick & Xu, Lai, 2022. "The cross section of the monetary policy announcement premium," Journal of Financial Economics, Elsevier, vol. 143(1), pages 247-276.
    29. Akbari, Amir & Krystyniak, Karolina, 2021. "Government real estate interventions and the stock market," International Review of Financial Analysis, Elsevier, vol. 75(C).
    30. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
    31. Hasan Fallahgoul, 2020. "Inside the Mind of Investors During the COVID-19 Pandemic: Evidence from the StockTwits Data," Papers 2004.11686, arXiv.org, revised May 2020.
    32. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2018. "Formation of Market Beliefs in the Oil Market," CERGE-EI Working Papers wp619, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    33. Tim Bollerslev & Jia Li & Zhipeng Liao, 2021. "Fixed‐k inference for volatility," Quantitative Economics, Econometric Society, vol. 12(4), pages 1053-1084, November.
    34. Voges, Michelle & Sibbertsen, Philipp, 2021. "Cyclical fractional cointegration," Econometrics and Statistics, Elsevier, vol. 19(C), pages 114-129.
    35. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    36. Sherif, Mohamed, 2020. "The impact of Coronavirus (COVID-19) outbreak on faith-based investments: An original analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    37. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    38. Federico A. Bugni & Jia Li & Qiyuan Li, 2020. "Permutation-based tests for discontinuities in event studies," Papers 2007.09837, arXiv.org, revised Jul 2022.
    39. Jameson K. M. Watts, 2020. "Language Consistency and Stock Market Trading Volume," SAGE Open, , vol. 10(2), pages 21582440209, May.
    40. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  3. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Hautsch, Nikolaus & Voigt, Stefan, 2017. "Large-scale portfolio allocation under transaction costs and model uncertainty," CFS Working Paper Series 582, Center for Financial Studies (CFS).
    2. Lv, Fei & Yang, Chen & Fang, Libing, 2020. "Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    4. Joel Hasbrouck, 2021. "Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 395-430.
    5. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2019. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Papers 1910.13960, arXiv.org, revised Oct 2020.
    6. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    8. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    9. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    10. Carlo Drago & Andrea Scozzari, 2023. "A Network-Based Analysis for Evaluating Conditional Covariance Estimates," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    11. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    12. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    13. Gaoxiu Qiao & Yangli Cao & Feng Ma & Weiping Li, 2023. "Liquidity and realized covariance forecasting: a hybrid method with model uncertainty," Empirical Economics, Springer, vol. 64(1), pages 437-463, January.
    14. Fabrizio Cipollini & Giampiero M. Gallo & Alessandro Palandri, 2020. "A dynamic conditional approach to portfolio weights forecasting," Papers 2004.12400, arXiv.org.
    15. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    16. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    17. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
    18. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2022. "Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality," Working Papers 202232, University of Pretoria, Department of Economics.
    19. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    20. Yutong Lu & Gesine Reinert & Mihai Cucuringu, 2023. "Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets," Papers 2302.09382, arXiv.org.
    21. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    22. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. Bekierman, Jeremias & Manner, Hans, 2018. "Forecasting realized variance measures using time-varying coefficient models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 276-287.
    24. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    25. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    26. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    27. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    28. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    29. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. Andre Lucas & Anne Opschoor & Luca Rossini, 2021. "Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution," Tinbergen Institute Discussion Papers 21-010/III, Tinbergen Institute, revised 11 Jul 2023.
    31. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    32. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    33. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2023. "The effect of uncertainty on stock market volatility and correlation," Journal of Banking & Finance, Elsevier, vol. 154(C).
    34. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    35. Sven Husmann & Antoniya Shivarova & Rick Steinert, 2021. "Cross-validated covariance estimators for high-dimensional minimum-variance portfolios," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 309-352, September.
    36. Jiawen Luo & Qun Zhang, 2024. "Air pollution, weather factors, and realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 151-217, February.
    37. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.
    38. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    39. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    40. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.

  4. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2015. "Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting," CREATES Research Papers 2015-14, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    2. Han, Chulwoo & Park, Frank C., 2022. "A geometric framework for covariance dynamics," Journal of Banking & Finance, Elsevier, vol. 134(C).
    3. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    4. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.
    6. Thijs Benschop & Brenda López Cabrera, 2017. "Realized volatility of CO2 futures," SFB 649 Discussion Papers SFB649DP2017-025, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    8. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    9. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    10. Evan Anderson & Ai-ru (Meg) Cheng, 2022. "Portfolio Choices with Many Big Models," Management Science, INFORMS, vol. 68(1), pages 690-715, January.
    11. Lai T. Hoang & Dirk G. Baur, 2020. "Forecasting bitcoin volatility: Evidence from the options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1584-1602, October.
    12. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    13. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2022. "Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    14. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    15. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    16. Kim Christensen & Charlotte Christiansen & Anders M. Posselt, 2019. "The Economic Value of VIX ETPs," CREATES Research Papers 2019-14, Department of Economics and Business Economics, Aarhus University.
    17. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    18. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
    19. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    20. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    21. Wang, Yajing & Liang, Fang & Wang, Tianyi & Huang, Zhuo, 2020. "Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 87(C), pages 148-157.
    22. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    23. Jiayuan Zhou & Feiyu Jiang & Ke Zhu & Wai Keung Li, 2019. "Time series models for realized covariance matrices based on the matrix-F distribution," Papers 1903.12077, arXiv.org, revised Jul 2020.
    24. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira Da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    26. Wang, Xiaohu & Xiao, Weilin & Yu, Jun, 2023. "Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process," Journal of Econometrics, Elsevier, vol. 232(2), pages 389-415.
    27. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    28. Sebastiano Michele Zema, 2023. "A non-Normal framework for price discovery: The independent component based information shares measure," LEM Papers Series 2023/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    29. Lv, Wendai, 2018. "Does the OVX matter for volatility forecasting? Evidence from the crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 916-922.
    30. Qiao, Gaoxiu & Teng, Yuxin & Li, Weiping & Liu, Wenwen, 2019. "Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 133-151.
    31. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    32. Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017. "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, vol. 61(C), pages 12-26.
    33. Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018. "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, vol. 72(C), pages 321-330.
    34. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
    35. Eghbal Rahimikia & Stefan Zohren & Ser-Huang Poon, 2021. "Realised Volatility Forecasting: Machine Learning via Financial Word Embedding," Papers 2108.00480, arXiv.org, revised Mar 2023.
    36. Clements, Adam & Vasnev, Andrey, 2021. "Forecast combination puzzle in the HAR model," Working Papers BAWP-2021-01, University of Sydney Business School, Discipline of Business Analytics.
    37. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    38. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    39. Clements, Adam & Hurn, Stan & Volkov, Vladimir, 2021. "A simple linear alternative to multiplicative error models with an application to trading volume," Working Papers 2021-06, University of Tasmania, Tasmanian School of Business and Economics.
    40. Liu, Guangqiang & Wang, Yan & Chen, Xiaodan & Zhang, Yifeng & Shang, Yue, 2020. "Forecasting volatility of the Chinese stock markets using TVP HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    41. Emese Lazar & Shuyuan Qi & Radu Tunaru, 2020. "Measures of Model Risk in Continuous-time Finance Models," Papers 2010.08113, arXiv.org, revised Oct 2020.
    42. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    43. Wang, Jianxin, 2022. "Market distraction and near-zero daily volatility persistence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    44. A Clements & D Preve, 2019. "A Practical Guide to Harnessing the HAR Volatility Model," NCER Working Paper Series 120, National Centre for Econometric Research.
    45. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    46. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
    47. Dudley Gilder & Leonidas Tsiaras, 2020. "Volatility forecasts embedded in the prices of crude‐oil options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1127-1159, July.
    48. Dicle, Mehmet F. & Levendis, John, 2020. "Historic risk and implied volatility," Global Finance Journal, Elsevier, vol. 45(C).
    49. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    50. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    51. Bent Jesper Christensen & Mads Markvart Kjær & Bezirgen Veliyev, 2021. "The incremental information in the yield curve about future interest rate risk," CREATES Research Papers 2021-11, Department of Economics and Business Economics, Aarhus University.
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    2. Maghyereh, Aktham & Abdoh, Hussein, 2022. "Extreme dependence between structural oil shocks and stock markets in GCC countries," Resources Policy, Elsevier, vol. 76(C).
    3. Kingstone Nyakurukwa & Yudhvir Seetharam, 2023. "Higher moment connectedness of cryptocurrencies: a time-frequency approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 793-814, September.
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    5. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    6. Ruan, Xinfeng & Zhang, Jin E., 2021. "The economics of the financial market for volatility trading," Journal of Financial Markets, Elsevier, vol. 52(C).
    7. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    8. Brice Corgnet & Camille Cornand & Nobuyuki Hanaki, 2024. "Emotional Markets: Competitive Arousal, Overbidding and Bubbles," Working Papers hal-04473406, HAL.
    9. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
    10. Ke-Li Xu & Junjie Guo, 2021. "A New Test for Multiple Predictive Regression," CAEPR Working Papers 2022-001 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
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    24. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    25. Davis, Richard & Drees, Holger & Segers, Johan & Warchol, Michal, 2018. "Inference on the tail process with application to financial time series modelling," LIDAM Discussion Papers ISBA 2018002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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    68. Luo, Di & Mishra, Tapas & Yarovaya, Larisa & Zhang, Zhuang, 2021. "Investing during a Fintech Revolution: Ambiguity and return risk in cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
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    71. Kwon, Ji Ho, 2019. "Tail risk and the consumption CAPM," Finance Research Letters, Elsevier, vol. 30(C), pages 69-75.
    72. Bai, Jennie & Goldstein, Robert S. & Yang, Fan, 2020. "Is the credit spread puzzle a myth?," Journal of Financial Economics, Elsevier, vol. 137(2), pages 297-319.
    73. Scaillet, Olivier & Trojani, Fabio & Camponovo, Lorenzo, 2016. "Comments on : Nonparametric Tail Risk, Stock Returns and the Macroeconomy," Working Papers unige:84999, University of Geneva, Geneva School of Economics and Management.
    74. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    75. Brice Corgnet & Camille Cornand & Nobuyuki Hanaki, 2021. "Risk-Taking and Tail Events Across Trading Institutions," Working Papers halshs-03357898, HAL.
    76. Brice Corgnet & Camille Cornand & Nobuyuki Hanaki, 2020. "Tail events, emotions and risk taking," Working Papers halshs-02613344, HAL.
    77. K. Victor Chow & Wanjun Jiang & Bingxin Li & Jingrui Li, 2020. "Decomposing the VIX: Implications for the predictability of stock returns," The Financial Review, Eastern Finance Association, vol. 55(4), pages 645-668, November.
    78. Da Fonseca, José & Xu, Yahua, 2017. "Higher moment risk premiums for the crude oil market: A downside and upside conditional decomposition," Energy Economics, Elsevier, vol. 67(C), pages 410-422.
    79. Xing Jin & Dan Luo & Xudong Zeng, 2021. "Tail Risk and Robust Portfolio Decisions," Management Science, INFORMS, vol. 67(5), pages 3254-3275, May.
    80. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    81. George P. Gao & Xiaomeng Lu & Zhaogang Song, 2019. "Tail Risk Concerns Everywhere," Management Science, INFORMS, vol. 65(7), pages 3111-3130, July.
    82. Hu, Debao & Li, Xin & Xiang, George & Zhou, Qiyao, 2023. "Asset pricing models in the presence of higher moments: Theory and evidence from the U.S. and China stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    83. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
    84. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation In Extreme Value Regression Models Of Hedge Fund Tail Risks," Working Papers hal-04090916, HAL.
    85. Masato Ubukata, 2022. "A time-varying jump tail risk measure using high-frequency options data," Empirical Economics, Springer, vol. 63(5), pages 2633-2653, November.
    86. Julien Hambuckers & Marie Kratz & Antoine Usseglio-Carleve, 2023. "Efficient Estimation in Extreme Value Regression Models of Hedge Fund Tail Risks," Papers 2304.06950, arXiv.org.
    87. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2018. "The Pricing of Tail Risk and the Equity Premium: Evidence from International Option Markets," CREATES Research Papers 2018-02, Department of Economics and Business Economics, Aarhus University.
    88. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    89. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    90. Oh, Sekyung & Kee, Hyukdo & Park, Kinam, 2019. "Tail risk under price limits," Economic Modelling, Elsevier, vol. 77(C), pages 113-123.
    91. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    92. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    93. Sonnan Chen & Yuchi Gu, 2021. "Joint estimation of volatility risk and tail risk premia with time-varying macro-state-dependent property," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1357-1397, May.
    94. Hsuan‐Ling Chang & Yen‐Cheng Chang & Hung‐Wen Cheng & Po‐Hsiang Peng & Kevin Tseng, 2019. "Jump variance risk: Evidence from option valuation and stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 890-915, July.
    95. Masato Ubukata, 2019. "Jump tail risk premium and predicting US and Japanese credit spreads," Empirical Economics, Springer, vol. 57(1), pages 79-104, July.
    96. Liu, Yiye & Han, Liyan & Wu, You, 2022. "Can skewness predict CNY-CNH spread?," Finance Research Letters, Elsevier, vol. 46(PB).
    97. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    98. Mirco Rubin & Dario Ruzzi, 2020. "Equity Tail Risk in the Treasury Bond Market," Papers 2007.05933, arXiv.org.
    99. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    100. Bjørn Eraker & Aoxiang Yang, 2022. "The Price of Higher Order Catastrophe Insurance: The Case of VIX Options," Journal of Finance, American Finance Association, vol. 77(6), pages 3289-3337, December.
    101. Jeroen V.K. Rombouts & Lars Stentoft & Francesco Violante, 2017. "Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability," CREATES Research Papers 2017-10, Department of Economics and Business Economics, Aarhus University.
    102. Reinhard Ellwanger, 2017. "On the Tail Risk Premium in the Oil Market," Staff Working Papers 17-46, Bank of Canada.
    103. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    104. Kwon, Ji Ho, 2020. "Tail behavior of Bitcoin, the dollar, gold and the stock market index," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    105. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
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  6. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    2. Jiri Novak, 2015. "Systematic Risk Changes, Negative Realized Excess Returns and Time-Varying CAPM Beta," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 167-190, April.
    3. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.

  7. Tim Bollerslev & Andrew J. Patton & Wang Wenjing, 2013. "Daily House Price Indexes: Construction, Modeling, and Longer-Run Predictions," Working Papers 13-29, Duke University, Department of Economics.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
    2. Aviral Kumar Tiwari & Rangan Gupta & Juncal Cunado & Xin Sheng, 2019. "Testing the White Noise Hypothesis in High-Frequency Housing Returns of the United States," Working Papers 201952, University of Pretoria, Department of Economics.
    3. Robert J. Hill & Alicia N. Rambaldi, 2022. "Hedonic Models and House Price Index Numbers," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 413-444, Springer.
    4. Wang, Xiaodan & Li, Keyang & Wu, Jing, 2020. "House price index based on online listing information: The case of China," Journal of Housing Economics, Elsevier, vol. 50(C).
    5. Isaiah Hull & Conny Olovsson & Karl Walentin & Andreas Westermark, 2022. "Manufacturing Decline and House Price Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 264-281, July.
    6. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2018. "Higher Frequency Hedonic Property Price Indices: A State Space Approach," Graz Economics Papers 2018-04, University of Graz, Department of Economics.
    7. Franziska Bremus & Thomas Krause & Felix Noth, 2021. "Lender-Specific Mortgage Supply Shocks and Macroeconomic Performance in the United States," Discussion Papers of DIW Berlin 1936, DIW Berlin, German Institute for Economic Research.
    8. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    9. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    10. Ryan Greenaway-McGrevy & Kade Sorensen, 2021. "A spatial model averaging approach to measuring house prices," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-32, December.
    11. Jian Yang & Meng Tong & Ziliang Yu, 2023. "Can volume be more informative than prices? Evidence from Chinese housing markets," Review of Quantitative Finance and Accounting, Springer, vol. 61(2), pages 633-672, August.
    12. Mehmet Balcilar & Elie Bouri & Rangan Gupta & Mark E. Wohar, 2018. "Mortgage Default Risks and High-Frequency Predictability of the US Housing Market: A Reconsideration," Working Papers 201875, University of Pretoria, Department of Economics.
    13. Aviral Kumar Tiwari & Rangan Gupta & Mark E. Wohar, 2019. "Is the Housing Market in the United States Really Weakly-Efficient?," Working Papers 201934, University of Pretoria, Department of Economics.
    14. Franziska Bremus & Thomas Krause & Felix Noth, 2017. "Bank-Specific Shocks and House Price Growth in the U.S," Discussion Papers of DIW Berlin 1636, DIW Berlin, German Institute for Economic Research.
    15. Elie Bouri & Rangan Gupta & Clement Kweku Kyei & Rinsuna Shivambu, 2020. "Uncertainty and Daily Predictability of Housing Returns and Volatility of the United States: Evidence from a Higher-Order Nonparametric Causality-in-Quantiles Test," Working Papers 202071, University of Pretoria, Department of Economics.
    16. Elie Bouri & Rangan Gupta & Hardik A. Marfatia & Jacobus Nel, 2022. "Do Climate Risks Predict US Housing Returns and Volatility? Evidence from a Quantiles-Based Approach," Working Papers 202240, University of Pretoria, Department of Economics.
    17. Elliot Anenberg & Steven Laufer, 2014. "Using Data on Seller Behavior to Forecast Short-run House Price Changes," Finance and Economics Discussion Series 2014-16, Board of Governors of the Federal Reserve System (U.S.).
    18. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High-Frequency Impact of Monetary Policy and Macroeconomic Surprises on US MSAs and Aggregate US Housing Returns and Volatility: A GJR-GARCH Approach," Working Papers 201817, University of Pretoria, Department of Economics.
    19. Yang, Jian & Tong, Meng & Yu, Ziliang, 2021. "Housing market spillovers through the lens of transaction volume: A new spillover index approach," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 351-378.
    20. Enwei Zhu & Jing Wu & Hongyu Liu & Keyang Li, 2023. "A Sentiment Index of the Housing Market in China: Text Mining of Narratives on Social Media," The Journal of Real Estate Finance and Economics, Springer, vol. 66(1), pages 77-118, January.
    21. Bremus, Franziska & Krause, Thomas & Noth, Felix, 2021. "Lender-specific mortgage supply shocks and macroeconomic performance in the United States," IWH Discussion Papers 3/2021, Halle Institute for Economic Research (IWH).
    22. Badarinza, Cristian & Ramadorai, Tarun, 2018. "Home away from home? Foreign demand and London house prices," Journal of Financial Economics, Elsevier, vol. 130(3), pages 532-555.
    23. Goodness C. Aye & Christina Christou & Rangan Gupta & Christis Hassapis, 2021. "High-Frequency Contagion between Aggregate and Regional Housing Markets of the United States with Financial Assets: Evidence from Multichannel Tests," Working Papers 202159, University of Pretoria, Department of Economics.
    24. Wendy Nyakabawo & Rangan Gupta & Hardik A. Marfatia, 2018. "High Frequency Impact Of Monetary Policy And Macroeconomic Surprises On Us Msas, Aggregate Us Housing Returns And Asymmetric Volatility," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 204-229, December.
    25. Lajos Horv'ath & Lorenzo Trapani, 2023. "Real-time monitoring with RCA models," Papers 2312.11710, arXiv.org.

  8. Tim Bollerslev & Lai Xu & Hao Zhou, 2012. "Stock Return and Cash Flow Predictability: The Role of Volatility Risk," CREATES Research Papers 2012-51, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. CHOW Alan & LAHTINEN Kyre Dane & EDWARDS Kelsey, 2020. "Comparison Of Estimators Of Equity Return Standard Deviation Using Pitman Closeness Criterion And Control Charting Applications," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 15(1), pages 5-12, April.
    2. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    3. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira Da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    5. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    6. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    7. Xiaomei Han & Wei Luo & Liansheng Wu & Wei Zhou, 2023. "Audit Effort and Stock Price Crash Risk," Abacus, Accounting Foundation, University of Sydney, vol. 59(1), pages 230-257, March.
    8. Walter Pohl & Karl Schmedders & Ole Wilms, 2018. "Higher Order Effects in Asset Pricing Models with Long‐Run Risks," Journal of Finance, American Finance Association, vol. 73(3), pages 1061-1111, June.
    9. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    10. Shi, Jinyan & Yu, Conghui & Liu, Xiangkun & Li, Yanxi, 2020. "Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics," Research in International Business and Finance, Elsevier, vol. 54(C).
    11. Christian Gakuba & Dr. Thomas K Tarus, 2022. "Effect of the Payment Process on the Performance of Construction Companies in Rwanda: Case of Rwanda Biomedical Center and Ministry of Health," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 6(11), pages 769-780, November.
    12. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    13. Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
    14. Marcelo Ochoa, 2013. "Volatility, labor heterogeneity and asset prices," Finance and Economics Discussion Series 2013-71, Board of Governors of the Federal Reserve System (U.S.).
    15. Yun, Jaeho, 2020. "A re-examination of the predictability of stock returns and cash flows via the decomposition of VIX," Economics Letters, Elsevier, vol. 186(C).
    16. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    17. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2020. "A mixed frequency approach for stock returns and valuation ratios," Economics Letters, Elsevier, vol. 187(C).
    18. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    19. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," Working Papers hal-04141871, HAL.

  9. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Belloni, Alexandre & Chen, Mingli & Chernozhukov, Victor, 2016. "Quantile Graphical Models : Prediction and Conditional Independence with Applications to Financial Risk Management," Economic Research Papers 269321, University of Warwick - Department of Economics.
    2. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," NBER Working Papers 19469, National Bureau of Economic Research, Inc.
    3. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," PIER Working Paper Archive 15-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Jul 2015.
    6. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    7. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    8. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    9. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    10. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    11. Alexandre Belloni & Mingli Chen & Victor Chernozhukov, 2016. "Quantile Graphical Models: Prediction and Conditional Independence with Applications to Systemic Risk," Papers 1607.00286, arXiv.org, revised Oct 2019.
    12. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    13. Christoffersen, Peter & Lunde, Asger & Olesen, Kasper V., 2019. "Factor Structure in Commodity Futures Return and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 1083-1115, June.
    14. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    15. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    16. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    17. Hoga, Yannick, 2021. "The uncertainty in extreme risk forecasts from covariate-augmented volatility models," International Journal of Forecasting, Elsevier, vol. 37(2), pages 675-686.
    18. Tim Bollerslev & Viktor Todorov & Lai Xu, 2014. "Tail Risk Premia and Return Predictability," CREATES Research Papers 2014-49, Department of Economics and Business Economics, Aarhus University.
    19. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    20. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    21. Nurulhasanah Abdul Rahman & Rafisah Mat Radzi, 2015. "Determinants of Effective Financial Risk Management in Small Business: A Theoretical Framework," Information Management and Business Review, AMH International, vol. 7(2), pages 87-92.
    22. Bent Jesper Christensen & Rasmus Tangsgaard Varneskov, 2021. "Dynamic Global Currency Hedging [Arbitrage in the Foreign Exchange Market: Turning on the Microscope]," Journal of Financial Econometrics, Oxford University Press, vol. 19(1), pages 97-127.
    23. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    24. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    25. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    26. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    27. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
    28. Hsuan‐Ling Chang & Yen‐Cheng Chang & Hung‐Wen Cheng & Po‐Hsiang Peng & Kevin Tseng, 2019. "Jump variance risk: Evidence from option valuation and stock returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 890-915, July.
    29. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.
    30. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    31. Dias, Alexandra, 2013. "Market capitalization and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5248-5260.
    32. Liu, Zhenya & Lu, Shanglin & Li, Bo & Wang, Shixuan, 2023. "Time series momentum and reversal: Intraday information from realized semivariance," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 54-77.
    33. Francis X. Diebold, 2020. ""Big Data" and its Origins," Papers 2008.05835, arXiv.org, revised Jan 2021.
    34. Han-Ching Huang & Yong-Chern Su & Jen-Tien Tsui, 2015. "Asymmetric GARCH Value-at-Risk over MSCI in Financial Crisis," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 390-398.
    35. Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
    36. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    37. BALTES Nicolae & DRAGOE Alexandra-Gabriela-Maria, 2017. "Estimating The Return Of The Financial Titles Of The Companies From The Manufacturing Industry, Listed On The Bucharest Stock Exchange," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(3), pages 19-28, August.
    38. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
    39. Richard Friberg & Mark Sanctuary, 2020. "Exchange rate risk and the skill composition of labor," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(2), pages 287-312, May.
    40. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    41. Diebold, Francis X. & Yılmaz, Kamil, 2023. "Reprint of: On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 234(S), pages 70-90.
    42. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    43. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    44. Hammadi Zouari, 2022. "On the Effectiveness of Stock Index Futures for Tail Risk Protection," International Journal of Economics and Financial Issues, Econjournals, vol. 12(3), pages 38-52, May.

  10. Tim Bollerslev & Daniela Osterrieder & Natalia Sizova & George Tauchen, 2011. "Risk and Return: Long-Run Relationships, Fractional Cointegration, and Return Predictability," CREATES Research Papers 2011-51, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.

  11. Tim Bollerslev & James Marrone & Lai Xu & Hao Zhou, 2011. "Stock return predictability and variance risk premia: statistical inference and international evidence," Finance and Economics Discussion Series 2011-52, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    2. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    3. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    4. Daniel O. Beltran & Deepa Dhume Datta & Thiago Revil T. Ferreira & Matteo Iacoviello & Mohammad Jahan-Parvar & Canlin Li & Juan M. Londono & Marius del Giudice Rodriguez & John H. Rogers & Bo Sun, 2017. "Taxonomy of Global Risk, Uncertainty, and Volatility Measures," International Finance Discussion Papers 1216, Board of Governors of the Federal Reserve System (U.S.).
    5. López, Raquel & Esparcia, Carlos, 2021. "Analysis of the performance of volatility-based trading strategies on scheduled news announcement days: An international equity market perspective," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 32-54.
    6. Li, Xiyang & Chen, Xiaoyue & Li, Bin & Singh, Tarlok & Shi, Kan, 2022. "Predictability of stock market returns: New evidence from developed and developing countries," Global Finance Journal, Elsevier, vol. 54(C).
    7. José Renato Haas Ornelas & Roberto Baltieri Mauad, 2019. "Implied Volatility Term Structure and Exchange Rate Predictability," Working Papers Series 492, Central Bank of Brazil, Research Department.
    8. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.
    9. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    10. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    11. Yi-Chieh Wen & Bin Li, 2020. "Lagged country returns and international stock return predictability during business cycle recession periods," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5005-5019, October.
    12. Dräger, Lena & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The Long Memory of Equity Volatility and the Macroeconomy: International Evidence," Hannover Economic Papers (HEP) dp-667, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    14. Ai, Hengjie & Han, Leyla Jianyu & Pan, Xuhui Nick & Xu, Lai, 2022. "The cross section of the monetary policy announcement premium," Journal of Financial Economics, Elsevier, vol. 143(1), pages 247-276.
    15. Ruan, Xinfeng & Zhang, Jin E., 2021. "The economics of the financial market for volatility trading," Journal of Financial Markets, Elsevier, vol. 52(C).
    16. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    17. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    18. Srivastava, Sasha & Lin, Hai & Premachandra, Inguruwatte M. & Roberts, Helen, 2016. "Global risk spillover and the predictability of sovereign CDS spread: International evidence," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 371-390.
    19. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "The Risk Premium of Gold," Hannover Economic Papers (HEP) dp-616, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    20. Zhenzhen Fan & Juan M. Londono & Xiao Xiao, 2019. "US Equity Tail Risk and Currency Risk Premia," International Finance Discussion Papers 1253, Board of Governors of the Federal Reserve System (U.S.).
    21. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    22. Markellos, Raphael N. & Psychoyios, Dimitris, 2018. "Interest rate volatility and risk management: Evidence from CBOE Treasury options," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 190-202.
    23. Haas Ornelas, José Renato, 2019. "Expected currency returns and volatility risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 206-234.
    24. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2017. "The Long Memory of Equity Volatility: International Evidence," Hannover Economic Papers (HEP) dp-614, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    25. Licheng Sun & Liang Meng & Mohammad Najand, 2017. "The Role of U.S. Market on International Risk-Return Tradeoff Relations," The Financial Review, Eastern Finance Association, vol. 52(3), pages 499-526, August.
    26. Konstantinidi, Eirini & Skiadopoulos, George, 2016. "How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 62-75.
    27. Mirco Rubin & Dario Ruzzi, 2020. "Equity tail risk in the treasury bond market," Temi di discussione (Economic working papers) 1311, Bank of Italy, Economic Research and International Relations Area.
    28. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
    29. Zhang, Yaojie & Zeng, Qing & Ma, Feng & Shi, Benshan, 2019. "Forecasting stock returns: Do less powerful predictors help?," Economic Modelling, Elsevier, vol. 78(C), pages 32-39.
    30. Londono, Juan M. & Zhou, Hao, 2017. "Variance risk premiums and the forward premium puzzle," Journal of Financial Economics, Elsevier, vol. 124(2), pages 415-440.
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    34. Juan M. Londono, 2011. "The variance risk premium around the world," International Finance Discussion Papers 1035, Board of Governors of the Federal Reserve System (U.S.).
    35. Aloosh, Arash, 2014. "Global Variance Risk Premium and Forex Return Predictability," MPRA Paper 59931, University Library of Munich, Germany.
    36. Yin, Libo & Lu, Man, 2022. "Oil uncertainty and firms' risk-taking," Energy Economics, Elsevier, vol. 108(C).
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    40. Tim Bollerslev & Viktor Todorov & Lai Xu, 2014. "Tail Risk Premia and Return Predictability," CREATES Research Papers 2014-49, Department of Economics and Business Economics, Aarhus University.
    41. Peter Christoffersen & Mathieu Fournier & Kris Jacobs & Mehdi Karoui, 2015. "Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk," CREATES Research Papers 2015-54, Department of Economics and Business Economics, Aarhus University.
    42. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    43. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.
    44. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2021. "Cross-stock market spillovers through variance risk premiums and equity flows," Journal of International Money and Finance, Elsevier, vol. 119(C).
    45. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Narayan, Seema, 2018. "Technology-investing countries and stock return predictability," Emerging Markets Review, Elsevier, vol. 36(C), pages 159-179.
    46. Juan M. Londono & Nancy R. Xu, 2019. "Variance Risk Premium Components and International Stock Return Predictability," International Finance Discussion Papers 1247, Board of Governors of the Federal Reserve System (U.S.).
    47. Zihao Zhang & Stefan Zohren & Stephen Roberts, 2018. "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books," Papers 1808.03668, arXiv.org, revised Jan 2020.
    48. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
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    1. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
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    3. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
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    5. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    6. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    7. Dungey, Mardi & Erdemlioglu, Deniz & Matei, Marius & Yang, Xiye, 2018. "Testing for mutually exciting jumps and financial flights in high frequency data," Journal of Econometrics, Elsevier, vol. 202(1), pages 18-44.
    8. Michael Ungeheuer & Martin Weber, 2021. "The Perception of Dependence, Investment Decisions, and Stock Prices," Journal of Finance, American Finance Association, vol. 76(2), pages 797-844, April.
    9. Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
    10. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch & Seong-Min Yoon, 2020. "OPEC News and Jumps in the Oil Market," Working Papers 202053, University of Pretoria, Department of Economics.
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    22. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    23. Xu, Weijun & Liu, Guifang & Li, Hongyi, 2016. "A novel jump diffusion model based on SGT distribution and its applications," Economic Modelling, Elsevier, vol. 59(C), pages 74-92.
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    30. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
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    33. Ahdi Noomen Ajmi & Roula Inglesi-Lotz, 2021. "Revisiting the Kuznets Curve Hypothesis for Tunisia: Carbon Dioxide vs. Ecological Footprint," Working Papers 202171, University of Pretoria, Department of Economics.
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    43. Van Cauwenberge, Annelies & Vancauteren, Mark & Braekers, Roel & Vandemaele, Sigrid, 2019. "International trade, foreign direct investments, and firms’ systemic risk : Evidence from the Netherlands," Economic Modelling, Elsevier, vol. 81(C), pages 361-386.
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    47. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2019. "Does Index Arbitrage Distort the Market Reaction to Shocks?," CERGE-EI Working Papers wp651, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
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    1. Barro, Robert J. & Liao, Gordon Y., 2021. "Rare disaster probability and options pricing," Journal of Financial Economics, Elsevier, vol. 139(3), pages 750-769.
    2. Deniz Erdemlioglu & Nikola Gradojevic, 2020. "Heterogeneous investment horizons, risk regimes, and realized jumps," Post-Print hal-02995997, HAL.
    3. Rhee, S. Ghon & Wu, Feng (Harry), 2020. "Conditional extreme risk, black swan hedging, and asset prices," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 412-435.
    4. Blanke, D. & Bosq, D., 2016. "Detecting and estimating intensity of jumps for discretely observed ARMAD(1,1) processes," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 119-137.
    5. Hans DEWACHTER & Deniz ERDEMLIOGLU & Jean-Yves GNABO & Christelle LECOURT, 2013. "The intra-day impact of communication on euro-dollar volatility and jumps," Working Papers of Department of Economics, Leuven ces13.04, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    6. Guay, François & Schwenkler, Gustavo, 2021. "Efficient estimation and filtering for multivariate jump–diffusions," Journal of Econometrics, Elsevier, vol. 223(1), pages 251-275.
    7. Aragon, George O. & Kim, Min S., 2023. "Fire sale risk and expected stock returns," Journal of Financial Economics, Elsevier, vol. 149(3), pages 578-609.
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    250. Yang Lu & Michael Siemer, 2013. "Learning, Rare Disasters, and Asset Prices," Finance and Economics Discussion Series 2013-85, Board of Governors of the Federal Reserve System (U.S.).
    251. Du, Du, 2013. "General equilibrium pricing of currency and currency options," Journal of Financial Economics, Elsevier, vol. 110(3), pages 730-751.
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    253. Kent Daniel & Ravi Jagannathan & Soohun Kim, 2012. "Tail Risk in Momentum Strategy Returns," NBER Working Papers 18169, National Bureau of Economic Research, Inc.
    254. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    255. Chollete, Loran & Ismailescu, Iuliana & Lu, Ching-Chih, 2014. "Dependence between Extreme Events in the Real and Financial Sectors," UiS Working Papers in Economics and Finance 2014/12, University of Stavanger.
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  15. Tim Bollerslev & Natalia Sizova & George Tauchen, 2009. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," CREATES Research Papers 2009-05, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kanniainen, Juho & Piché, Robert, 2013. "Stock price dynamics and option valuations under volatility feedback effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 722-740.
    2. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    3. Asai, M. & McAleer, M.J. & Medeiros, M.C., 2010. "Asymmetry and Long Memory in Volatility Modelling," Econometric Institute Research Papers EI 2010-60, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Stanislav Khrapov, 2011. "Pricing Central Tendency in Volatility," Working Papers w0168, New Economic School (NES).
    5. Manabu Asai & Michael McAleer, 2013. "A Fractionally Integrated Wishart Stochastic Volatility Model," Tinbergen Institute Discussion Papers 13-025/III, Tinbergen Institute.
    6. Ilze Kalnina & Dacheng Xiu, 2017. "Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 384-396, January.
    7. Jovanović, Mario, 2011. "Does Monetary Policy Affect Stock Market Uncertainty? – Empirical Evidence from the United States," Ruhr Economic Papers 240, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Christian Schlag & Michael Semenischev & Julian Thimme, 2021. "Predictability and the Cross-Section of Expected Returns: A Challenge for Asset Pricing Models," Management Science, INFORMS, vol. 67(12), pages 7932-7950, December.
    9. Manabu Asai & Michael McAleer, 2014. "Forecasting Co-Volatilities via Factor Models with Asymmetry and Long Memory in Realized Covariance," Working Papers in Economics 14/10, University of Canterbury, Department of Economics and Finance.
    10. Flavia Barsotti, 2012. "Optimal Capital Structure with Endogenous Default and Volatility Risk," Working Papers - Mathematical Economics 2012-02, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    11. Aït-Sahalia, Yacine & Fan, Jianqing & Li, Yingying, 2013. "The leverage effect puzzle: Disentangling sources of bias at high frequency," Journal of Financial Economics, Elsevier, vol. 109(1), pages 224-249.
    12. Izhakian, Yehuda, 2020. "A theoretical foundation of ambiguity measurement," Journal of Economic Theory, Elsevier, vol. 187(C).
    13. Senarathne Chamil W. & Šoja Tijana, 2019. "Heteroskedasticity in Excess Bitcoin Return Data: Google Trend vs. Garch Effects," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(3), pages 35-45, September.
    14. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 633-661, June.
    15. Bekaert, Geert & Engstrom, Eric, 2010. "Asset Return Dynamics Under Bad Environment-Good Environment Fundamentals," CEPR Discussion Papers 8150, C.E.P.R. Discussion Papers.
    16. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    17. Tim Bollerslev & Daniela Osterrieder & Natalia Sizova & George Tauchen, 2011. "Risk and Return: Long-Run Relationships, Fractional Cointegration, and Return Predictability," CREATES Research Papers 2011-51, Department of Economics and Business Economics, Aarhus University.
    18. Schlag, Christian & Semenischev, Michael & Thimme, Julian, 2020. "Predictability and the cross-section of expected returns: A challenge for asset pricing models," SAFE Working Paper Series 289, Leibniz Institute for Financial Research SAFE.
    19. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    20. Stelios Arvanitis & Tassos Magdalinos, 2018. "Mildly Explosive Autoregression Under Stationary Conditional Heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 892-908, November.
    21. Eraker, Bjørn & Wang, Jiakou, 2015. "A non-linear dynamic model of the variance risk premium," Journal of Econometrics, Elsevier, vol. 187(2), pages 547-556.
    22. Jianjun Miao & Bin Wei & Hao Zhou, 2018. "Ambiguity Aversion and Variance Premium," FRB Atlanta Working Paper 2018-14, Federal Reserve Bank of Atlanta.

  16. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Mauro Bernardi & Leopoldo Catania, 2014. "The Model Confidence Set package for R," Papers 1410.8504, arXiv.org.
    2. Sayantan Bandhu Majumder & Ranjanendra Narayan Nag, 2018. "Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India," Global Business Review, International Management Institute, vol. 19(1), pages 227-240, February.
    3. Javier Sánchez García & Salvador Cruz Rambaud, 2022. "A GARCH approach to model short‐term interest rates: Evidence from Spanish economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1621-1632, April.
    4. Allison Roehling, 2021. "Implications of exchange rate volatility for trade: Volatility measurement matters," Review of International Economics, Wiley Blackwell, vol. 29(5), pages 1486-1523, November.
    5. Václav Klepáč & David Hampel, 2015. "Assessing Efficiency of D-Vine Copula ARMA-GARCH Method in Value at Risk Forecasting: Evidence from PSE Listed Companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(4), pages 1287-1295.
    6. Daniel Levin & Terry Lyons & Hao Ni, 2013. "Learning from the past, predicting the statistics for the future, learning an evolving system," Papers 1309.0260, arXiv.org, revised Mar 2016.
    7. Kononovicius, A. & Ruseckas, J., 2015. "Nonlinear GARCH model and 1/f noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 74-81.
    8. Thilo A. Schmitt & Rudi Schafer & Holger Dette & Thomas Guhr, 2015. "Quantile Correlations: Uncovering temporal dependencies in financial time series," Papers 1507.04990, arXiv.org.
    9. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Marcel Bräutigam & Marie Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," Working Papers hal-02176276, HAL.
    11. Tsatsura, Oleg, 2010. "A Smooth Transition GARCH-M Model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 17(1), pages 45-61.
    12. Bertram, Philip & Sibbertsen, Philipp & Stahl, Gerhard, 2011. "About the Impact of Model Risk on Capital Reserves: A Quantitative Analysis," Hannover Economic Papers (HEP) dp-469, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
    14. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2020. "Uncertainty Shocks and Business Cycle Research," NBER Working Papers 26768, National Bureau of Economic Research, Inc.
    15. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
    16. Trong‐Nghia Nguyen & Minh‐Ngoc Tran & Robert Kohn, 2022. "Recurrent conditional heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1031-1054, August.
    17. Jamal Bouoiyour & Refk Selmi, 2016. "Bitcoin: a beginning of a new phase?," Economics Bulletin, AccessEcon, vol. 36(3), pages 1430-1440.
    18. Bouoiyour, Jamal & Miftah, Amal & Selmi, Refk, 2014. "Do Financial Flows raise or reduce Economic growth Volatility? Some Lessons from Moroccan case," MPRA Paper 57258, University Library of Munich, Germany.
    19. Borusyak, K., 2011. "Nonlinear Dynamics of the Russian Stock Market in Problems of Risk Management," Journal of the New Economic Association, New Economic Association, issue 11, pages 85-105.
    20. Marcel, Bräutigam & Marie, Kratz, 2019. "Bivariate FCLT for the Sample Quantile and Measures of Dispersion for Augmented GARCH(p, q) processes," ESSEC Working Papers WP1909, ESSEC Research Center, ESSEC Business School.
    21. Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
    22. Willy Alanya & Gabriel Rodríguez, 2014. "Stochastic Volatility in Peruvian Stock Market and Exchange Rate Returns: a Bayesian Approximation," Documentos de Trabajo / Working Papers 2014-392, Departamento de Economía - Pontificia Universidad Católica del Perú.
    23. Tafakori, Laleh & Pourkhanali, Armin & Fard, Farzad Alavi, 2018. "Forecasting spikes in electricity return innovations," Energy, Elsevier, vol. 150(C), pages 508-526.
    24. Thilo A. Schmitt & Rudi Schäfer & Holger Dette & Thomas Guhr, 2015. "Quantile Correlations: Uncovering Temporal Dependencies In Financial Time Series," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-16, November.
    25. Carl H. Korkpoe & Peterson Owusu Junior, 2018. "Behaviour of Johannesburg Stock Exchange All Share Index Returns - An Asymmetric GARCH and News Impact Effects Approach," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 68(1), pages 26-42, January-M.
    26. Kraicova, Lucie & Barunik, Jozef, 2015. "Estimation of long memory in volatility using wavelets," FinMaP-Working Papers 33, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    27. Constantin ANGHELACHE & Madalina Gabriela ANGHEL, 2015. "Theoretical aspects concerning the use of the statistical-econometric instruments the analysis of the financial assets," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 63(9), pages 44-48, September.
    28. Aleksejus Kononovicius & Julius Ruseckas, 2014. "Nonlinear GARCH model and 1/f noise," Papers 1412.6244, arXiv.org, revised Feb 2015.
    29. Silvo Dajcman, 2013. "Dependence between Croatian and European stock markets – A copula GARCH approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 31(2), pages 209-232.
    30. Francq, Christian & Thieu, Le Quyen, 2015. "Qml inference for volatility models with covariates," MPRA Paper 63198, University Library of Munich, Germany.
    31. González-Hermosillo, Brenda & Johnson, Christian, 2017. "Transmission of financial stress in Europe: The pivotal role of Italy and Spain, but not Greece," Journal of Economics and Business, Elsevier, vol. 90(C), pages 49-64.
    32. Marín Díazaraque, Juan Miguel & Rodríguez Bernal, M. T. & Romero, Eva, 2013. "Data cloning estimation of GARCH and COGARCH models," DES - Working Papers. Statistics and Econometrics. WS ws132723, Universidad Carlos III de Madrid. Departamento de Estadística.
    33. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    34. Florent S'egonne, 2015. "Variance Dynamics - An empirical journey," Papers 1507.00846, arXiv.org.
    35. Bouoiyour, Jamal & Selmi, Refk, 2015. "Bitcoin Price: Is it really that New Round of Volatility can be on way?," MPRA Paper 65580, University Library of Munich, Germany.
    36. Abdelouahab Bibi, 2021. "Asymptotic properties of QMLE for seasonal threshold GARCH model with periodic coefficients," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 477-514, June.
    37. Jungsik Noh & Sangyeol Lee, 2016. "Quantile Regression for Location-Scale Time Series Models with Conditional Heteroscedasticity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 700-720, September.
    38. Fethi Ayachi & Jamal Bouoiyour & Refk Selmi, 2012. "Another look at the interaction between oil price uncertainty and exchange rate volatility: The case of small open economies," Post-Print hal-01879693, HAL.
    39. Aleksejus Kononovicius & Bronislovas Kaulakys, 2022. "$1/f$ noise from the sequence of nonoverlapping rectangular pulses," Papers 2210.11792, arXiv.org, revised Mar 2023.
    40. Marko Voutilainen & Pauliina Ilmonen & Soledad Torres & Ciprian Tudor & Lauri Viitasaari, 2021. "On the ARCH model with stationary liquidity," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(2), pages 195-224, February.
    41. Chen Liu & Chao Wang & Minh-Ngoc Tran & Robert Kohn, 2023. "Deep Learning Enhanced Realized GARCH," Papers 2302.08002, arXiv.org, revised Oct 2023.
    42. Lönnbark, Carl, 2017. "Long vs. short term asymmetry in volatility and the term structure of risk," Finance Research Letters, Elsevier, vol. 23(C), pages 202-209.
    43. Randal Douc & François Roueff & Tepmony Sim, 2021. "Necessary and sufficient conditions for the identifiability of observation‐driven models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 140-160, March.
    44. Chris Motengwe & Angel Pardo, 2015. "A Study of Seasonality on the Safex Wheat Market," Agrekon, Taylor & Francis Journals, vol. 54(4), pages 45-72, November.
    45. T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
    46. Fakhrul Hasan & Umar Nawaz Kayani & Tonmoy Choudhury, 2023. "Behavioral Risk Preferences and Dividend Changes: Exploring the Linkages with Prospect Theory Through Empirical Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 517-535, December.
    47. Tomasz Skoczylas, 2015. "Log-volatility enhanced GARCH models for single asset returns," Bank i Kredyt, Narodowy Bank Polski, vol. 46(5), pages 411-432.
    48. Milan Fičura, 2017. "Forecasting Stock Market Realized Variance with Echo State Neural Networks," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2017(3), pages 145-155.
    49. Fredy Gamboa-Estrada & José Vicente Romero, 2022. "Modelling CDS Volatility at Different Tenures: An Application for Latin-American Countries," Borradores de Economia 1199, Banco de la Republica de Colombia.
    50. Waldemar Tarczyński & Sebastian Majewski & Małgorzata Tarczyńska-Łuniewska & Agnieszka Majewska & Grzegorz Mentel, 2021. "The Impact of Weather Factors on Quotations of Energy Sector Companies on Warsaw Stock Exchange," Energies, MDPI, vol. 14(6), pages 1-14, March.
    51. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    52. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
    53. Chalabi, Yohan / Y. & Wuertz, Diethelm, 2010. "Weighted trimmed likelihood estimator for GARCH models," MPRA Paper 26536, University Library of Munich, Germany.
    54. Rytis Kazakevicius & Aleksejus Kononovicius & Bronislovas Kaulakys & Vygintas Gontis, 2021. "Understanding the nature of the long-range memory phenomenon in socioeconomic systems," Papers 2108.02506, arXiv.org, revised Aug 2021.
    55. Stavros Stavroyiannis, 2016. "Value-at-Risk and backtesting with the APARCH model and the standardized Pearson type IV distribution," Papers 1602.05749, arXiv.org.
    56. Zapodeanu Daniela & Cociuba Mihai & Petria Nicolae, 2012. "The Role Of Value At Risk In The Management Of Asset And Liabilities," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 635-640, December.
    57. Linn Arnell & Emma Engström & Gazi Salah Uddin & Md. Bokhtiar Hasan & Sang Hoon Kang, 2023. "Volatility spillovers, structural breaks and uncertainty in technology sector markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-31, December.
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  17. Tim Bollerslev & Morten Ø. Nielsen & Per Houmann Frederiksen & Torben G. Andersen, 2008. "Continuous-time Models, Realized Volatilities, And Testable Distributional Implications For Daily Stock Returns," Working Paper 1173, Economics Department, Queen's University.

    Cited by:

    1. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    2. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02505861, HAL.
    3. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    4. Thierry Ane & Carole Metais, 2010. "Jump Distribution Characteristics: Evidence from European Stock Markets," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(1), pages 1-22, April.
    5. Fengler, Matthias R. & Mammen, Enno & Vogt, Michael, 2013. "Additive modeling of realized variance: tests for parametric specifications and structural breaks," Economics Working Paper Series 1332, University of St. Gallen, School of Economics and Political Science.
    6. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    7. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    8. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    9. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    10. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    11. Johannes Stübinger & Lucas Schneider, 2019. "Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    12. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
    13. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    14. Mardi Dungey & Lyudmyla Hvozdyk, 2010. "Cojumping: Evidence from the US Treasury Bond and Futures Markets," NCER Working Paper Series 56, National Centre for Econometric Research, revised 20 Jul 2010.
    15. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    16. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    17. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    22. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
    23. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    24. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
    25. Dungey, Mardi & Hvozdyk, Lyudmyla, 2010. "Cojumping: Evidence from the US Treasury Bond and Future Markets (Discussion Paper 2010-06)," Working Papers 10450, University of Tasmania, Tasmanian School of Business and Economics, revised 14 Jul 2010.
    26. Dion Bongaerts & Richard Roll & Dominik Rösch & Mathijs van Dijk & Darya Yuferova, 2022. "How Do Shocks Arise and Spread Across Stock Markets? A Microstructure Perspective," Management Science, INFORMS, vol. 68(4), pages 3071-3089, April.
    27. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    28. Chan, Kam Fong & Powell, John G. & Treepongkaruna, Sirimon, 2014. "Currency jumps and crises: Do developed and emerging market currencies jump together?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 132-157.
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    104. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    105. Song, Zhaogang, 2011. "A martingale approach for testing diffusion models based on infinitesimal operator," Journal of Econometrics, Elsevier, vol. 162(2), pages 189-212, June.
    106. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.
    107. Jawadi, Fredj & Louhichi, Waël & Idi Cheffou, Abdoulkarim, 2015. "Testing and modeling jump contagion across international stock markets: A nonparametric intraday approach," Journal of Financial Markets, Elsevier, vol. 26(C), pages 64-84.
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    113. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
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    116. Lee, Suzanne S., 2023. "The role of idiosyncratic jumps in stock markets," Journal of Financial Markets, Elsevier, vol. 64(C).
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    121. Lee, Suzanne S. & Wang, Minho, 2020. "Tales of tails: Jumps in currency markets," Journal of Financial Markets, Elsevier, vol. 48(C).
    122. Zeng, Qing & Lu, Xinjie & Li, Tao & Wu, Lan, 2022. "Jumps and stock market variance during the COVID-19 pandemic: Evidence from international stock markets," Finance Research Letters, Elsevier, vol. 48(C).
    123. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2013. "Modelling systemic price cojumps with Hawkes factor models," Papers 1301.6141, arXiv.org, revised Mar 2013.
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    125. Xu, Fang & Bouri, Elie & Cepni, Oguzhan, 2022. "Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps," Finance Research Letters, Elsevier, vol. 50(C).
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    130. Dumitru, Ana-Maria & Urga, Giovanni, 2016. "Jumps and Information Asymmetry in the US Treasury Market," EconStor Preprints 130148, ZBW - Leibniz Information Centre for Economics.
    131. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
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  21. Viktor Todorov & Tim Bollerslev, 2007. "Jumps and Betas: A New Framework for Disentangling and Estimating Systematic Risks," CREATES Research Papers 2007-15, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    2. Mardi Dungey & Lyudmyla Hvozdyk, 2010. "Cojumping: Evidence from the US Treasury Bond and Futures Markets," NCER Working Paper Series 56, National Centre for Econometric Research, revised 20 Jul 2010.
    3. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    4. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    5. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    6. Dovonon, Prosper & Taamouti, Abderrahim & Williams, Julian, 2022. "Testing the eigenvalue structure of spot and integrated covariance," Journal of Econometrics, Elsevier, vol. 229(2), pages 363-395.
    7. Aït-Sahalia, Yacine & Xiu, Dacheng, 2017. "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, vol. 201(2), pages 384-399.
    8. Eric Jacquier & Cedric Okou, 2013. "Disentangling Continuous Volatility from Jumps in Long-Run Risk-Return Relationships," CIRANO Working Papers 2013s-14, CIRANO.
    9. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
    10. Shabir A A Saleem & Peter N Smith & Abdullah Yalaman, 2021. "Analysis of systematic risk around firm-specific news in an emerging market using high frequency data," CAMA Working Papers 2021-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, Department of Economics and Business Economics, Aarhus University.
    12. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    13. Bannouh, K. & Martens, M.P.E. & Oomen, R.C.A. & van Dijk, D.J.C., 2012. "Realized mixed-frequency factor models for vast dimensional covariance estimation," ERIM Report Series Research in Management ERS-2012-017-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Lee, Suzanne S. & Wang, Minho, 2019. "The impact of jumps on carry trade returns," Journal of Financial Economics, Elsevier, vol. 131(2), pages 433-455.
    15. Dinesh Gajurel & Mardi Dungey & Wenying Yao & Nagaratnam Jeyasreedharan, 2020. "Jump Risk in the US Financial Sector," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 331-349, September.
    16. Ilze KALNINA, 2015. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Cahiers de recherche 13-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    17. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    18. Van Ness, Bonnie & Van Ness, Robert & Yildiz, Serhat, 2021. "Private information in trades, R2, and large stock price movements," Journal of Banking & Finance, Elsevier, vol. 131(C).
    19. Dovonon, Prosper & Goncalves, Silvia & Meddahi, Nour, 2010. "Bootstrapping realized multivariate volatility measures," MPRA Paper 40123, University Library of Munich, Germany.
    20. Liu, Wenwen & Zhang, Chang & Qiao, Gaoxiu & Xu, Lei, 2022. "Impact of network investor sentiment and news arrival on jumps," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    21. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    22. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
    23. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
    24. Chen, Xi & Wang, Junbo & Wu, Chunchi, 2022. "Jump and volatility risk in the cross-section of corporate bond returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    25. Alexeev, Vitali & Dungey, Mardi & Yao, Wenying, 2017. "Time-varying continuous and jump betas: The role of firm characteristics and periods of stress," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 1-19.
    26. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    27. Markus Reiß & Viktor Todorov & George Tauchen, 2014. "Nonparametric Test for a Constant Beta over a Fixed Time Interval," SFB 649 Discussion Papers SFB649DP2014-022, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    28. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    29. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    30. Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022. "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, vol. 228(1), pages 156-175.
    31. Li, Jia & Todorov, Viktor & Tauchen, George & Chen, Rui, 2017. "Mixed-scale jump regressions with bootstrap inference," Journal of Econometrics, Elsevier, vol. 201(2), pages 417-432.
    32. Yuta Koike, 2014. "An estimator for the cumulative co-volatility of asynchronously observed semimartingales with jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 460-481, June.
    33. Patton, Andrew J. & Verardo, Michela, 2009. "Does beta move with news? Systematic risk and firm-specific information flows," LSE Research Online Documents on Economics 24421, London School of Economics and Political Science, LSE Library.
    34. Maarten R C van Oordt & Chen Zhou, 2019. "Estimating Systematic Risk under Extremely Adverse Market Conditions," Journal of Financial Econometrics, Oxford University Press, vol. 17(3), pages 432-461.
    35. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    36. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    37. Vitali Alexeev & Mardi Dungey, 2015. "Equity portfolio diversification with high frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1205-1215, July.
    38. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2013. "Conditional alphas and realized betas," Textos para discussão 341, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    39. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    40. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
    41. Gajurel, Dinesh & Chowdhury, Biplob, 2020. "Realized volatility, jump and beta: evidence from Canadian stock market," Working Papers 2020-11, University of Tasmania, Tasmanian School of Business and Economics.
    42. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    43. Wenying Yao & Mardi Dungey & Vitali Alexeev, 2020. "Modelling Financial Contagion Using High Frequency Data," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 314-330, September.
    44. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
    45. Zhou, Haigang & Zhu, John Qi, 2019. "Firm characteristics and jump dynamics in stock prices around earnings announcements," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    46. Li, Jia & Todorov, Viktor & Tauchen, George, 2017. "Adaptive estimation of continuous-time regression models using high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 36-47.
    47. Andrew Phin & Todd Prono & Jonathan J. Reeves & Konark Saxena, 2018. "Level Shifts in Beta, Spurious Abnormal Returns and the TARP Announcement," Finance and Economics Discussion Series 2018-081, Board of Governors of the Federal Reserve System (U.S.).
    48. Yao, Wenying & Tian, Jing, 2015. "The role of intra-day volatility pattern in jump detection: empirical evidence on how financial markets respond to macroeconomic news announcements," Working Papers 2015-05, University of Tasmania, Tasmanian School of Business and Economics.
    49. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    50. Leong, Minhao & Kwok, Simon, 2023. "The pricing of jump and diffusive risks in the cross-section of cryptocurrency returns," Journal of Empirical Finance, Elsevier, vol. 74(C).
    51. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.
    52. KALNINA, Ilze & TEWOU, Kokouvi, 2015. "Cross-sectional dependence in idiosyncratic volatility," Cahiers de recherche 2015-04, Universite de Montreal, Departement de sciences economiques.
    53. Lars Winkelmann & Markus Bibinger & Tobias Linzert, 2016. "ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 613-629, June.
    54. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    55. Djellout, Hacène & Guillin, Arnaud & Samoura, Yacouba, 2017. "Estimation of the realized (co-)volatility vector: Large deviations approach," Stochastic Processes and their Applications, Elsevier, vol. 127(9), pages 2926-2960.
    56. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2019. "Does Index Arbitrage Distort the Market Reaction to Shocks?," CERGE-EI Working Papers wp651, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    57. Youcong Chao & Xiaoqun Liu & Shijun Guo, 2017. "Sign realized jump risk and the cross-section of stock returns: Evidence from China's stock market," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    58. Vitali Alexeev & Mardi Dungey & Wenying Yao, 2016. "Continuous and Jump Betas: Implications for Portfolio Diversification," Econometrics, MDPI, vol. 4(2), pages 1-15, June.
    59. Liu, Zhi & Kong, Xin-Bing & Jing, Bing-Yi, 2018. "Estimating the integrated volatility using high-frequency data with zero durations," Journal of Econometrics, Elsevier, vol. 204(1), pages 18-32.
    60. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
    61. Phin, Andrew & Prono, Todd & Reeves, Jonathan J. & Saxena, Konark, 2022. "Shifts in beta and the TARP announcement," Finance Research Letters, Elsevier, vol. 47(PB).
    62. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam, 2019. "An empirical examination of the jump and diffusion aspects of asset pricing: Japanese evidence," Working Papers 2019-02, University of Tasmania, Tasmanian School of Business and Economics.
    63. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.

  22. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," JRFM, MDPI, vol. 7(2), pages 1-30, June.
    2. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    3. Tim Bollerslev & Viktor Todorov, 2010. "Tails, Fears and Risk Premia," Working Papers 10-33, Duke University, Department of Economics.
    4. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    5. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
    6. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    7. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Working Papers 201925, University of Pretoria, Department of Economics.
    8. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    9. Fan, Lina & Yang, Hao & Zhai, Jia & Zhang, Xiaotao, 2023. "Forecasting stock volatility during the stock market crash period: The role of Hawkes process," Finance Research Letters, Elsevier, vol. 55(PA).
    10. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    11. Yaxiong Zeng & Diego Klabjan, 2017. "Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling," Papers 1706.01833, arXiv.org, revised Jun 2018.
    12. Peter Christoffersen & Bruno Feunou & Yoontae Jeon, 2014. "Option Valuation with Observable Volatility and Jump Dynamics," CREATES Research Papers 2015-07, Department of Economics and Business Economics, Aarhus University.
    13. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    14. Matteo Bonato & Rangan Gupta & Chi Keung Marco Lau & Shixuan Wang, 2019. "Moments-Based Spillovers across Gold and Oil Markets," Working Papers 201966, University of Pretoria, Department of Economics.
    15. Manabu Asai & Michael McAleer, 2017. "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE 2017-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    16. Ilze Kalnina & Dacheng Xiu, 2017. "Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 384-396, January.
    17. Manabu Asai & Michael McAleer, 2017. "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 638-650, October.
    18. Zhou, Jian, 2016. "A high-frequency analysis of the interactions between REIT return and volatility," Economic Modelling, Elsevier, vol. 56(C), pages 102-108.
    19. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    20. Cem Cakmakli & Verda Ozturk, 2021. "Economic Value of Modeling the Joint Distribution of Returns and Volatility: Leverage Timing," Koç University-TUSIAD Economic Research Forum Working Papers 2110, Koc University-TUSIAD Economic Research Forum.
    21. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "High-Frequency Jump Tests: Which Test Should We Use?," Papers 1708.09520, arXiv.org, revised Jan 2020.
    22. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    23. Qu, Hui & Chen, Wei & Niu, Mengyi & Li, Xindan, 2016. "Forecasting realized volatility in electricity markets using logistic smooth transition heterogeneous autoregressive models," Energy Economics, Elsevier, vol. 54(C), pages 68-76.
    24. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    25. Wang, Yajing & Liang, Fang & Wang, Tianyi & Huang, Zhuo, 2020. "Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 87(C), pages 148-157.
    26. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    27. Bee, Marco & Dupuis, Debbie J. & Trapin, Luca, 2016. "Realizing the extremes: Estimation of tail-risk measures from a high-frequency perspective," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 86-99.
    28. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    29. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    30. Fulvio Corsi & Davide Pirino & Roberto Renò, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Post-Print hal-00741630, HAL.
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    1. Courtenay, Roger & Clare, Andrew, 2001. "What can we learn about monetary policy transparency from financial market data?," Discussion Paper Series 1: Economic Studies 2001,06, Deutsche Bundesbank.
    2. Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
    3. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    4. Olkhov, Victor, 2021. "Three Remarks On Asset Pricing," MPRA Paper 109238, University Library of Munich, Germany.
    5. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    6. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    7. Victor Olkhov, 2020. "Volatility Depend on Market Trades and Macro Theory," Papers 2008.07907, arXiv.org.
    8. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    9. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    10. Victoria Zinde-Walsh & Dongming Zhu, 2007. "Properties And Estimation Of Asymmetric Exponential Power Distribution," Departmental Working Papers 2007-11, McGill University, Department of Economics.
    11. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    12. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
    13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
    14. Eric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1999. "Stochastic Volatility: Univariate and Multivariate Extensions," CIRANO Working Papers 99s-26, CIRANO.
    15. Suhejla Hoiti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2005. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," DEA Working Papers 14, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    16. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    17. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    18. Victor Olkhov, 2020. "Price, Volatility and the Second-Order Economic Theory," Papers 2009.14278, arXiv.org, revised Apr 2021.
    19. Théoret, Raymond & Racicot, François-Éric, 2010. "Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio," MPRA Paper 35911, University Library of Munich, Germany.
    20. Luisa Bisaglia & Silvano Bordignon & Francesco Lisi, 2003. "k -Factor GARMA models for intraday volatility forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 10(4), pages 251-254.
    21. Francois-Éric Racicot & Raymond Théoret, 2005. "Quelques applications du filtre de Kalman en finance: estimation et prévision de la volatilité stochastique et du rapport cours-bénéfices," RePAd Working Paper Series UQO-DSA-wp0312005, Département des sciences administratives, UQO.
    22. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    23. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    24. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    25. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    26. Yan-Leung Cheung & Yin-Wong Cheung & Alan T.K. Wan, 2008. "A High-Low Model of Daily Stock Price Ranges," CESifo Working Paper Series 2387, CESifo.
    27. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    28. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    29. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    30. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    31. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    32. Andrew Clare & Roger Courtenay, 2001. "Assessing the impact of macroeconomic news announcements on securities prices under different monetary policy regimes," Bank of England working papers 125, Bank of England.
    33. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    34. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    35. SUCARRAT, Genaro, 2006. "The first stage in Hendry’s reduction theory revisited," LIDAM Discussion Papers CORE 2006082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    37. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, Department of Economics and Business Economics, Aarhus University.
    38. Bistra Radeva, 2019. "Stock price fluctuations and GARCH modelling of stock market indexes," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 3, pages 6-19.
    39. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    40. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
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    Cited by:

    1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
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    3. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    4. Erie Febrian & Aldrin Herwany, 2010. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Business, Management and Finance 201005, Department of Management and Business, Padjadjaran University, revised May 2010.
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    6. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
    7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
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    25. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    26. Othmar M. Lehner, 2013. "Crowdfunding social ventures: a model and research agenda," Venture Capital, Taylor & Francis Journals, vol. 15(4), pages 289-311, October.
    27. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    28. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    29. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    30. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    31. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    32. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    33. Bates, David S., 2012. "U.S. stock market crash risk, 1926–2010," Journal of Financial Economics, Elsevier, vol. 105(2), pages 229-259.
    34. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    35. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    36. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

  28. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).

    Cited by:

    1. Courtenay, Roger & Clare, Andrew, 2001. "What can we learn about monetary policy transparency from financial market data?," Discussion Paper Series 1: Economic Studies 2001,06, Deutsche Bundesbank.
    2. Anthony S. Tay & Peter F. Christoffersen & Francis X. Diebold & Roberto S. Mariano & Yiu Kuen Tse, 2006. "Direction-of-Change Forecasts Based on Conditional Variance, Skewness and Kurtosis Dynamics : International Evidence," Finance Working Papers 22481, East Asian Bureau of Economic Research.
    3. Olkhov, Victor, 2021. "Three Remarks On Asset Pricing," MPRA Paper 109238, University Library of Munich, Germany.
    4. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    5. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    6. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    7. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    8. Eric Jacquier & Nicholas G. Polson & Peter E. Rossi, 1999. "Stochastic Volatility: Univariate and Multivariate Extensions," CIRANO Working Papers 99s-26, CIRANO.
    9. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    10. Victor Olkhov, 2020. "Price, Volatility and the Second-Order Economic Theory," Papers 2009.14278, arXiv.org, revised Apr 2021.
    11. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    12. Luisa Bisaglia & Silvano Bordignon & Francesco Lisi, 2003. "k -Factor GARMA models for intraday volatility forecasting," Applied Economics Letters, Taylor & Francis Journals, vol. 10(4), pages 251-254.
    13. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
    14. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    15. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    16. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    17. Yan-Leung Cheung & Yin-Wong Cheung & Alan T.K. Wan, 2008. "A High-Low Model of Daily Stock Price Ranges," CESifo Working Paper Series 2387, CESifo.
    18. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    19. ZHU, Dongming & ZINDE-WALSH, Victoria, 2007. "Properties and Estimation of Asymmetric Exponential Power Distribution," Cahiers de recherche 13-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    20. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    22. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
    23. Milan Ficura & Jiri Witzany, 2016. "Estimating Stochastic Volatility and Jumps Using High-Frequency Data and Bayesian Methods," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 278-301, August.
    24. SUCARRAT, Genaro, 2006. "The first stage in Hendry’s reduction theory revisited," LIDAM Discussion Papers CORE 2006082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    26. Olkhov, Victor, 2020. "Volatility Depend on Market Trades and Macro Theory," MPRA Paper 102434, University Library of Munich, Germany.
    27. Ariño, Miguel A. & Canela, Miguel A., 2006. "Study of the dollar-euro exchange rate," IESE Research Papers D/620, IESE Business School, revised 30 Mar 2006.
    28. Tim Bollerslev & Morten Ø. Nielsen & Per Houmann Frederiksen & Torben G. Andersen, 2008. "Continuous-time Models, Realized Volatilities, And Testable Distributional Implications For Daily Stock Returns," Working Paper 1173, Economics Department, Queen's University.
    29. Abramov, Vyacheslav & Klebaner, Fima, 2006. "Forecasting and testing a non-constant volatility," MPRA Paper 207, University Library of Munich, Germany.
    30. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    31. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    32. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
    33. Suhejla Hoiti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2005. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," DEA Working Papers 14, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    34. Théoret, Raymond & Racicot, François-Éric, 2010. "Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio," MPRA Paper 35911, University Library of Munich, Germany.
    35. Francois-Éric Racicot & Raymond Théoret, 2005. "Quelques applications du filtre de Kalman en finance: estimation et prévision de la volatilité stochastique et du rapport cours-bénéfices," RePAd Working Paper Series UQO-DSA-wp0312005, Département des sciences administratives, UQO.
    36. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    37. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    38. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    39. Andrew Clare & Roger Courtenay, 2001. "Assessing the impact of macroeconomic news announcements on securities prices under different monetary policy regimes," Bank of England working papers 125, Bank of England.
    40. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Oct 2021.
    41. Bistra Radeva, 2019. "Stock price fluctuations and GARCH modelling of stock market indexes," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 3, pages 6-19.
    42. Sizova, Natalia, 2011. "Integrated variance forecasting: Model based vs. reduced form," Journal of Econometrics, Elsevier, vol. 162(2), pages 294-311, June.
    43. Juliusz Jabłecki & Ryszard Kokoszczyński & Paweł Sakowski & Robert Ślepaczuk & Piotr Wójcik, 2014. "Does historical volatility term structure contain valuable in-formation for predicting volatility index futures?," Working Papers 2014-18, Faculty of Economic Sciences, University of Warsaw.
    44. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
    45. Vyacheslav Abramov & Fima Klebaner, 2007. "Estimation and Prediction of a Non-Constant Volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(1), pages 1-23, March.
    46. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.

  29. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.

    Cited by:

    1. Jean-Paul Laurent & Hassan Omidi Firouzi, 2022. "Market Risk and Volatility Weighted Historical Simulation After Basel III," Working Papers hal-03679434, HAL.
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    3. Olkhov, Victor, 2022. "Introduction of the Market-Based Price Autocorrelation," MPRA Paper 112003, University Library of Munich, Germany.
    4. Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
    5. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," EconomiX Working Papers 2014-46, University of Paris Nanterre, EconomiX.
    6. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    7. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    8. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    9. Othmar M. Lehner, 2013. "Crowdfunding social ventures: a model and research agenda," Venture Capital, Taylor & Francis Journals, vol. 15(4), pages 289-311, October.
    10. Erie Febrian & Aldrin Herwany, 2010. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Business, Management and Finance 201005, Department of Management and Business, Padjadjaran University, revised May 2010.
    11. O’Brien, James & Szerszeń, Paweł J., 2017. "An evaluation of bank measures for market risk before, during and after the financial crisis," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 215-234.
    12. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    13. Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
    14. James M. O'Brien & Pawel J. Szerszen, 2014. "An Evaluation of Bank VaR Measures for Market Risk During and Before the Financial Crisis," Finance and Economics Discussion Series 2014-21, Board of Governors of the Federal Reserve System (U.S.).
    15. Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
    16. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    17. Erie Febrian & Aldrin Herwany, 2010. "Forecasting Stocks of Government Owned Companies (GOCS):Volatility Modeling," Working Papers in Business, Management and Finance 201002, Department of Management and Business, Padjadjaran University, revised Feb 2010.
    18. David S. Bates, 2009. "U.S. Stock Market Crash Risk, 1926-2006," NBER Working Papers 14913, National Bureau of Economic Research, Inc.
    19. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    20. Gaisser, Sandra & Memmel, Christoph & Schmidt, Rafael & Wehn, Carsten, 2009. "Time dynamic and hierarchical dependence modelling of an aggregated portfolio of trading books: a multivariate nonparametric approach," Discussion Paper Series 2: Banking and Financial Studies 2009,07, Deutsche Bundesbank.
    21. Markus Bibinger & Lars Winkelmann, 2014. "Common price and volatility jumps in noisy high-frequency data," SFB 649 Discussion Papers SFB649DP2014-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    22. Erie Febrian & Aldrin Herwany, 2009. "Volatility Model for Financial Market Risk Management : An Analysis on JSX Index Return Covariance Matrix," Working Papers in Economics and Development Studies (WoPEDS) 200907, Department of Economics, Padjadjaran University, revised Sep 2009.
    23. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    24. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    25. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
    26. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    27. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    28. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    29. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    30. Faheem Aslam & Paulo Ferreira & Khurrum Shahzad Mughal & Beenish Bashir, 2021. "Intraday Volatility Spillovers among European Financial Markets during COVID-19," IJFS, MDPI, vol. 9(1), pages 1-19, January.
    31. Bates, David S., 2012. "U.S. stock market crash risk, 1926–2010," Journal of Financial Economics, Elsevier, vol. 105(2), pages 229-259.
    32. Barbara Bedowska-Sojka, 2017. "Evaluating the Accuracy of Time-varying Beta. The Evidence from Poland," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 161-176.
    33. Krahnen, Jan-Pieter & Wilde, Christian, 2006. "Risk Transfer with CDOs and Systemic Risk in Banking," CEPR Discussion Papers 5618, C.E.P.R. Discussion Papers.
    34. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    35. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    36. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

  30. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin (Ginger) Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," NBER Working Papers 11134, National Bureau of Economic Research, Inc.

    Cited by:

    1. Hassan, Gazi & Hisham, Al refai, 2010. "Can Macroeconomic Factors Explain Equity Returns in the Long Run? The Case of Jordan," MPRA Paper 22713, University Library of Munich, Germany.
    2. Fredj Jawadi & Wael Louhichi & Abdoulkarim Idi Cheffou & Hachmi Ben Ameur, 2019. "Modeling time-varying beta in a sustainable stock market with a three-regime threshold GARCH model," Annals of Operations Research, Springer, vol. 281(1), pages 275-295, October.
    3. Samet Günay, 2017. "Risk Configuration of S&P 500 Industries: Sigma-risk and Alpha-risk Approximation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(2), pages 196-221, May.
    4. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    5. Radosław Kurach, 2013. "Does Beta Explain Global Equity Market Volatility – Some Empirical Evidence," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    6. Hautsch, Nikolaus & Hess, Dieter E. & Veredas, David, 2010. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," CFS Working Paper Series 2010/01, Center for Financial Studies (CFS).
    7. Roberto Pascual & David Veredas, 2009. "Does the open limit order book matter in explaining informational volatility?," ULB Institutional Repository 2013/183777, ULB -- Universite Libre de Bruxelles.
    8. Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
    9. Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    10. Dungey, Mardi & Henry, Olan T & Hvodzdyk, Lyudmyla, 2013. "The impact of jumps and thin trading on realized hedge ratios," Working Papers 2013-02, University of Tasmania, Tasmanian School of Business and Economics, revised 28 Mar 2013.
    11. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2015. "Factor Models as 'Explanatory Unifiers' versus 'Explanatory Ideals' of Empirical Regularities of Stock Returns," DEOS Working Papers 1507, Athens University of Economics and Business.
    12. Marcelle Chauvet & Zeynep Senyuz & Emre Yoldas, 2013. "What does financial volatility tell us about macroeconomic fluctuations?," Finance and Economics Discussion Series 2013-61, Board of Governors of the Federal Reserve System (U.S.).
    13. Degiannakis, Stavros & Filis, George & Kizys, Renatas, 2014. "The effects of oil price shocks on stock market volatility: Evidence from European data," MPRA Paper 96296, University Library of Munich, Germany.
    14. Marshall, Andrew & Maulana, Tubagus & Tang, Leilei, 2009. "The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 250-259, December.
    15. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    16. Murillo Campello & Long Chen & Lu Zhang, 2005. "Expected returns, yield spreads, and asset pricing tests," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
    17. Bergsma, Kelley & Tayal, Jitendra, 2020. "Quarterly earnings announcements and intra-industry information transfer from the Pacific to the Atlantic," International Review of Financial Analysis, Elsevier, vol. 70(C).
    18. Peter Reinhard Hansen & Yiyao Luo, 2023. "Robust Estimation of Realized Correlation: New Insight about Intraday Fluctuations in Market Betas," Papers 2310.19992, arXiv.org.
    19. Christoffersen, Peter & Lunde, Asger & Olesen, Kasper V., 2019. "Factor Structure in Commodity Futures Return and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 1083-1115, June.
    20. Lillie Lam & Laurence Fung & Ip-wing Yu, 2009. "Forecasting a Large Dimensional Covariance Matrix of a Portfolio of Different Asset Classes," Working Papers 0901, Hong Kong Monetary Authority.
    21. Peter C. B. Phillips & Jun Yu, 2009. "Information Loss in Volatility Measurement with Flat Price Trading," Global COE Hi-Stat Discussion Paper Series gd08-039, Institute of Economic Research, Hitotsubashi University.
    22. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Econometrics, MDPI, vol. 11(3), pages 1-36, August.
    23. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    24. Andersen, Torben G. & Riva, Raul & Thyrsgaard, Martin & Todorov, Viktor, 2023. "Intraday cross-sectional distributions of systematic risk," Journal of Econometrics, Elsevier, vol. 235(2), pages 1394-1418.
    25. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    26. Ilze KALNINA, 2015. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Cahiers de recherche 13-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    27. Sean D. Campbell & Francis X. Diebold, 2005. "Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence," NBER Working Papers 11736, National Bureau of Economic Research, Inc.
    28. Kizys, Renatas & Pierdzioch, Christian, 2011. "The changing sensitivity of realized portfolio betas to U.S. output growth: An analysis based on real-time data," Journal of Economics and Business, Elsevier, vol. 63(3), pages 168-186, May.
    29. Sydney C. Ludvigson & Serena Ng, 2005. "The Empirical Risk-Return Relation: A Factor Analysis Approach," NBER Working Papers 11477, National Bureau of Economic Research, Inc.
    30. Dovonon, Prosper & Goncalves, Silvia & Meddahi, Nour, 2010. "Bootstrapping realized multivariate volatility measures," MPRA Paper 40123, University Library of Munich, Germany.
    31. Victor Olkhov, 2018. "Econophysics Beyond General Equilibrium: the Business Cycle Model," Papers 1804.04721, arXiv.org.
    32. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    33. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    34. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    35. 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).
    36. Becker, Janis & Hollstein, Fabian & Prokopczuk, Marcel & Sibbertsen, Philipp, 2019. "The Memory of Beta Factors," Hannover Economic Papers (HEP) dp-661, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    37. Ciner, Cetin, 2015. "Time variation in systematic risk, returns and trading volume: Evidence from precious metals mining stocks," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 277-283.
    38. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    39. Cho, Sungjun, 2014. "What drives stochastic risk aversion?," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 44-63.
    40. Drobetz, Wolfgang & Menzel, Christina & Schröder, Henning, 2016. "Systematic risk behavior in cyclical industries: The case of shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 129-145.
    41. Cooper, Michael J. & Gubellini, Stefano, 2011. "The critical role of conditioning information in determining if value is really riskier than growth," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 289-305, March.
    42. Hwang, Young-Soon & Min, Hong-Ghi & McDonald, Judith A. & Kim, Hwagyun & Kim, Bong-Han, 2010. "Using the credit spread as an option-risk factor: Size and value effects in CAPM," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2995-3009, December.
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    45. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    46. Panagiotis Samartzis & Nikitas Pittis & Nikolaos Kourogenis & Phoebe Koundouri, 2013. "Factor Models of Stock Returns: GARCH Errors versus Autoregressive Betas," DEOS Working Papers 1318, Athens University of Economics and Business.
    47. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
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    55. Barahona, Ricardo & Driessen, Joost & Frehen, Rik, 2021. "Can unpredictable risk exposure be priced?," Journal of Financial Economics, Elsevier, vol. 139(2), pages 522-544.
    56. Andrew Phin & Todd Prono & Jonathan J. Reeves & Konark Saxena, 2018. "Level Shifts in Beta, Spurious Abnormal Returns and the TARP Announcement," Finance and Economics Discussion Series 2018-081, Board of Governors of the Federal Reserve System (U.S.).
    57. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
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    59. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    60. Stavros Degiannakis & George Filis & Renatas Kizys, 2013. "Oil price shocks and stock market volatility: evidence from European data," Working Papers 161, Bank of Greece.
    61. Claudio Morana, 2008. "Realized Betas and the Cross-Section of Expected Returns," ICER Working Papers - Applied Mathematics Series 15-2008, ICER - International Centre for Economic Research.
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    5. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    6. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
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    8. Levich, Richard M. & Potì, Valerio, 2015. "Predictability and ‘good deals’ in currency markets," International Journal of Forecasting, Elsevier, vol. 31(2), pages 454-472.
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    12. David W. Berger & Alain P. Chaboud & Erik Hjalmarsson & Edward Howorka, 2006. "What drives volatility persistence in the foreign exchange market?," International Finance Discussion Papers 862, Board of Governors of the Federal Reserve System (U.S.).
    13. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.

  32. Tim Bollerslev & Michael S. Gibson & Hao Zhou, 2004. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Finance and Economics Discussion Series 2004-56, Board of Governors of the Federal Reserve System (U.S.).

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    3. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    4. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    5. Tai‐Yong Roh & Alireza Tourani‐Rad & Yahua Xu & Yang Zhao, 2021. "Volatility‐of‐volatility risk in the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 245-265, February.
    6. Juan M. Londono & Mary Tian, 2014. "Bank Interventions and Options-based Systemic Risk: Evidence from the Global and Euro-area Crisis," International Finance Discussion Papers 1117, Board of Governors of the Federal Reserve System (U.S.).
    7. Daniel O. Beltran & Deepa Dhume Datta & Thiago Revil T. Ferreira & Matteo Iacoviello & Mohammad Jahan-Parvar & Canlin Li & Juan M. Londono & Marius del Giudice Rodriguez & John H. Rogers & Bo Sun, 2017. "Taxonomy of Global Risk, Uncertainty, and Volatility Measures," International Finance Discussion Papers 1216, Board of Governors of the Federal Reserve System (U.S.).
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
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    15. Nikolay Gospodinov & Ibrahim Jamali, 2014. "The Response of Stock Market Volatility to Futures-Based Measures of Monetary Policy Shocks," FRB Atlanta Working Paper 2014-14, Federal Reserve Bank of Atlanta.
    16. Leonidas Tsiaras, 2010. "The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks," CREATES Research Papers 2010-34, Department of Economics and Business Economics, Aarhus University.
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    41. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
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    43. Ceylan, Özcan, 2016. "Global Risk Aversion Spillover Dynamics and Investors' Attention Allocation," MPRA Paper 71320, University Library of Munich, Germany.
    44. Konstantinidi, Eirini & Skiadopoulos, George, 2016. "How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 62-75.
    45. Muzzioli, Silvia, 2015. "The optimal corridor for implied volatility: From periods of calm to turmoil," Journal of Economics and Business, Elsevier, vol. 81(C), pages 77-94.
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    48. Bu, Ruijun & Fu, Xi & Jawadi, Fredj, 2019. "Does the volatility of volatility risk forecast future stock returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 16-36.
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    51. Geert Bekaert & Eric Engstrom, 2015. "Asset Return Dynamics under Habits and Bad-Environment Good-Environment Fundamentals," Finance and Economics Discussion Series 2015-53, Board of Governors of the Federal Reserve System (U.S.).
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  33. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2003. "Realized Beta: Persistence and Predictability," PIER Working Paper Archive 04-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Mar 2004.

    Cited by:

    1. Dovern, Jonas, 2006. "Predicting GDP components: do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW Kiel).
    2. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    3. David W. Berger & Alain P. Chaboud & Erik Hjalmarsson & Edward Howorka, 2006. "What drives volatility persistence in the foreign exchange market?," International Finance Discussion Papers 862, Board of Governors of the Federal Reserve System (U.S.).
    4. A. Mbairadjim Moussa & J. Sadefo Kamdem & A.F. Shapiro & M. Terraza, 2014. "CAPM with fuzzy returns and hypothesis testing," Post-Print hal-02901727, HAL.
    5. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.
    6. Alfred Mbairadjim Moussa & Jules Sadefo Kamdem & Arnold F. Shapiro & Michel Terraza, 2012. "Capital asset pricing model with fuzzy returns and hypothesis testing," Working Papers 12-33, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    7. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.
    8. Stoja, Evarist & Polanski, Arnold & Nguyen, Linh H. & Pereverzin, Aleksandr, 2023. "Does systematic tail risk matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    9. Richard M. Levich & Valerio Poti, 2008. "Predictability and 'Good Deals' in Currency Markets," NBER Working Papers 14597, National Bureau of Economic Research, Inc.
    10. Fernandes, José L. B. & Hasman, Augusto & Peña, Juan Ignacio, 2006. "Risk premium: insights over the threshold," DEE - Working Papers. Business Economics. WB wb062808, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    11. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    12. Haselmann, Rainer & Herwartz, Helmut, 2008. "Portfolio performance and the Euro: Prospects for new potential EMU members," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 314-330, March.
    13. Nekhili, Ramzi & Bouri, Elie, 2023. "Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management," Energy Economics, Elsevier, vol. 119(C).

  34. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," PIER Working Paper Archive 03-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Sep 2003.

    Cited by:

    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Papers 2003-W21, Economics Group, Nuffield College, University of Oxford.
    2. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    3. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    4. Dominique Guegan & Florian Ielpo, 2007. "Further evidence on the impact of economic news on interest rates," Post-Print halshs-00188331, HAL.
    5. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    6. Mende, Alexander, 2005. "09/11 on the USD/EUR Foreign Exchange Market," Hannover Economic Papers (HEP) dp-312, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    8. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    9. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    10. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    12. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
    13. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2004. "The Cross-Section of Volatility and Expected Returns," NBER Working Papers 10852, National Bureau of Economic Research, Inc.
    14. Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 North American Summer Meetings 487, Econometric Society.
    15. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    16. Jeremy Large, 2005. "Estimating Quadratic Variation When Quoted Prices Jump by a Constant Increment," Economics Series Working Papers 2005-FE-05, University of Oxford, Department of Economics.
    17. Heather Anderson & Fashid Vahid, 2005. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," ANU Working Papers in Economics and Econometrics 2005-451, Australian National University, College of Business and Economics, School of Economics.
    18. Talpsepp, Tõnn & Rieger, Marc Oliver, 2010. "Explaining asymmetric volatility around the world," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 938-956, December.
    19. Álvaro Cartea & Dimitrios Karyampas, 2009. "The Relationship Between the Volatility of Returns and the Number of Jumps in Financial Markets," Birkbeck Working Papers in Economics and Finance 0914, Birkbeck, Department of Economics, Mathematics & Statistics.
    20. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    21. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    22. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    23. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    24. Hassan Zada & Arshad Hassan & Wing-Keung Wong, 2021. "Do Jumps Matter in Both Equity Market Returns and Integrated Volatility: A Comparison of Asian Developed and Emerging Markets," Economies, MDPI, vol. 9(2), pages 1-26, June.
    25. Çelik, Sibel & Ergin, Hüseyin, 2014. "Volatility forecasting using high frequency data: Evidence from stock markets," Economic Modelling, Elsevier, vol. 36(C), pages 176-190.
    26. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    27. Wagner, Niklas & Szimayer, Alexander, 2004. "Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany," Research in International Business and Finance, Elsevier, vol. 18(3), pages 237-251, September.
    28. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    29. Perron, Benoit, 2004. "Détection non paramétrique de sauts dans la volatilité des marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 229-251, Juin-Sept.
    30. Tao, Minjing & Wang, Yahzen & Yao, Qiwei & Zou, Jian, 2011. "Large volatility matrix inference via combining low-frequency and high-frequency approaches," LSE Research Online Documents on Economics 39321, London School of Economics and Political Science, LSE Library.
    31. Antoine Bouveret & Martin Haferkorn & Gaetano Marseglia & Onofrio Panzarino, 2022. "Flash crashes on sovereign bond markets – EU evidence," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 20, Bank of Italy, Directorate General for Markets and Payment System.
    32. Jian Chen & Xiaoquan Liu, 2010. "The model-free measures and the volatility spread," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1829-1833.
    33. Ysusi Carla, 2006. "Estimating Integrated Volatility Using Absolute High-Frequency Returns," Working Papers 2006-13, Banco de México.
    34. Tim Leung & Theodore Zhao, 2024. "A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices," Mathematics, MDPI, vol. 12(6), pages 1-21, March.

  35. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    2. Hui Guo & Christopher J. Neely & Jason Higbee, 2008. "Foreign Exchange Volatility Is Priced in Equities," Financial Management, Financial Management Association International, vol. 37(4), pages 769-790, December.
    3. Juan M. Londono, 2011. "The variance risk premium around the world," International Finance Discussion Papers 1035, Board of Governors of the Federal Reserve System (U.S.).
    4. Christoffersen, Peter & Mazzotta, Stefano, 2004. "The informational content of over-the-counter currency options," Working Paper Series 366, European Central Bank.
    5. Castrén, Olli & Mazzotta, Stefano, 2005. "Foreign exchange option and returns based correlation forecasts: evaluation and two applications," Working Paper Series 447, European Central Bank.

  36. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Real-Time Price Discovery in Stock, Bond and Foreign Exchange Markets," PIER Working Paper Archive 04-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Jun 2004.

    Cited by:

    1. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2014. "Macro News and Bond Yield Spreads in the Euro Area," Discussion Papers of DIW Berlin 1413, DIW Berlin, German Institute for Economic Research.
    2. Michael Ehrmann & Marcel Fratzscher & Roberto Rigobon, 2011. "Stocks, bonds, money markets and exchange rates: measuring international financial transmission," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 948-974, September.
    3. Mihaela NICOLAU, 2010. "Financial Markets Interactions between Economic Theory and Practice," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 27-36.
    4. Yuko Hashimoto & Takatoshi Ito, 2009. "Effects of Japanese Macroeconomic Announcements on the Dollar/Yen Exchange Rate: High-Resolution Picture," NBER Working Papers 15020, National Bureau of Economic Research, Inc.
    5. Ielpo, Florian & Guégan, Dominique, 2006. "Further evidence on the impact of economic news on interest rates," MPRA Paper 3425, University Library of Munich, Germany, revised Jun 2007.
    6. Alenka Kavkler & Mejra Festić, 2011. "Modelling Stock Exchange Index Returns in Different GDP Growth Regimes," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(1), pages 3-22.
    7. Bredin, Don & Hyde, Stuart & O'Reilly, Gerard, 2005. "European Monetary Policy Surprises: The Aggregate and Sectoral Stock Market Response," Research Technical Papers 10/RT/05, Central Bank of Ireland.
    8. Alessandro Beber & Michael W. Brandt, 2003. "The Effect of Macroeconomic News on Beliefs and Preferences: Evidence from the Options Market," NBER Working Papers 9914, National Bureau of Economic Research, Inc.
    9. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    10. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
    11. Mo, Henry & Wu, Liuren, 2007. "International capital asset pricing: Evidence from options," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 465-498, September.
    12. Hanno Lustig & Stijn Van Nieuwerburgh, 2005. "The Returns on Human Capital: Good News on Wall Street is Bad News on Main Street," NBER Working Papers 11564, National Bureau of Economic Research, Inc.
    13. Saban Nazlioglu & Shawkat Hammoudeh & Rangan Gupta, 2015. "Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4996-5011, October.
    14. Victor Fang & Chien-Ting Lin & Kunaal Parbhoo, 2008. "Macroeconomic News, Business Cycles and Australian Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(3), pages 185-207, December.
    15. Enzo Weber, 2007. "Volatility and Causality in Asia Pacific Financial Markets," SFB 649 Discussion Papers SFB649DP2007-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Fatih Ozatay & Erdal Ozmen & Gülbin Sahinbeyoglu, 2007. "Emerging Market Sovereign Spreads, Global Financial Conditions and U.S. Macroeconomic News," ERC Working Papers 0707, ERC - Economic Research Center, Middle East Technical University, revised Dec 2007.
    17. Faust, Jon & Rogers, John H. & Wang, Shing-Yi B. & Wright, Jonathan H., 2007. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1051-1068, May.
    18. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    19. Francis X. Diebold & Kamil Yilmaz, 2008. "Macroeconomic Volatility and Stock Market Volatility, World-Wide," PIER Working Paper Archive 08-031, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Bruce Mizrach & Christopher J. Neely, 2007. "The microstructure of the U.S. treasury market," Working Papers 2007-052, Federal Reserve Bank of St. Louis.
    21. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    22. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    23. Jon Wongswan, 2005. "The response of global equity indexes to U.S. monetary policy announcements," International Finance Discussion Papers 844, Board of Governors of the Federal Reserve System (U.S.).
    24. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    25. Rui Albuquerque & Gregory Bauer & Martin Schneider, 2004. "Characterizing Asymmetric Information in International Equity Markets," International Finance 0405005, University Library of Munich, Germany.
    26. Schneider, Martin & Albuquerque, Rui & ,, 2006. "Global Private Information in International Equity Markets," CEPR Discussion Papers 5819, C.E.P.R. Discussion Papers.
    27. Patrice T. Robitaille & Jennifer E. Roush, 2006. "How do FOMC actions and U.S. macroeconomic data announcements move Brazilian sovereign yield spreads and stock prices?," International Finance Discussion Papers 868, Board of Governors of the Federal Reserve System (U.S.).
    28. Meredith J. Beechey & Jonathan H. Wright, 2008. "The high-frequency impact of news on long-term yields and forward rates: Is it real?," Finance and Economics Discussion Series 2008-39, Board of Governors of the Federal Reserve System (U.S.).
    29. Savaser, Tanseli, 2011. "Exchange rate response to macronews: Through the lens of microstructure," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 107-126, February.
    30. Joshua Hausman & Jon Wongswan, 2006. "Global asset prices and FOMC announcements," International Finance Discussion Papers 886, Board of Governors of the Federal Reserve System (U.S.).
    31. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2017. "Macro News and Commodity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 68-80, January.
    32. Marcel Fratzscher, 2011. "Capital Flows, Push versus Pull Factors and the Global Financial Crisis," NBER Working Papers 17357, National Bureau of Economic Research, Inc.
    33. Luc Arrondel & Hector Calvo Pardo & Xisco Oliver, 2007. "Temperant portfolio choice and background risk: evidence from France," PSE Working Papers halshs-00588069, HAL.
    34. Massimo Guidolin & Allan Timmerman, 2005. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Working Papers 2005-003, Federal Reserve Bank of St. Louis.
    35. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
    36. Hashimoto, Yuko & Ito, Takatoshi, 2010. "Effects of Japanese macroeconomic statistic announcements on the dollar/yen exchange rate: High-resolution picture," Journal of the Japanese and International Economies, Elsevier, vol. 24(3), pages 334-354, September.
    37. Aron Drew & Özer Karagedikli, 2007. "Some Benefits of Monetary-Policy Transparency in New Zealand," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(11-12), pages 521-539, December.
    38. Christian Gourieroux & Alain Monfort & Razvan Sufana, 2005. "International Money and Stock Market Contingent Claims," Working Papers 2005-41, Center for Research in Economics and Statistics.
    39. Oikarinen, Elias, 2006. "Price Linkages between Stock, Bond and Housing Markets - Evidence from Finnish Data," Discussion Papers 1004, The Research Institute of the Finnish Economy.
    40. Alessandro Beber & Michael W. Brandt, 2009. "Resolving Macroeconomic Uncertainty in Stock and Bond Markets," Review of Finance, European Finance Association, vol. 13(1), pages 1-45.
    41. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    42. Erenburg, Grigori & Kurov, Alexander & Lasser, Dennis J., 2006. "Trading around macroeconomic announcements: Are all traders created equal?," Journal of Financial Intermediation, Elsevier, vol. 15(4), pages 470-493, October.
    43. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    44. Christiansen, Charlotte & Ranaldo, Angelo, 2005. "Realized Bond-Stock Correlation: Macroeconomic Announcement Effects," Finance Research Group Working Papers F-2005-05, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    45. Marc Simpson & Sanjay Ramchander & James Webb, 2007. "The Asymmetric Response of Equity REIT Returns to Inflation," The Journal of Real Estate Finance and Economics, Springer, vol. 34(4), pages 513-529, May.
    46. Ehrmann, Michael & Fratzscher, Marcel & Swanson, Eric & Gürkaynak, Refet S., 2007. "Convergence and anchoring of yield curves in the euro area," Working Paper Series 817, European Central Bank.
    47. P. Siklos, M. Bohl, 2006. "Policy Words and Policy Deeds: The ECB and the Euro," Working Papers eg0050, Wilfrid Laurier University, Department of Economics, revised 2006.
    48. Gropp, Reint E. & Kadareja, Arjan, 2007. "Stale information, shocks and volatility," ZEW Discussion Papers 07-012, ZEW - Leibniz Centre for European Economic Research.
    49. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    50. Condie, Scott & Ganguli, Jayant, 2017. "The pricing effects of ambiguous private information," Journal of Economic Theory, Elsevier, vol. 172(C), pages 512-557.
    51. Guo, Hui & Savickas, Robert, 2008. "Forecasting foreign exchange rates using idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1322-1332, July.
    52. Stefano d'Addona & Axel H. Kind, 2005. "International Stock-Bond Correlations in a Simple Affine Asset Pricing Model," Finance 0502018, University Library of Munich, Germany.
    53. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," Economics Series Working Papers 389, University of Oxford, Department of Economics.
    54. Hui Guo & Robert Savickas, 2006. "Idiosyncratic volatility, economic fundamentals, and foreign exchange rates," Working Papers 2005-025, Federal Reserve Bank of St. Louis.
    55. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    56. Celine Gimet & Sandra Montchaud, 2016. "What Drives European Football Clubs’ Stock Returns and Volatility?," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 23(3), pages 351-390, September.
    57. Troy Davig & Jeffrey R. Gerlach, 2006. "Monetary Policy, the Bond Market, and Changes in FOMC Communication Policy," Working Papers 31, Department of Economics, College of William and Mary.
    58. Michael Ehrmann & Marcel Fratzscher, 2009. "Global Financial Transmission of Monetary Policy Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 739-759, December.
    59. Pietro Cova & Mr. Alessandro Rebucci & Mr. Akito Matsumoto & Massimiliano Pisani, 2008. "New Shocks, Exchange Rates and Equity Prices," IMF Working Papers 2008/284, International Monetary Fund.
    60. Paola Paiardini, 2010. "The Price Impact of Economic News, Private Information and Trading Intensity," Birkbeck Working Papers in Economics and Finance 1011, Birkbeck, Department of Economics, Mathematics & Statistics.
    61. Andersson, Magnus & Hansen, Lars Jul & Sebestyén, Szabolcs, 2006. "Which news moves the euro area bond market?," Working Paper Series 631, European Central Bank.
    62. Mizrach, Bruce & Neely, Christopher J., 2008. "Information shares in the US Treasury market," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1221-1233, July.
    63. Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank.
    64. Alexandr Èerný & Michal Koblas, 2008. "Stock Market Integration and the Speed of Information Transmission," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(01-02), pages 2-20, January.
    65. Lindner Axel, 2009. "Evaluating Communication Strategies for Public Agencies: Transparency, Opacity, and Secrecy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-18, July.
    66. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    67. Torben G. Andersen & Luca Benzoni, 2007. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification test for Affine Term Structure Models," NBER Working Papers 12962, National Bureau of Economic Research, Inc.
    68. Helena Chuliá & Hipòlit Torró, 2008. "The economic value of volatility transmission between the stock and bond markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(11), pages 1066-1094, November.
    69. Weihua Shi & Larry Eisenberg & Cheng-few Lee, 2009. "Intraday Patterns, Announcement Effects, and Volatility Persistence in the Japanese Government Bond Futures Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 63-85.
    70. George Jiang & Ingrid Lo & Adrien Verdelhan, 2008. "Information Shocks, Jumps, and Price Discovery -- Evidence from the U.S. Treasury Market," Staff Working Papers 08-22, Bank of Canada.
    71. Albuquerque, Rui & Vega, Clara, 2006. "Asymmetric Information in the Stock Market: Economic News and Co-movement," CEPR Discussion Papers 5598, C.E.P.R. Discussion Papers.
    72. Tamim Bayoumi & Andrew Swiston, 2010. "The Ties that Bind: Measuring International Bond Spillovers Using Inflation-Indexed Bond Yields," IMF Staff Papers, Palgrave Macmillan, vol. 57(2), pages 366-406, June.
    73. Herrmann, Klaus & Teis, Stefan & Yu, Weijun, 2014. "Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures," FAU Discussion Papers in Economics 15/2014, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    74. Gregory H. Bauer & Clara Vega, 2006. "The monetary origins of asymmetric information in international equity markets," International Finance Discussion Papers 872, Board of Governors of the Federal Reserve System (U.S.).
    75. Paolo Pasquariello & Clara Vega, 2006. "Informed and strategic order flow in the bond markets," International Finance Discussion Papers 874, Board of Governors of the Federal Reserve System (U.S.).
    76. Lindner, Axel, 2008. "Evaluating communication strategies for public agencies: transparency, opacity, and secrecy," IWH Discussion Papers 8/2008, Halle Institute for Economic Research (IWH).
    77. Apergis, Nicholas, 2015. "The role of FOMC minutes for US asset prices before and after the 2008 crisis: Evidence from GARCH volatility modeling," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 100-107.
    78. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    79. Tuysuz, Sukriye, 2007. "The asymmetric impact of macroeconomic announcements on U.S. Government bond rate level and volatility," MPRA Paper 5381, University Library of Munich, Germany.
    80. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
    81. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
    82. Laakkonen, Helinä, 2004. "The impact of macroeconomic news on exchange rate volatility," Bank of Finland Research Discussion Papers 24/2004, Bank of Finland.
    83. Bent Jesper Christensen & Morten Ø. Nielsen, 2005. "The Implied-realized Volatility Relation With Jumps In Underlying Asset Prices," Working Paper 1186, Economics Department, Queen's University.
    84. Ghent, Andra, 2007. "Why do markets react badly to good news? Evidence from Fed Funds Futures," MPRA Paper 1708, University Library of Munich, Germany.
    85. Jon Faust & Jonathan H. Wright, 2008. "Efficient Prediction of Excess Returns," NBER Working Papers 14169, National Bureau of Economic Research, Inc.
    86. Jeffrey R. Gerlach, 2007. "Macroeconomic News And Stock Market Calendar And Weather Anomalies," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 30(2), pages 283-300, June.

  37. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. Dominique Guegan & Florian Ielpo, 2007. "Further evidence on the impact of economic news on interest rates," Post-Print halshs-00188331, HAL.
    3. Laurent E. Calvet & Adlai J. Fisher, 2005. "Multifrequency News and Stock Returns," NBER Working Papers 11441, National Bureau of Economic Research, Inc.
    4. Mende, Alexander, 2005. "09/11 on the USD/EUR Foreign Exchange Market," Hannover Economic Papers (HEP) dp-312, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    5. Gregory Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Staff Working Papers 07-20, Bank of Canada.
    6. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre.
    7. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    9. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    10. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
    11. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometrics of testing for jumps in financial economics using bipower variationÂ," OFRC Working Papers Series 2004fe01, Oxford Financial Research Centre.
    12. Anderson, Heather M. & Vahid, Farshid, 2007. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 76-90, January.
    13. Álvaro Cartea & Dimitrios Karyampas, 2009. "The Relationship Between the Volatility of Returns and the Number of Jumps in Financial Markets," Birkbeck Working Papers in Economics and Finance 0914, Birkbeck, Department of Economics, Mathematics & Statistics.
    14. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    15. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    16. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    17. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    18. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    19. Wagner, Niklas & Szimayer, Alexander, 2004. "Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany," Research in International Business and Finance, Elsevier, vol. 18(3), pages 237-251, September.
    20. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    21. Perron, Benoit, 2004. "Détection non paramétrique de sauts dans la volatilité des marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 229-251, Juin-Sept.
    22. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford.
    23. Jian Chen & Xiaoquan Liu, 2010. "The model-free measures and the volatility spread," Applied Economics Letters, Taylor & Francis Journals, vol. 17(18), pages 1829-1833.
    24. Tim Leung & Theodore Zhao, 2024. "A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    25. Audrino, Francesco & Camponovo, Lorenzo & Roth, Constantin, 2015. "Testing the lag structure of assets’ realized volatility dynamics," Economics Working Paper Series 1501, University of St. Gallen, School of Economics and Political Science.
    26. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2004. "The Cross-Section of Volatility and Expected Returns," NBER Working Papers 10852, National Bureau of Economic Research, Inc.
    27. Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 North American Summer Meetings 487, Econometric Society.
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    Cited by:

    1. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    3. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    4. Alessandra Amendola & Giuseppe Storti, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers SFB649DP2009-007, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Neil Shephard & Ole Barndorff-Nielsen, 2003. "A feasible central limit theory for realised volatility under leverage," Economics Series Working Papers 2004-FE-03, University of Oxford, Department of Economics.
    6. Barndorff-Nielsen, Ole E. & Shephard, Neil, 2006. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 217-252.
    7. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    8. Christoffersen, Peter & Mazzotta, Stefano, 2004. "The informational content of over-the-counter currency options," Working Paper Series 366, European Central Bank.
    9. Scott I. White & Adam E. Clements & Stan Hurn, 2004. "Discretised Non-Linear Filtering for Dynamic Latent Variable Models: with Application to Stochastic Volatility," Econometric Society 2004 Australasian Meetings 46, Econometric Society.
    10. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.

  40. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," NBER Technical Working Papers 0279, National Bureau of Economic Research, Inc.

    Cited by:

    1. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    2. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    4. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    5. Zagaglia, Paolo, 2008. "Money-market segmentation in the euro area: what has changed during the turmoil?," Bank of Finland Research Discussion Papers 23/2008, Bank of Finland.
    6. Haselmann, Rainer & Helmut, Herwartz, 2005. "The Introduction of the Euro and its Effects on Investment Decisions," Economics Working Papers 2005-15, Christian-Albrechts-University of Kiel, Department of Economics.
    7. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    8. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    9. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," CIRANO Working Papers 2002s-91, CIRANO.
    10. Laarni Bulan & Christopher Mayer & C. Tsuriel Somerville, "undated". "Irreversible Investment, Real Options, and Competition: Evidence from Real Estate Development," Zell/Lurie Center Working Papers 391, Wharton School Samuel Zell and Robert Lurie Real Estate Center, University of Pennsylvania.
    11. Victor Olkhov, 2020. "Volatility Depend on Market Trades and Macro Theory," Papers 2008.07907, arXiv.org.
    12. Sabrina Camargo & Silvio M. Duarte Queiros & Celia Anteneodo, 2013. "Bridging stylized facts in finance and data non-stationarities," Papers 1302.3197, arXiv.org, revised May 2013.
    13. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
    14. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    15. Brousseau, Vincent & Durré, Alain, 2013. "Interest rate volatility: a consol rate-based measure," Working Paper Series 1505, European Central Bank.
    16. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
    17. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    18. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    19. Michael W. Brandt & Francis X. Diebold, 2006. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
    20. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    21. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
    22. Ole E. Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2001. "Some recent developments in stochastic volatility modelling," Economics Papers 2001-W25, Economics Group, Nuffield College, University of Oxford.
    23. Frowin Schulz & Karl Mosler, 2011. "The effect of infrequent trading on detecting price jumps," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 27-58, March.
    24. Ravi Bansal & Varoujan Khatchatrian & Amir Yaron, 2004. "Interpretable Asset Markets?," 2004 Meeting Papers 136b, Society for Economic Dynamics.
    25. Julian Pareja Vasseur & Juan Giraldo Cerón & Santiago Zapata Valencia, 2017. "Market Risk, Non-parametric Methods: Hong-Kong Case," Economia Coyuntural,Revista de temas de perspectivas y coyuntura, Instituto de Investigaciones Economicas y Sociales 'Jose Ortiz Mercado' (IIES-JOM), Facultad de Ciencias Economicas, Administrativas y Financieras, Universidad Autonoma Gabriel Rene Moreno, vol. 2(4), pages 45-80.
    26. Sydney C. Ludvigson & Serena Ng, 2005. "The Empirical Risk-Return Relation: A Factor Analysis Approach," NBER Working Papers 11477, National Bureau of Economic Research, Inc.
    27. Nadhem Selmi & Nejib Hachicha, 2014. "Were Oil Price Markets the Source of Credit Crisis in European Countries? Evidence Using a VAR-MGARCH-DCC Model," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 169-177.
    28. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
    29. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    30. Li, Handong & Cao, Shi-Nan & Wang, Yan, 2010. "The properties and mechanism of long-term memory in nonparametric volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3254-3259.
    31. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    32. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    33. Oliver Linton & Anisha Ghosh, 2007. "Consistent Estimation of the Risk-Return Tradeoff in the Presence of Measurement Error," FMG Discussion Papers dp605, Financial Markets Group.
    34. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    35. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    36. Sean D. Campbell & Canlin Li, 2004. "Alternative estimates of the presidential premium," Finance and Economics Discussion Series 2004-69, Board of Governors of the Federal Reserve System (U.S.).
    37. Jeremy Large, 2005. "Estimating Quadratic Variation When Quoted Prices Jump by a Constant Increment," Economics Series Working Papers 2005-FE-05, University of Oxford, Department of Economics.
    38. B. Jungbacker & S.J. Koopman, 2005. "Model-based Measurement of Actual Volatility in High-Frequency Data," Tinbergen Institute Discussion Papers 05-002/4, Tinbergen Institute.
    39. Jianqing Fan & Yingying Fan & Jinchi Lv, 0. "Aggregation of Nonparametric Estimators for Volatility Matrix," Journal of Financial Econometrics, Oxford University Press, vol. 5(3), pages 321-357.
    40. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
    41. Yi, Chae-Deug, 2020. "Jump probability using volatility periodicity filters in US Dollar/Euro exchange rates," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    42. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2010. "Jump-robust volatility estimation using nearest neighbor truncation," Staff Reports 465, Federal Reserve Bank of New York.
    43. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    44. Fornari, Fabio, 2010. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 722-743, September.
    45. Fornari, Fabio, 2008. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Working Paper Series 859, European Central Bank.
    46. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
    47. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    48. Amir Safari & Detlef Seese, 2009. "Non-parametric estimation of a multiscale CHARN model using SVR," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 105-121.
    49. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    50. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.
    51. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    52. Daniel Jubinski & Amy F. Lipton, 2012. "Equity volatility, bond yields, and yield spreads," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(5), pages 480-503, May.
    53. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    54. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
    55. Hyeong-Ohk Bae & Seung-Yeal Ha & Yongsik Kim & Hyuncheul Lim & Jane Yoo, 2020. "Volatility Flocking by Cucker–Smale Mechanism in Financial Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 387-414, September.
    56. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
    57. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    58. Fornari, Fabio & Mele, Antonio, 2006. "Approximating volatility diffusions with CEV-ARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 931-966, June.
    59. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
    60. Chun-Hung Chen & Wei-Choun Yu & Eric Zivot, 2009. "Predicting Stock Volatility Using After-Hours Information," Working Papers UWEC-2009-01, University of Washington, Department of Economics.
    61. YI, Chae-Deug, 2023. "Exchange rate volatility and intraday jump probability with periodicity filters using a local robust variance," Finance Research Letters, Elsevier, vol. 55(PA).
    62. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "How accurate is the asymptotic approximation to the distribution of realised volatility?," Economics Papers 2001-W16, Economics Group, Nuffield College, University of Oxford.

  41. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.

    Cited by:

    1. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    2. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    3. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    4. Ke Yang & Langnan Chen & Fengping Tian, 2015. "Realized Volatility Forecast of Stock Index Under Structural Breaks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(1), pages 57-82, January.
    5. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    6. Corradi, Valentina & Distaso, Walter & Swanson, Norman R., 2009. "Predictive density estimators for daily volatility based on the use of realized measures," Journal of Econometrics, Elsevier, vol. 150(2), pages 119-138, June.
    7. Sugra Ingilab Humbatova & Natig Gadim-Oglu Hajiyev, 2022. "The Impact of Oil Prices on Income in Azerbaijan," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 207-216.
    8. Tim Bollerslev & Natalia Sizova & George Tauchen, 2009. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," Working Papers 10-73, Duke University, Department of Economics.
    9. Álvaro Cartea & Dimitrios Karyampas, 2009. "Volatility and Covariation of Financial Assets: A High-Frequency Analysis," Birkbeck Working Papers in Economics and Finance 0913, Birkbeck, Department of Economics, Mathematics & Statistics.
    10. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    11. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," CIRANO Working Papers 2002s-91, CIRANO.
    12. Wang, Gang & Sharma, Paritosh & Jain, Vipin & Shukla, Avanish & Shahzad Shabbir, Malik & Tabash, Mosab I. & Chawla, Chanchal, 2022. "The relationship among oil prices volatility, inflation rate, and sustainable economic growth: Evidence from top oil importer and exporter countries," Resources Policy, Elsevier, vol. 77(C).
    13. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    14. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    15. Politis, Dimitris N & Thomakos, Dimitrios D, 2008. "NoVaS Transformations: Flexible Inference for Volatility Forecasting," University of California at San Diego, Economics Working Paper Series qt982208kx, Department of Economics, UC San Diego.
    16. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    17. Rentschler, Jun E., 2013. "Oil price volatility, economic growth and the hedging role of renewable energy," Policy Research Working Paper Series 6603, The World Bank.
    18. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2008. "The Role Of Implied Volatility In Forecasting Future Realized Volatility And Jumps In Foreign Exchange, Stock, And Bond Markets," Working Paper 1181, Economics Department, Queen's University.
    19. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    20. Bent Jesper Christensen & Morten Ø. Nielsen & Thomas Busch, 2006. "The Information Content Of Treasury Bond Options Concerning Future Volatility And Price Jumps," Working Paper 1188, Economics Department, Queen's University.
    21. Laurent Calvet & Adlai Fisher, 2003. "Regime-Switching and the Estimation of Multifractal Processes," Harvard Institute of Economic Research Working Papers 1999, Harvard - Institute of Economic Research.
    22. Basistha, Arabinda & Kurov, Alexander & Wolfe, Marketa Halova, 2019. "Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility," MPRA Paper 111037, University Library of Munich, Germany.
    23. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "There is a Risk-Return Tradeoff After All," CIRANO Working Papers 2004s-24, CIRANO.
    24. Marina Theodosiou, 2010. "Calendar Time Sampling of High Frequency Financial Asset Price and the Verdict on Jumps," Working Papers 2010-7, Central Bank of Cyprus.
    25. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    26. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    27. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    28. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," PIER Working Paper Archive 11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    29. Beum-Jo Park, 2011. "Forecasting Volatility in Financial Markets Using a Bivariate Stochastic Volatility Model with Surprising Information," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 37-58, September.
    30. Peter Reinhard Hansen & Asger Lunde, 2005. "A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 525-554.
    31. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk — realised semivariance," CREATES Research Papers 2008-42, Department of Economics and Business Economics, Aarhus University.
    32. Ghysels, Eric & Sinko, Arthur, 2011. "Volatility forecasting and microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 257-271, January.
    33. John M Maheu & Thomas H McCurdy, 2008. "Do high-frequency measures of volatility improve forecasts of return distributions?," Working Papers tecipa-324, University of Toronto, Department of Economics.
    34. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    35. Cheng Jiang & Kose John & David Larsen, 2021. "R&D investment intensity and jump volatility of stock price," Review of Quantitative Finance and Accounting, Springer, vol. 57(1), pages 235-277, July.
    36. Andersen, Torben G. & Bollerslev, Tim & Huang, Xin, 2011. "A reduced form framework for modeling volatility of speculative prices based on realized variation measures," Journal of Econometrics, Elsevier, vol. 160(1), pages 176-189, January.
    37. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    38. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    39. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    40. Neil Shephard & Silja Kinnebrock & Ole E. Barndorff-Neilsen, 2008. "Measuring downside risk - realised semivariance," Economics Series Working Papers 382, University of Oxford, Department of Economics.
    41. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    42. Basel Awartani & Valentina Corradi, 2004. "Testing and Modelling Market Microstructure Effects with an Application to the Dow Jones Industrial Average," Econometric Society 2004 North American Summer Meetings 487, Econometric Society.
    43. Mehdi Mili & Jean‐Michel Sahut & Frédéric Teulon, 2020. "Shift‐contagion in energy markets and global crisis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 725-736, August.
    44. Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
    45. Barndorff-Nielsen, Ole E. & Shephard, Neil, 2006. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 217-252.
    46. Shirota, Shinichiro & Hizu, Takayuki & Omori, Yasuhiro, 2014. "Realized stochastic volatility with leverage and long memory," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 618-641.
    47. Masoumeh Fathi & Klaus Grobys & James W. Kolari, 2024. "On the Realized Risk of Foreign Exchange Rates: A Fractal Perspective," JRFM, MDPI, vol. 17(2), pages 1-14, February.
    48. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    49. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    50. Torben G. Andersen & Viktor Todorov, 2009. "Realized Volatility and Multipower Variation," CREATES Research Papers 2009-49, Department of Economics and Business Economics, Aarhus University.
    51. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    52. Jeremy Large, 2005. "Estimating Quadratic Variation When Quoted Prices Jump by a Constant Increment," Economics Series Working Papers 2005-FE-05, University of Oxford, Department of Economics.
    53. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    54. Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
    55. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    56. Bozhechkova, Alexandra (Божечкова, Александра) & Ivanov, Evgeny (Иванов, Евгений) & Orekhov, Mikhail (Орехов, Михаил) & Trunin, Pavel (Трунин, Павел) & Chembulatova, Maria (Чембулатова, Мария) & Yakov, 2021. "Analysis of the Behavior of Banks and Companies in the Conditions of Exchange Volatility in Russia [Анализ Поведения Банков И Компаний В Условиях Курсовой Волатильности В России]," Working Papers w20220176, Russian Presidential Academy of National Economy and Public Administration.
    57. Duembgen, Moritz & Podolskij, Mark, 2015. "High-frequency asymptotics for path-dependent functionals of Itô semimartingales," Stochastic Processes and their Applications, Elsevier, vol. 125(4), pages 1195-1217.
    58. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    59. Peter R. Hansen & Asger Lunde, 2010. "Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error," CREATES Research Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    60. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    61. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility Regressions with Fat Tails," TSE Working Papers 20-1097, Toulouse School of Economics (TSE).
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    117. Garcia, René & Lewis, Marc-André & Pastorello, Sergio & Renault, Éric, 2011. "Estimation of objective and risk-neutral distributions based on moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 22-32, January.
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    119. Fan, Jianqing & Fan, Yingying & Jiang, Jiancheng, 2007. "Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 618-631, June.
    120. Jie Zhu, 2009. "Pricing volatility of stock returns with volatile and persistent components," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(3), pages 243-269, September.
    121. Sohel Azad, A.S.M. & Batten, Jonathan A. & Fang, Victor & Wickramanayake, Jayasinghe, 2015. "International swap market contagion and volatility," Economic Modelling, Elsevier, vol. 47(C), pages 355-371.
    122. Jie Zhu, 2008. "Pricing Volatility of Stock Returns with Volatile and Persistent Components," CREATES Research Papers 2008-14, Department of Economics and Business Economics, Aarhus University.
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    124. Chun Liu & John M Maheu, 2008. "Forecasting Realized Volatility: A Bayesian Model Averaging Approach," Working Papers tecipa-313, University of Toronto, Department of Economics.
    125. Barone-Adesi, Giovanni & Rasmussen, Henrik & Ravanelli, Claudia, 2005. "An option pricing formula for the GARCH diffusion model," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 287-310, April.
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    127. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.
    128. Yacine Ait-Sahalia & Robert Kimmel, 2004. "Maximum Likelihood Estimation of Stochastic Volatility Models," NBER Working Papers 10579, National Bureau of Economic Research, Inc.
    129. Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.
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    131. Kaeck, Andreas & Alexander, Carol, 2012. "Volatility dynamics for the S&P 500: Further evidence from non-affine, multi-factor jump diffusions," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3110-3121.
    132. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.
    133. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    134. Kyungsub Lee, 2013. "Probabilistic and statistical properties of moment variations and their use in inference and estimation based on high frequency return data," Papers 1311.5036, arXiv.org, revised Jul 2015.
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  44. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.

    Cited by:

    1. Hau, Harald, 2002. "The Role of Transaction Costs for Financial Volatility: Evidence from the Paris Bourse," CEPR Discussion Papers 3651, C.E.P.R. Discussion Papers.
    2. Adam Wu, 2017. "Systematic Noise: Micro-movements in Equity Options Markets," Papers 1708.06855, arXiv.org.
    3. Magdalena Vorzsak & Carmen Maria Gut, 2008. "Constraints Concerning Investment And Participation In Professional Training In The Companies From The Romanian Manufacturing Industry," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    4. Theodoros Diasakos, 2008. "Comparative Statics of Asset Prices," Carlo Alberto Notebooks 72, Collegio Carlo Alberto, revised 2011.
    5. M. Illueca & J. A. LaFuente, 2006. "New evidence on expiration‐day effects using realized volatility: An intraday analysis for the Spanish stock exchange," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(9), pages 923-938, September.
    6. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0504009, University Library of Munich, Germany, revised 17 Jan 2006.
    7. Özer Karagedikli & Pierre L. Siklos, 2008. "Explaining Movements in the NZ Dollar - Central Bank Communication and the Surprise Element in Monetary Policy?," Reserve Bank of New Zealand Discussion Paper Series DP2008/02, Reserve Bank of New Zealand.
    8. Sam Howison & David Lamper, 2001. "Trading volume in models of financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(2), pages 119-135.
    9. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    10. Tiberiu Cristian Avramescu, 2008. "Romanian Tourism: A Regional Approach," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    11. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    12. Šárka Brychtová, 2008. "Spa Healing Sources In Czech Republic," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    13. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    14. Mihaela Dragan & Zenovia Cristiana Pop, 2008. "CRITERIA FOR PRODUCT QUALITY IN THE FRAME OF INTERCULTURAL MARKET STRATEGIES OF SMALL AND MEDIUM SIZED ENTERPRISES - a brief review of literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    15. Hayette Gatfaoui, 2006. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton's Credit Risk Valuation," Post-Print hal-00589918, HAL.
    16. Manole Velicanu & Gheorghe Matei, 2008. "Decision Support Systems: Present And Future Trends," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    17. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch Small und Mid Caps?," Sonderforschungsbereich 504 Publications 05-10, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    18. Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
    19. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    20. Cristina Silvia Nistor & Crina Ioana Filip & Adela Deaconu, 2008. "Derivative Instruments – Alternatives To Cover The Foreign Exchange Rate In The Case Of Import-Export Operations - Accounting Approach For Romania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    21. David S. Bates, 2003. "Maximum Likelihood Estimation of Latent Affine Processes," NBER Working Papers 9673, National Bureau of Economic Research, Inc.
    22. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    23. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    24. Cristina Curutiu, 2008. "Methods Of Portfolio Management - A Review Of Literature -," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    25. Partenie Dumbrava & Ioan Pop & Eniko Fazakas & Jozsef Fazakas & Ludovica Breban, 2008. "The Environmental Impact Of Beer Production," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    26. Michael W. Brandt & Qiang Kang, 2002. "On the Relationship Between the Conditional Mean and Volatility of Stock Returns: A Latent VAR Approach," NBER Working Papers 9056, National Bureau of Economic Research, Inc.
    27. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    28. Srečko Devjak & Andraž Grum, 2006. "Third Moment of Yield Probability Distributions for Instruments on Slovenian Financial Markets," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(4), pages 364-373.
    29. Su, Ender & Wong, Kai Wen, 2018. "Measuring bank downside systemic risk in Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 172-193.
    30. Stavros Degiannakis & Alexandra Livada & Epaminondas Panas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," Applied Economics, Taylor & Francis Journals, vol. 40(23), pages 3051-3067.
    31. Srecko Devjak & Andraz Grum, 2005. "Market Risk Control In Stable Paretian Markets," Economic Thought and Practice, Department of Economics and Business, University of Dubrovnik, vol. 14(2), pages 147-160, december.
    32. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    33. Borgsen, Sina & Glaser, Markus, 2005. "Diversifikationseffekte durch small und mid caps? : Eine empirische Untersuchung basierend auf europäischen Aktienindizes," Papers 05-10, Sonderforschungsbreich 504.
    34. Adina Negrusa & Oana Adriana Gica, 2008. "Analysis Of Potential Sme’S Role For Developing Tourism In Transylvania," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    35. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    36. Høg, Esben, 2008. "Volatility and realized quadratic variation of differenced returns : A wavelet method approach," Finance Research Group Working Papers F-2008-06, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    37. Ivanovski, Zoran & Stojanovski, Toni & Narasanov, Zoran, 2015. "Volatility And Kurtosis Of Daily Stock Returns At Mse," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 6(2), pages 209-221.
    38. Adrian Grosanu & Paula Ramona Rachisan, 2008. "The Implementation Of Profit Centres Inside An Economic Entity," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    39. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.

  45. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    4. Meddahi, N., 2001. "A Theoretical Comparison Between Integrated and Realized Volatilies," Cahiers de recherche 2001-26, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    5. Dmitri Koulikov, 2002. "Modeling Sequences of Long Memory Positive Weakly Stationary Random Variables," William Davidson Institute Working Papers Series 493, William Davidson Institute at the University of Michigan.
    6. Adusei Jumah, 2001. "The effects of dollar-sterling exchange rate volatility on futures markets for coffee and cocoa," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 28(3), pages 307-328, October.
    7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics," Economics Papers 2002-W13, Economics Group, Nuffield College, University of Oxford, revised 18 Mar 2002.
    9. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Correcting the Errors: A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," CIRANO Working Papers 2002s-91, CIRANO.
    10. Klaassen, F.J.G.M., 1999. "Why is it so Difficult to Find An Effect of Exchange Rate Risk on Trade?," Discussion Paper 1999-73, Tilburg University, Center for Economic Research.
    11. Elena Andreou & Eric Ghysels, 2000. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation and Empirical Results," CIRANO Working Papers 2000s-19, CIRANO.
    12. Michel Beine, 2004. "Conditional covariance and direct Central Bank intervention in the foreign exchange markets," ULB Institutional Repository 2013/10431, ULB -- Universite Libre de Bruxelles.
    13. Dimitrios D. Thomakos & Michail S. Koubouros, 2005. "Realized Volatility and Asymmetries in the A.S.E. Returns," Finance 0504009, University Library of Munich, Germany, revised 17 Jan 2006.
    14. Campbell, John Y & Kim, Sangjoon & Lettau, Martin, 1998. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," CEPR Discussion Papers 1923, C.E.P.R. Discussion Papers.
    15. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    16. Perez, Ana & Ruiz, Esther, 2001. "Finite sample properties of a QML estimator of stochastic volatility models with long memory," Economics Letters, Elsevier, vol. 70(2), pages 157-164, February.
    17. Eric Hillebrand & Marcelo Cunha Medeiros, 2007. "Forecasting realized volatility models:the benefits of bagging and nonlinear specifications," Textos para discussão 547, Department of Economics PUC-Rio (Brazil).
    18. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    19. Laurent Calvet, 2000. "Forecasting Multifractal Volatility," Harvard Institute of Economic Research Working Papers 1902, Harvard - Institute of Economic Research.
    20. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    21. Ole E. Barndorff-Nielsen & Elisa Nicolato & Neil Shephard, 2001. "Some recent developments in stochastic volatility modelling," Economics Papers 2001-W25, Economics Group, Nuffield College, University of Oxford.
    22. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.
    23. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
    24. Murat Körs & Mehmet Baha Karan, 2023. "Stock exchange volatility forecasting under market stress with MIDAS regression," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 295-306, January.
    25. Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
    26. Nuno Cassola & Claudio Morana, 2006. "Volatility of interest rates in the euro area: Evidence from high frequency data," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 513-528.
    27. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    28. Elena Andreou & Eric Ghysels, 2001. "Detecting Mutiple Breaks in Financial Market Volatility Dynamics," CIRANO Working Papers 2001s-65, CIRANO.
    29. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    30. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    31. Ole E. Barndorff-Nielsen & Bent Nielsen & Neil Shephard & Carla Ysusi, 2002. "Measuring and forecasting financial variability using realised variance with and without a model," Economics Papers 2002-W21, Economics Group, Nuffield College, University of Oxford.
    32. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    33. Sylvain Friederich & Richard Payne, 2007. "Dealer Liquidity in an Auction Market: Evidence from the London Stock Exchange," Economic Journal, Royal Economic Society, vol. 117(522), pages 1168-1191, July.
    34. Nour Meddahi & Eric Renault, 2000. "Temporal Aggregation of Volatility Models," CIRANO Working Papers 2000s-22, CIRANO.
    35. Jarl G. Kallberg & Paolo Pasquariello, 2005. "An Examination of the Asian Crisis: Regime Shifts in Currency and Equity Markets," The Journal of Business, University of Chicago Press, vol. 78(1), pages 169-212, January.
    36. Barndorff-Nielsen, Ole E. & Shephard, Neil, 2006. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 217-252.
    37. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, April.
    38. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    39. Mapa, Dennis S., 2003. "A Range-Based GARCH Model for Forecasting Volatility," MPRA Paper 21323, University Library of Munich, Germany.
    40. Ole E. Barndorff-Nielsen & Neil Shephard, 2001. "Realised power variation and stochastic volatility models," Economics Papers 2001-W18, Economics Group, Nuffield College, University of Oxford.
    41. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    42. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    43. John W. Galbraith & Victoria Zinde-Walsh, 2000. "Properties of Estimates of Daily GARCH Parameters Based on Intra-Day Observations," Econometric Society World Congress 2000 Contributed Papers 1800, Econometric Society.
    44. Mr. Armando Méndez Morales & Miss Liliana B Schumacher, 2003. "Market Volatility As a Financial Soundness Indicator: An Application to Israel," IMF Working Papers 2003/047, International Monetary Fund.
    45. Barucci, Emilio & Reno, Roberto, 2002. "On measuring volatility and the GARCH forecasting performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 12(3), pages 183-200, July.
    46. van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    47. Christian Bontemps & Nour Meddahi, 2005. "Testing normality: a GMM approach," Post-Print hal-02875105, HAL.
    48. Gerhard, Frank & Hautsch, Nikolaus, 2002. "Volatility estimation on the basis of price intensities," Journal of Empirical Finance, Elsevier, vol. 9(1), pages 57-89, January.
    49. Claudio Morana, 2004. "Frequency domain principal components estimation of fractionally cointegrated processes," Applied Economics Letters, Taylor & Francis Journals, vol. 11(13), pages 837-842.
    50. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," CIRANO Working Papers 2004s-19, CIRANO.
    51. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    52. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2004. "Analytical Evaluation Of Volatility Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(4), pages 1079-1110, November.
    53. Pascual, Lorenzo & Romo, Juan & Ruiz Ortega, Esther, 2000. "Forecasting returns and volatilities in GARCH processes using the bootstrap," DES - Working Papers. Statistics and Econometrics. WS 10059, Universidad Carlos III de Madrid. Departamento de Estadística.
    54. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    55. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    56. Christian Schittenkopf & Peter Tino & Georg Dorffner, 2002. "The benefit of information reduction for trading strategies," Applied Economics, Taylor & Francis Journals, vol. 34(7), pages 917-930.
    57. Elena Andreou & Eric Ghysels, 2003. "Test for Breaks in the Conditional Co-Movements of Asset Returns," University of Cyprus Working Papers in Economics 3-2003, University of Cyprus Department of Economics.
    58. John Cotter, 2011. "Uncovering Long Memory in High Frequency UK Futures," Papers 1103.5651, arXiv.org.
    59. Brusco, Sandro & Manzano, Carolina & Tapia, Mikel, 2003. "Price discovery in the pre-opening period. theory and evidence from the madrid stock exchange," DEE - Working Papers. Business Economics. WB wb035814, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    60. Moosa, Imad A. & Bollen, Bernard, 2002. "A benchmark for measuring bias in estimated daily value at risk," International Review of Financial Analysis, Elsevier, vol. 11(1), pages 85-100.
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    63. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    64. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    65. Laurini, Márcio Poletti & Portugal, Marcelo Savino, 2004. "Long memory in the R$ / US$ exchange rate: A robust analysis," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 24(1), May.
    66. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    67. GARCIA, René & RENAULT, Éric, 2000. "Latent Variable Models for Stochastic Discount Factors," Cahiers de recherche 2000-01, Universite de Montreal, Departement de sciences economiques.
    68. Veiga, Helena, 2006. "Volatility forecasts: a continuous time model versus discrete time models," DES - Working Papers. Statistics and Econometrics. WS ws062509, Universidad Carlos III de Madrid. Departamento de Estadística.
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    70. Christodoulakis, George A. & Satchell, Stephen E., 2002. "Correlated ARCH (CorrARCH): Modelling the time-varying conditional correlation between financial asset returns," European Journal of Operational Research, Elsevier, vol. 139(2), pages 351-370, June.
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    1. Takaishi, Tetsuya, 2018. "Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 139-154.
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    4. Cotter, John, 2004. "Varying the VaR for Unconditional and Conditional Environments," MPRA Paper 3483, University Library of Munich, Germany.
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    6. Mihaela Craioveanu & Eric Hillebrand, 2012. "Why It Is Ok To Use The Har-Rv(1,5,21) Model," Working Papers 1201, University of Central Missouri, Department of Economics & Finance, revised Aug 2012.
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    9. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
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    1. Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas, 2015. "Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 560-573, November.
    2. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper 96276, University Library of Munich, Germany.
    3. Broto, Carmen & Ruiz Ortega, Esther, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. 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.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
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    7. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
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    26. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
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    34. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    35. Mofleh Alshogeathri & Jamel Jouini, 2017. "Linkages Between Equity and Global Food Markets: New Evidence from Including Structural Changes," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(3), pages 166-198, June.
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    38. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    39. Axel Grossmann & Emiliano Giudici & Marc Simpson, 2014. "Euro conversion and return dynamics of European financial markets: a frequency domain approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(1), pages 1-26, January.
    40. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    41. Kuo, Chen-Yin, 2016. "Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory," Economic Modelling, Elsevier, vol. 52(PB), pages 772-789.
    42. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
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    45. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
    46. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    47. 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.
    48. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
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    51. Wang, Lu & Zhao, Chenchen & Liang, Chao & Jiu, Song, 2022. "Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 48(C).
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    1. Ralf Becker & Adam Clements, 2007. "Are combination forecasts of S&P 500 volatility statistically superior?," NCER Working Paper Series 17, National Centre for Econometric Research.
    2. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    3. Elisa Alòs & Maria Elvira Mancino & Tai-Ho Wang, 2019. "Volatility and volatility-linked derivatives: estimation, modeling, and pricing," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 321-349, December.
    4. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    5. Aldrich, Eric M. & Heckenbach, Indra & Laughlin, Gregory, 2016. "A compound duration model for high-frequency asset returns," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 105-128.
    6. Karthik Raju & Saravanan Rangaswamy, 2017. "Forecasting volatility in the Indian equity market using return and range-based models," Applied Economics, Taylor & Francis Journals, vol. 49(49), pages 5027-5039, October.
    7. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    8. Selma Chaker & Nour Meddahi, 2013. "A Distributional Approach to Realized Volatility," Staff Working Papers 13-49, Bank of Canada.
    9. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
    10. Amir Safari & Detlef Seese, 2010. "Behavior of realized volatility and correlation in exchange markets," International Econometric Review (IER), Econometric Research Association, vol. 2(2), pages 73-96, September.
    11. Becker, Ralf & Clements, Adam E. & White, Scott I., 2007. "Does implied volatility provide any information beyond that captured in model-based volatility forecasts?," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2535-2549, August.
    12. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
    13. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
    14. Maria Elvira Mancino & Simona Sanfelici, 2011. "Estimation of Quarticity with High Frequency Data," Working Papers - Mathematical Economics 2011-06, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, revised Jan 2012.
    15. Daniel Djupsjobacka, 2010. "Implications of market microstructure for realized variance measurement," The European Journal of Finance, Taylor & Francis Journals, vol. 16(1), pages 27-43.
    16. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
    17. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    18. Sébastien Laurent & Jeroen V. K. Rombouts & Francesco Violante, 2012. "On the forecasting accuracy of multivariate GARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 934-955, September.
    19. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
    20. Ai-ru (Meg) Cheng & Kuntal Das & Takeshi Shimatani, 2013. "Central Bank Intervention and Exchange Rate Volatility: Evidence from Japan Using Realized Volatility," Working Papers in Economics 13/19, University of Canterbury, Department of Economics and Finance.
    21. Ingmar Nolte & Valeri Voev, 2008. "Estimating High-Frequency Based (Co-) Variances: A Unified Approach," CREATES Research Papers 2008-31, Department of Economics and Business Economics, Aarhus University.
    22. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    23. Eugenie Hol & Siem Jan Koopman, 2002. "Stock Index Volatility Forecasting with High Frequency Data," Tinbergen Institute Discussion Papers 02-068/4, Tinbergen Institute.
    24. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    25. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
    26. Becker, Ralf & Clements, Adam E. & McClelland, Andrew, 2009. "The jump component of S&P 500 volatility and the VIX index," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1033-1038, June.
    27. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2008. "A multivariate integer count hurdle model: theory and application to exchange rate dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 31-48, Springer.
    28. Becker, Ralf & Clements, Adam E. & White, Scott I., 2006. "On the informational efficiency of S&P500 implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 17(2), pages 139-153, August.
    29. Antonakakis, Nikolaos & Darby, Julia, 2012. "Forecasting Volatility in Developing Countries' Nominal Exchange Returns," MPRA Paper 40875, University Library of Munich, Germany.
    30. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    31. Mancino, M.E. & Sanfelici, S., 2008. "Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2966-2989, February.
    32. E. C. Brechmann & M. Heiden & Y. Okhrin, 2018. "A multivariate volatility vine copula model," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 281-308, April.
    33. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.
    34. Gang-Zhi Fan & Zsuzsa Huszár & Weina Zhang, 2013. "The Relationships between Real Estate Price and Expected Financial Asset Risk and Return: Theory and Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 46(4), pages 568-595, May.
    35. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018.
    36. Roland Füss & Ferdinand Mager & Michael Stein & Lu Zhao, 2018. "Financial crises, price discovery, and information transmission: a high-frequency perspective," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 333-365, November.
    37. Scott I. White & Adam E. Clements & Stan Hurn, 2004. "Discretised Non-Linear Filtering for Dynamic Latent Variable Models: with Application to Stochastic Volatility," Econometric Society 2004 Australasian Meetings 46, Econometric Society.
    38. Adam Clements & Annastiina Silvennoinen, 2009. "On the economic benefit of utility based estimation of a volatility model," NCER Working Paper Series 44, National Centre for Econometric Research.
    39. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.
    40. Su, Fei & Zhang, Jingjing, 2018. "Global price discovery in the Australian dollar market and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 48(C), pages 35-55.
    41. Dimpfl, Thomas & Peter, Franziska J., 2021. "Nothing but noise? Price discovery across cryptocurrency exchanges," Journal of Financial Markets, Elsevier, vol. 54(C).
    42. Georgios Chortareas & John Nankervis & Ying Jiang, 2007. "Forecasting Exchange Rate Volatility with High Frequency Data: Is the Euro Different?," Money Macro and Finance (MMF) Research Group Conference 2006 79, Money Macro and Finance Research Group.
    43. Scott I White & Ralf Becker & Adam E Clements, 2004. "Forward looking information in S&P 500 options," Econometric Society 2004 Australasian Meetings 233, Econometric Society.
    44. Adam Clements & Ralf Becker, 2009. "A nonparametric approach to forecasting realized volatility," NCER Working Paper Series 43, National Centre for Econometric Research.
    45. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
    46. Linlan Xiao & Vigdis Boasson & Sergey Shishlenin & Victoria Makushina, 2018. "Volatility forecasting: combinations of realized volatility measures and forecasting models," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1428-1441, March.
    47. Wang, Yuanfang & Roberts, Matthew C., 2005. "Realized Volatility in the Agricultural Futures Market," 2005 Annual meeting, July 24-27, Providence, RI 19211, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    48. A. Saichev & D. Sornette, 2014. "A simple microstructure return model explaining microstructure noise and Epps effects," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(06), pages 1-36.
    49. André Schöne, 2010. "Zum Informationsgehalt der Volatilitätsindizes VDAX und VDAX-New der Deutsche Börse AG," Schmalenbach Journal of Business Research, Springer, vol. 62(6), pages 625-661, September.
    50. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).

  49. Torben G. Anderson & Tim Bollerslev & Ashish Das, 1998. "Testing for Market Microstructure Effects in Intraday Volatility: A Reassessment of the Tokyo FX Experiment," NBER Working Papers 6666, National Bureau of Economic Research, Inc.

    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    3. Corbet, Shaen & Dunne, John James & Larkin, Charles, 2019. "Quantitative easing announcements and high-frequency stock market volatility: Evidence from the United States," Research in International Business and Finance, Elsevier, vol. 48(C), pages 321-334.
    4. Imen Kouki & Hélène Raymond, 2006. "Analyse microstructurelle du comportement du teneur de marché des changes : étude intra-journalière de l'activité d'un teneur de marché tunisien," EconomiX Working Papers 2006-14, University of Paris Nanterre, EconomiX.

  50. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.

    Cited by:

    1. Wai Yan Cheng & Michael Chak Sham Wong & Clement Yuk Pang Wong, 2003. "Market risk management of banks: implications from the accuracy of Value-at-Risk forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 23-33.
    2. Klaassen, F.J.G.M., 1998. "Improving Garch Volatility Forecasts," Discussion Paper 1998-52, Tilburg University, Center for Economic Research.
    3. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2017. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," MPRA Paper 80435, University Library of Munich, Germany.
    4. Luwen Zhang & Li Wang, 2023. "Generalized Method of Moments Estimation of Realized Stochastic Volatility Model," JRFM, MDPI, vol. 16(8), pages 1-12, August.
    5. PERRON, Benoît, 1999. "Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off," Cahiers de recherche 9901, Universite de Montreal, Departement de sciences economiques.
    6. Capobianco, Enrico, 2003. "Empirical volatility analysis: feature detection and signal extraction with function dictionaries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 319(C), pages 495-518.
    7. Oliver Pfante & Nils Bertschinger, 2019. "Volatility Inference And Return Dependencies In Stochastic Volatility Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-44, May.
    8. Mr. Torbjorn I. Becker & Mr. Amadou N Sy, 2005. "Were Bid-Ask Spreads in the Foreign Exchange Market Excessive During the Asian Crisis?," IMF Working Papers 2005/034, International Monetary Fund.
    9. Chrétien, Stéphane & Ortega, Juan-Pablo, 2014. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 210-236.
    10. Vuorenmaa, Tommi A., 2005. "A wavelet analysis of scaling laws and long-memory in stock market volatility," Bank of Finland Research Discussion Papers 27/2005, Bank of Finland.
    11. Peter F. Christoffersen & Francis X. Diebold, 1998. "How Relevant is Volatility Forecasting for Financial Risk Management?," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-080, New York University, Leonard N. Stern School of Business-.
    12. Rosenow, Bernd, 2008. "Determining the optimal dimensionality of multivariate volatility models with tools from random matrix theory," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 279-302, January.
    13. Enrico Capobianco, 1999. "Statistical Analysis of Financial Volatility by Wavelet Shrinkage," Methodology and Computing in Applied Probability, Springer, vol. 1(4), pages 423-443, December.
    14. Peter R. Hansen & Asger Lunde, 2010. "Estimating the Persistence and the Autocorrelation Function of a Time Series that is Measured with Error," CREATES Research Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    15. Martens, Martin & van Dijk, Dick & de Pooter, Michiel, 2009. "Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements," International Journal of Forecasting, Elsevier, vol. 25(2), pages 282-303.
    16. Martin Anderson & Shan Chen & James Hacking & Marc R Lieberman & Mark Lundin & Vaida Maleckaite & Allan Martin & Ryan Parham & Mark Steed, 2014. "Modern pension fund diversification," Journal of Asset Management, Palgrave Macmillan, vol. 15(3), pages 205-217, June.
    17. Ceci, Vladimiro & Manganelli, Simone & Vecchiato, Walter, 2002. "Sensitivity analysis of volatility: a new tool for risk management," Working Paper Series 194, European Central Bank.
    18. Eskandar A. Tooma, 2003. "Modeling and Forecasting Egyptian Stock Market Volatility Before and After Price Limits," Working Papers 0310, Economic Research Forum, revised Apr 2003.
    19. Lee, Gabriel S. & Boss, Michael & Klisz, Chris, 2001. "Empirical Performance of the Czech and Hungarian Index Options under Jump," Economics Series 91, Institute for Advanced Studies.
    20. St'ephane Chr'etien & Juan-Pablo Ortega, 2011. "Multivariate GARCH estimation via a Bregman-proximal trust-region method," Papers 1101.5475, arXiv.org.
    21. Kevin Daly, 2011. "An Overview of the Determinants of Financial Volatility: An Explanation of Measuring Techniques," Modern Applied Science, Canadian Center of Science and Education, vol. 5(5), pages 1-46, October.
    22. Maher Asal, 2012. "Has the Euro Boosted Equity Markets in the Euro Area?," Journal of Business Administration Research, Journal of Business Administration Research, Sciedu Press, vol. 1(2), pages 51-70, October.

  51. Torben G. Andersen & Tim Bollerslev, 1996. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," NBER Working Papers 5752, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ambrogio Cesa-Bianchi & M. Hashem Pesaran & Alessandro Rebucci, 2014. "Uncertainty and Economic Activity: A Global Perspective," CESifo Working Paper Series 4736, CESifo.
    2. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    3. Nasr, Adnen Ben & Lux, Thomas & Ajm, Ahdi Noomen & Gupta, Rangan, 2014. "Forecasting the volatility of the dow jones islamic stock market index: Long memory vs. regime switching," Economics Working Papers 2014-07, Christian-Albrechts-University of Kiel, Department of Economics.
    4. Jurado Pedroza Wilfrido, 2021. "Around-the-Clock USD/MXN Volatility: Macroeconomic Announcement Spillovers and FX Market Intervention Mechanisms," Working Papers 2021-05, Banco de México.
    5. Evans, Kevin P. & Speight, Alan E.H., 2010. "Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility," Research in International Business and Finance, Elsevier, vol. 24(1), pages 82-101, January.
    6. Liesenfeld, Roman, 1997. "Trading volume and the short and long-run components of volatility," Tübinger Diskussionsbeiträge 102, University of Tübingen, School of Business and Economics.
    7. VEREDAS, David & RODRIGUEZ-POO, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," LIDAM Discussion Papers CORE 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    9. Phuong Pham, Thu & Joakim Westerholm, P., 2013. "An international trend in market design: Endogenous effects of limit order book transparency on volatility, spreads, depth and volume," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 202-223.
    10. Gordon R. Richards, 2004. "A fractal forecasting model for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(8), pages 586-601.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    12. Kyongwook Choi & Wei-Choun Yu & Eric Zivot, 2008. "Long Memory versus Structural Breaks in Modeling and Forecasting Realized Volatility," Working Papers UWEC-2008-20-FC, University of Washington, Department of Economics.
    13. Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
    14. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    15. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    16. Grace Lee Ching Yap, 2020. "Optimal Filter Approximations for Latent Long Memory Stochastic Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 547-568, August.
    17. Broto, Carmen & Ruiz Ortega, Esther, 2002. "Estimation methods for stochastic volatility models: a survey," DES - Working Papers. Statistics and Econometrics. WS ws025414, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    19. Pierre Perron & Zhongjun Qu, 2008. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Boston University - Department of Economics - Working Papers Series wp2008-004, Boston University - Department of Economics.
    20. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    21. Pedro J. F. de Lima & Michelle L. Barnes, 2000. "Modeling Financial Volatility: Extreme Observations, Nonlinearities and Nonstationarities," School of Economics and Public Policy Working Papers 2000-05, University of Adelaide, School of Economics and Public Policy.
    22. Mulligan, Robert F. & Koppl, Roger, 2011. "Monetary policy regimes in macroeconomic data: An application of fractal analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(2), pages 201-211, May.
    23. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    24. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions," NBER Working Papers 28570, National Bureau of Economic Research, Inc.
    25. Kousik Guhathakurta & Sharad Nath Bhattacharya & Mousumi Bhattacharya, 2012. "Exploring Presence of Long Memory in Emerging and Developed Stock Markets," Working papers 107, Indian Institute of Management Kozhikode.
    26. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 225-241, April.
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    Cited by:

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    6829. Tao Xiong & Wendong Zhang & Fangxiao Zhao, 2023. "When China strikes: Quantifying Australian companies' stock price responses to China's trade restrictions," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 67(4), pages 636-671, October.
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    6837. Adrian Grosanu & Paula Ramona Rachisan, 2008. "The Implementation Of Profit Centres Inside An Economic Entity," JOURNAL STUDIA UNIVERSITATIS BABES-BOLYAI NEGOTIA, Babes-Bolyai University, Faculty of Business.
    6838. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
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    6841. Morema, Kgotso & Bonga-Bonga, Lumengo, 2018. "The impact of oil and gold price fluctuations on the South African equity market: volatility spillovers and implications for portfolio management," MPRA Paper 87637, University Library of Munich, Germany.
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    6855. Matei, Marius, 2012. "Perspectives on risk measurement: a critical assessment of PC-GARCH against the main volatility forecasting models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 95-115, March.
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    6857. Mário Correia Fernandes & José Carlos Dias & João Pedro Vidal Nunes, 2024. "Performance comparison of alternative stochastic volatility models and its determinants in energy futures: COVID‐19 and Russia–Ukraine conflict features," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 343-383, March.
    6858. Dominique Guegan & Zhiping Lu, 2007. "A note on self-similarity for discrete time series," Post-Print halshs-00187910, HAL.
    6859. Vipul Kumar Singh, 2013. "Effectiveness of volatility models in option pricing: evidence from recent financial upheavals," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 10(3), pages 352-375, October.
    6860. Debalke, Negash Mulatu, 2023. "Examining volatility and spillover effects between markets for sovereign bonds of African countries and the world’s long term interest rate," MPRA Paper 117491, University Library of Munich, Germany.
    6861. Liu, Min & Lee, Chien-Chiang, 2022. "Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS," Resources Policy, Elsevier, vol. 76(C).
    6862. Pilar Abad & Alfonso Novales, 2002. "Volatility Transmission acros the Term Structure of Swap Markets: International Evidence," Documentos de Trabajo del ICAE 0220, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    6863. Luigi Aldieri & Alessandra Amendola & Vincenzo Candila, 2023. "The Impact of ESG Scores on Risk Market Performance," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
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    6865. Lee, Chia-Hao & Chou, Pei-I, 2019. "Information dissemination and investors’ sensitivity," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 242-250.
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    6867. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.
    6868. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    6869. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    6870. Hassan, M. Kabir & Kamran, Muhammad & Djajadikerta, Hadrian Geri & Choudhury, Tonmoy, 2022. "Search for safe havens and resilience to global financial volatility: Response of GCC equity indexes to GFC and Covid-19," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
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    6872. Paravee Maneejuk & Nootchanat Pirabun & Suphawit Singjai & Woraphon Yamaka, 2021. "Currency Hedging Strategies Using Histogram-Valued Data: Bivariate Markov Switching GARCH Models," Mathematics, MDPI, vol. 9(21), pages 1-20, November.
    6873. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.
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    6875. Wen Zhang & Zhibin Wu, 2022. "Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 615-632, April.
    6876. Abdelhakim Aknouche & Eid Al-Eid & Nacer Demouche, 2018. "Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 485-511, October.
    6877. Racicot, François-Éric & Théoret, Raymond, 2016. "Macroeconomic shocks, forward-looking dynamics, and the behavior of hedge funds," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 41-61.
    6878. Baillie, R. & Chung, C. & Tieslau, M., 1992. "The Long Memory and Variability of Inflation : A Reappraisal of the Friedman Hypothesis," Discussion Paper 1992-46, Tilburg University, Center for Economic Research.
    6879. Klein, Tony & Walther, Thomas, 2016. "Oil price volatility forecast with mixture memory GARCH," Energy Economics, Elsevier, vol. 58(C), pages 46-58.
    6880. Botshekan , Mohammad Hashem & Takaloo , Amir & H. soureh , Reza & Abdollahi Poor , Mohammad Sadegh, 2021. "Global Economic Policy Uncertainty (GEPU) and Non-Performing Loans (NPL) in Iran's Banking System: Dynamic Correlation using the DCC-GARCH Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 187-212, June.
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    6883. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.
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    6885. Alin Marius ANDRIEŞ & Iulian IHNATOV & Nicu SPRINCEAN, 2017. "Do Seasonal Anomalies Still Exist In Central And Eastern European Countries? A Conditional Variance Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 60-83, December.
    6886. Green, Christopher J. & Maggioni, Paolo & Murinde, Victor, 2000. "Regulatory lessons for emerging stock markets from a century of evidence on transactions costs and share price volatility in the London Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 24(4), pages 577-601, April.
    6887. Michael P. Hughes & Karl Rogers, 2016. "Zero Lower Bound Monetary Policy’s Effect on Financial Asset’s Correlations," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(2), pages 151-170, May.
    6888. Butler, K. C. & Joaquin, D. C., 2002. "Are the gains from international portfolio diversification exaggerated? The influence of downside risk in bear markets," Journal of International Money and Finance, Elsevier, vol. 21(7), pages 981-1011, December.
    6889. Degiannakis, Stavros & Floros, Christos, 2010. "VIX Index in Interday and Intraday Volatility Models," MPRA Paper 96304, University Library of Munich, Germany.
    6890. Harold Ngalawa & Adebayo Augustine Kutu, 2017. "Modelling exchange rate variations and global shocks in Brazil," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 35(1), pages 73-95.
    6891. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
    6892. Brenner, Menachem & Pasquariello, Paolo & Subrahmanyam, Marti, 2009. "On the Volatility and Comovement of U.S. Financial Markets around Macroeconomic News Announcements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(6), pages 1265-1289, December.
    6893. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.
    6894. Jin, Hyun Joung & Cho, Guedae & Koo, Won W., 2004. "Third-Country Effects on the Market Shares of U.S. Wheat in Asian Countries," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 36(3), pages 1-17, December.
    6895. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6896. Isha Narula, 2016. "Dynamics of volatility behaviour and transmission: evidences from BRICS countries," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(1), pages 31-51, March.
    6897. Mitchell, Jason & Izan, H.Y., 2006. "Clustering and psychological barriers in exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 318-344, October.
    6898. Komunjer, Ivana, 2001. "Consistent Estimation for Aggregated GARCH," University of California at San Diego, Economics Working Paper Series qt1fp2v3q7, Department of Economics, UC San Diego.
    6899. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.
    6900. Hu Liang & Shin Yongcheol, 2008. "Optimal Test for Markov Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-27, September.
    6901. Bomfim, Antulio N., 2003. "Pre-announcement effects, news effects, and volatility: Monetary policy and the stock market," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 133-151, January.
    6902. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.
    6903. Li, Yong & Huang, Wei-Ping & Zhang, Jie, 2013. "Forecasting volatility in the Chinese stock market under model uncertainty," Economic Modelling, Elsevier, vol. 35(C), pages 231-234.
    6904. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
    6905. Boppana Nagarjuna & Varadi Vijay Kumar, 2010. "Heat waves or Meteor showers: Empirical evidence from the stock markets," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 53(2), pages 57-74.
    6906. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.
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    6908. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    6909. Jesús Téllez Gaytán & Carlos A. Martínez, 2005. "Volatility Co-Movement Among Latin American Stock Exchanges: Bad Times Vs. Good Times," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 4(4), pages 387-426, Diciembre.
    6910. Adlai Fisher & Laurent Calvet & Benoit Mandelbrot, 1997. "Multifractality of Deutschemark/US Dollar Exchange Rates," Cowles Foundation Discussion Papers 1166, Cowles Foundation for Research in Economics, Yale University.
    6911. Dicle, Mehmet F. & Levendis, John, 2011. "Greek market efficiency and its international integration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(2), pages 229-246, April.
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    6913. Khim-Sen Liew & Kian-Ping Lim & Chee-Keong Choong, 2003. "On The Forecastability Of Asean-5 Stock Markets Returns Using Time Series Models," Finance 0307012, University Library of Munich, Germany.
    6914. Sclip, Alex & Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2016. "Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets," Review of Financial Economics, Elsevier, vol. 31(C), pages 34-44.
    6915. Gagan Deep Sharma & Namish Mishra, 2015. "Return Linkages and Volatility Spillover Effect Between Stock Markets and Currency Markets," Review of Market Integration, India Development Foundation, vol. 7(3), pages 175-197, December.
    6916. Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.
    6917. Nikolaos A. Kyriazis, 2021. "The Nexus of Sophisticated Digital Assets with Economic Policy Uncertainty: A Survey of Empirical Findings and an Empirical Investigation," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    6918. Giuseppe Storti & Chao Wang, 2023. "Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1648-1663, November.
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    6930. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.

Articles

  1. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.

    Cited by:

    1. Boudt, Kris & Dragun, Kirill & Sauri, Orimar & Vanduffel, Steven, 2023. "ETF Basket-Adjusted Covariance estimation," Journal of Econometrics, Elsevier, vol. 235(2), pages 1144-1171.
    2. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    3. Kirill Dragun & Kris Boudt & Orimar Sauri & Steven Vanduffel, 2021. "Beta-Adjusted Covariance Estimation," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1010, Ghent University, Faculty of Economics and Business Administration.
    4. Li, Yuan & Pakkanen, Mikko S. & Veraart, Almut E.D., 2023. "Limit theorems for the realised semicovariances of multivariate Brownian semistationary processes," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 202-231.
    5. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
    6. Asgar Ali & K. N. Badhani, 2023. "Downside risk matters once the lottery effect is controlled: explaining risk–return relationship in the Indian equity market," Journal of Asset Management, Palgrave Macmillan, vol. 24(1), pages 27-43, February.
    7. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    8. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Petropoulou, Athina & Sivaprasad, Sheeja, 2023. "The impact of the Russian-Ukrainian war on global financial markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
    9. Christis Katsouris, 2021. "Optimal Portfolio Choice and Stock Centrality for Tail Risk Events," Papers 2112.12031, arXiv.org.
    10. Chanatásig-Niza, Evelyn & Ciarreta, Aitor & Zarraga, Ainhoa, 2022. "A volatility spillover analysis with realized semi(co)variances in Australian electricity markets," Energy Economics, Elsevier, vol. 111(C).
    11. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    12. Neil Shephard, 2020. "An estimator for predictive regression: reliable inference for financial economics," Papers 2008.06130, arXiv.org.
    13. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.
    14. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.

  2. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.

    Cited by:

    1. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    2. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    3. Manabu Asai & Mike K. P. So, 2021. "Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(3), pages 271-294, May.
    4. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    5. Asai Manabu & So Mike K. P., 2023. "Realized BEKK-CAW Models," Journal of Time Series Econometrics, De Gruyter, vol. 15(1), pages 49-77, January.
    6. Marius Matei & Xari Rovira & Núria Agell, 2019. "Bivariate Volatility Modeling with High-Frequency Data," Econometrics, MDPI, vol. 7(3), pages 1-15, September.
    7. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    8. Dey, Asim K. & Hoque, G.M. Toufiqul & Das, Kumer P. & Panovska, Irina, 2022. "Impacts of COVID-19 local spread and Google search trend on the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    9. Anke D. Leroux & Vance L. Martin & Kathryn A. St. John, 2022. "Modeling time varying risk of natural resource assets: Implications of climate change," Quantitative Economics, Econometric Society, vol. 13(1), pages 225-257, January.
    10. Yu‐Sheng Lai, 2023. "Optimal futures hedging by using realized semicovariances: The information contained in signed high‐frequency returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(5), pages 677-701, May.

  3. Bollerslev, Tim & Li, Sophia Zhengzi & Zhao, Bingzhi, 2020. "Good Volatility, Bad Volatility, and the Cross Section of Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(3), pages 751-781, May.

    Cited by:

    1. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    2. Jozef Barunik & Josef Kurka, 2021. "Risks of heterogeneously persistent higher moments," Papers 2104.04264, arXiv.org, revised Mar 2024.
    3. Luo, Xin & Tao, Yunqing & Zou, Kai, 2022. "A new measure of realized volatility: Inertial and reverse realized semivariance," Finance Research Letters, Elsevier, vol. 47(PA).
    4. Gaoxiu Qiao & Gongyue Jiang, 2023. "VIX futures pricing based on high‐frequency VIX: A hybrid approach combining SVR with parametric models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1238-1260, September.
    5. Chen, Yan & Qiao, Gaoxiu & Zhang, Feipeng, 2022. "Oil price volatility forecasting: Threshold effect from stock market volatility," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    6. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    7. Wang, Qingxia & Faff, Robert & Zhu, Min, 2022. "Realized moments and the cross-sectional stock returns around earnings announcements," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 408-427.
    8. Baur, Dirk G., 2022. "The Anna Karenina principle and stock prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    9. Yuewen Xiao & Xiangkang Yin & Jing Zhao, 2020. "Jumps, News, And Subsequent Return Dynamics: An Intraday Study," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 705-731, August.
    10. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    11. Xingguo Luo & Xiaoli Yu & Shihua Qin & Qi Xu, 2020. "Option trading and the cross‐listed stock returns: Evidence from Chinese A–H shares," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1665-1690, November.
    12. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
    13. Li Liu & Yudong Wang, 2021. "Forecasting aggregate market volatility: The role of good and bad uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 40-61, January.
    14. Bo Yu & Bruce Mizrach & Norman R. Swanson, 2020. "New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section," Econometrics, MDPI, vol. 8(2), pages 1-52, May.
    15. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    16. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    17. Chen, Xi & Wang, Junbo & Wu, Chunchi, 2022. "Jump and volatility risk in the cross-section of corporate bond returns," Journal of Financial Markets, Elsevier, vol. 60(C).
    18. Zhiyuan Pan & Yudong Wang & Li Liu, 2021. "Realized bipower variation, jump components, and option valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1933-1958, December.
    19. Zhang, Zehua & Zhao, Ran, 2023. "Good volatility, bad volatility, and the cross section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 89(C).
    20. Annaert, Jan & De Ceuster, Marc & Van Cappellen, Jef, 2023. "Can average skewness really predict financial returns? The euro area case," Finance Research Letters, Elsevier, vol. 52(C).
    21. Wang, Feifei & Yan, Xuemin Sterling, 2021. "Downside risk and the performance of volatility-managed portfolios," Journal of Banking & Finance, Elsevier, vol. 131(C).
    22. Seema REHMAN & Saqib SHARIF & Wali ULLAH, 2023. "Relative Signed Jump and Future Stock Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 25-45, March.
    23. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
    24. Lee, Suzanne S., 2023. "The role of idiosyncratic jumps in stock markets," Journal of Financial Markets, Elsevier, vol. 64(C).
    25. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.
    26. 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).
    27. James W. Kolari & Jianhua Z. Huang & Wei Liu & Huiling Liao, 2022. "Further Tests of the ZCAPM Asset Pricing Model," JRFM, MDPI, vol. 15(3), pages 1-23, March.

  4. Bollerslev, Tim & Meddahi, Nour & Nyawa, Serge, 2019. "High-dimensional multivariate realized volatility estimation," Journal of Econometrics, Elsevier, vol. 212(1), pages 116-136.

    Cited by:

    1. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org.
    2. Gaoxiu Qiao & Yangli Cao & Feng Ma & Weiping Li, 2023. "Liquidity and realized covariance forecasting: a hybrid method with model uncertainty," Empirical Economics, Springer, vol. 64(1), pages 437-463, January.
    3. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    4. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    5. Qinkai Chen & Christian-Yann Robert, 2021. "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers 2112.09015, arXiv.org, revised Dec 2021.
    6. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    7. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.

  5. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    See citations under working paper version above.
  6. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    See citations under working paper version above.
  7. Tim Bollerslev & Jia Li & Yuan Xue, 2018. "Volume, Volatility, and Public News Announcements," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2005-2041.
    See citations under working paper version above.
  8. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.

    Cited by:

    1. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    2. Ilze Kalnina & Dacheng Xiu, 2017. "Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 384-396, January.
    3. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2019. "Cross-Sectional Dispersion of Risk in Trading Time," NBER Working Papers 26329, National Bureau of Economic Research, Inc.
    4. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    5. Lee, Suzanne S. & Wang, Minho, 2019. "The impact of jumps on carry trade returns," Journal of Financial Economics, Elsevier, vol. 131(2), pages 433-455.
    6. Mohamed Arouri & Oussama M’saddek & Kuntara Pukthuanthong, 2017. "Jump risk premia across major international equity markets," Post-Print hal-02083723, HAL.
    7. Yang, Xiye, 2020. "Time-invariant restrictions of volatility functionals: Efficient estimation and specification tests," Journal of Econometrics, Elsevier, vol. 215(2), pages 486-516.
    8. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2017. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Working Papers 2017-10, University of Tasmania, Tasmanian School of Business and Economics.
    9. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    10. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    11. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    12. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    13. Johnson, James A. & Medeiros, Marcelo C. & Paye, Bradley S., 2022. "Jumps in stock prices: New insights from old data," Journal of Financial Markets, Elsevier, vol. 60(C).
    14. Leong, Minhao & Kwok, Simon, 2023. "The pricing of jump and diffusive risks in the cross-section of cryptocurrency returns," Journal of Empirical Finance, Elsevier, vol. 74(C).
    15. Hollstein, Fabian & Wese Simen, Chardin, 2020. "Variance risk: A bird’s eye view," Journal of Econometrics, Elsevier, vol. 215(2), pages 517-535.
    16. Srivastava, Pranjal & Jacob, Joshy, 2022. "Arbitrage constraints and behaviour of volatility components: Evidence from a natural experiment," IIMA Working Papers WP 2022-10-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    17. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Conditional Factor Models with Instrumental and Idiosyncratic Betas," Departmental Working Papers 201711, Rutgers University, Department of Economics.
    18. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2019. "Does Index Arbitrage Distort the Market Reaction to Shocks?," CERGE-EI Working Papers wp651, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    19. Jan Novotný & Giovanni Urga, 2018. "Testing for Co-jumps in Financial Markets," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 118-128.
    20. Liu, Xiaoqun & Zhang, Yuchen & Tian, Mengqiao & Chao, Youcong, 2023. "Financial distress and jump tail risk: Evidence from China's listed companies," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 316-336.
    21. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
    22. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2020. "Beta uncertainty," Journal of Banking & Finance, Elsevier, vol. 116(C).
    23. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    24. Bandi, Federico M. & Renò, Roberto, 2022. "β in the tails," Journal of Econometrics, Elsevier, vol. 227(1), pages 134-150.
    25. Zhu, Jiaqing, 2019. "External financial liabilities and real exchange rate jumps," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 202-220.
    26. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    27. Dinesh Gajurel & Mardi Dungey & Wenying Yao & Nagaratnam Jeyasreedharan, 2020. "Jump Risk in the US Financial Sector," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 331-349, September.
    28. Liyun Zhou & Chunpeng Yang, 2019. "Differences in the effects of seller-initiated versus buyer-initiated crowded trades in stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 859-890, December.
    29. Alexeev, Vitali & Dungey, Mardi & Yao, Wenying, 2017. "Time-varying continuous and jump betas: The role of firm characteristics and periods of stress," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 1-19.
    30. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    31. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    32. Gajurel, Dinesh & Chowdhury, Biplob, 2020. "Realized volatility, jump and beta: evidence from Canadian stock market," Working Papers 2020-11, University of Tasmania, Tasmanian School of Business and Economics.
    33. Wenying Yao & Mardi Dungey & Vitali Alexeev, 2020. "Modelling Financial Contagion Using High Frequency Data," The Economic Record, The Economic Society of Australia, vol. 96(314), pages 314-330, September.
    34. Liu, Jinjing, 2023. "A novel downside beta and expected stock returns," International Review of Financial Analysis, Elsevier, vol. 85(C).
    35. Patrizia Perras & Niklas Wagner, 2020. "On the pricing of overnight market risk," Empirical Economics, Springer, vol. 59(3), pages 1307-1327, September.
    36. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    37. Dinesh Gajurel & Biplob Chowdhury, 2021. "Realized Volatility, Jump and Beta: evidence from Canadian Stock Market," Applied Economics, Taylor & Francis Journals, vol. 53(55), pages 6376-6397, November.
    38. Lee, Suzanne S., 2023. "The role of idiosyncratic jumps in stock markets," Journal of Financial Markets, Elsevier, vol. 64(C).
    39. Zhang, Hao & Zhu, Jiaqing, 2022. "Does trade cause fear of appreciation?," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 68-80.
    40. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "Realized semibetas: Disentangling “good” and “bad” downside risks," Journal of Financial Economics, Elsevier, vol. 144(1), pages 227-246.

  9. Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2016. "Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1005-1025, September.
    See citations under working paper version above.
  10. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    See citations under working paper version above.
  11. Bollerslev, Tim & Xu, Lai & Zhou, Hao, 2015. "Stock return and cash flow predictability: The role of volatility risk," Journal of Econometrics, Elsevier, vol. 187(2), pages 458-471.
    See citations under working paper version above.
  12. Bollerslev, Tim & Todorov, Viktor & Xu, Lai, 2015. "Tail risk premia and return predictability," Journal of Financial Economics, Elsevier, vol. 118(1), pages 113-134.
    See citations under working paper version above.
  13. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.

    Cited by:

    1. Horvath, Jaroslav, 2019. "Isolating the disaster risk premium with equity options," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 138-148.
    2. Daly, Kevin & Batten, Jonathan A. & Mishra, Anil V. & Choudhury, Tonmoy, 2019. "Contagion risk in global banking sector," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    3. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2018. "Short-Term Market Risks Implied by Weekly Options," CREATES Research Papers 2018-08, Department of Economics and Business Economics, Aarhus University.
    4. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    5. Todorov, Viktor & Zhang, Yang, 2023. "Bias reduction in spot volatility estimation from options," Journal of Econometrics, Elsevier, vol. 234(1), pages 53-81.
    6. Nicolau, João & Rodrigues, Paulo M.M. & Stoykov, Marian Z., 2023. "Tail index estimation in the presence of covariates: Stock returns’ tail risk dynamics," Journal of Econometrics, Elsevier, vol. 235(2), pages 2266-2284.
    7. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2014. "The Risk Premia Embedded in Index Options," CREATES Research Papers 2014-56, Department of Economics and Business Economics, Aarhus University.
    8. Andersen, Torben G. & Todorov, Viktor & Ubukata, Masato, 2021. "Tail risk and return predictability for the Japanese equity market," Journal of Econometrics, Elsevier, vol. 222(1), pages 344-363.
    9. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2015. "The Pricing of Short-Term market Risk: Evidence from Weekly Options," NBER Working Papers 21491, National Bureau of Economic Research, Inc.
    10. Li, Zhenxiong & Yao, Xingzhi & Izzeldin, Marwan, 2023. "On the right jump tail inferred from the VIX market," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Todorov, Viktor, 2022. "Nonparametric jump variation measures from options," Journal of Econometrics, Elsevier, vol. 230(2), pages 255-280.
    12. Wong, Patrick, 2023. "Explaining intraday crude oil returns with higher order risk-neutral moments," Journal of Commodity Markets, Elsevier, vol. 31(C).
    13. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "The Risk Premium of Gold," Hannover Economic Papers (HEP) dp-616, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. Deniz Erdemlioglu & Christopher J. Neely & Xiye Yang, 2023. "Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications," Working Papers 2023-016, Federal Reserve Bank of St. Louis.
    15. Boswijk, H. Peter & Laeven, Roger J.A. & Yang, Xiye, 2018. "Testing for self-excitation in jumps," Journal of Econometrics, Elsevier, vol. 203(2), pages 256-266.
    16. Tim Bollerslev & Viktor Todorov & Lai Xu, 2014. "Tail Risk Premia and Return Predictability," CREATES Research Papers 2014-49, Department of Economics and Business Economics, Aarhus University.
    17. Hitesh Doshi & Hyung Joo Kim & Sang Byung Seo, 2023. "Options on Interbank Rates and Implied Disaster Risk," Finance and Economics Discussion Series 2023-054, Board of Governors of the Federal Reserve System (U.S.).
    18. Masato Ubukata, 2022. "A time-varying jump tail risk measure using high-frequency options data," Empirical Economics, Springer, vol. 63(5), pages 2633-2653, November.
    19. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Score-driven time series models with dynamic shape : an application to the Standard & Poor's 500 index," UC3M Working papers. Economics 28133, Universidad Carlos III de Madrid. Departamento de Economía.
    20. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Sonnan Chen & Yuchi Gu, 2021. "Joint estimation of volatility risk and tail risk premia with time-varying macro-state-dependent property," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1357-1397, May.
    22. Masato Ubukata, 2019. "Jump tail risk premium and predicting US and Japanese credit spreads," Empirical Economics, Springer, vol. 57(1), pages 79-104, July.
    23. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    24. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.

  14. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 633-661, June.
    See citations under working paper version above.
  15. Bollerslev, Tim & Todorov, Viktor & Li, Sophia Zhengzi, 2013. "Jump tails, extreme dependencies, and the distribution of stock returns," Journal of Econometrics, Elsevier, vol. 172(2), pages 307-324.
    See citations under working paper version above.
  16. Bollerslev, Tim & Osterrieder, Daniela & Sizova, Natalia & Tauchen, George, 2013. "Risk and return: Long-run relations, fractional cointegration, and return predictability," Journal of Financial Economics, Elsevier, vol. 108(2), pages 409-424.

    Cited by:

    1. Chi Zhang & Zhengning Pu & Qin Zhou, 2018. "Sustainable Energy Consumption in Northeast Asia: A Case from China’s Fuel Oil Futures Market," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    2. Josselin Garnier & Knut Sølna, 2018. "Option pricing under fast-varying and rough stochastic volatility," Annals of Finance, Springer, vol. 14(4), pages 489-516, November.
    3. Søren Johansen & Morten Ørregaard Nielsen, 2017. "Testing the CVAR in the fractional CVAR model," CREATES Research Papers 2017-37, Department of Economics and Business Economics, Aarhus University.
    4. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2016. "International stock market cointegration under the risk-neutral measure," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 243-255.
    5. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
    6. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2018-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    7. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2021. "Persistence in the market risk premium: evidence across countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(3), pages 413-427, July.
    8. Christian Leschinski & Michelle Voges & Philipp Sibbertsen, 2021. "Integration and Disintegration of EMU Government Bond Markets," Econometrics, MDPI, vol. 9(1), pages 1-17, March.
    9. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    10. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
    11. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
    12. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    13. 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.
    14. Haugom, Erik & Langeland, Henrik & Molnár, Peter & Westgaard, Sjur, 2014. "Forecasting volatility of the U.S. oil market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 1-14.
    15. Christensen, Bent Jesper & Varneskov, Rasmus Tangsgaard, 2017. "Medium band least squares estimation of fractional cointegration in the presence of low-frequency contamination," Journal of Econometrics, Elsevier, vol. 197(2), pages 218-244.
    16. Matteo Bonato & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2016. "Gold Futures Returns and Realized Moments: A Forecasting Experiment Using a Quantile-Boosting Approach," Working Papers 201645, University of Pretoria, Department of Economics.
    17. Ergemen, Yunus Emre & Velasco, Carlos, 2017. "Estimation of fractionally integrated panels with fixed effects and cross-section dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 248-258.
    18. Yunus Emre Ergemen & Abderrahim Taamouti, 2015. "Parametric Portfolio Policies with Common Volatility Dynamics," CREATES Research Papers 2015-41, Department of Economics and Business Economics, Aarhus University.
    19. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    20. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    21. Daniela Osterrieder & Daniel Ventosa-Santaulària & J. Eduardo Vera-Valdés, 2015. "Unbalanced Regressions and the Predictive Equation," CREATES Research Papers 2015-09, Department of Economics and Business Economics, Aarhus University.
    22. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    23. Bollerslev, Tim & Xu, Lai & Zhou, Hao, 2015. "Stock return and cash flow predictability: The role of volatility risk," Journal of Econometrics, Elsevier, vol. 187(2), pages 458-471.
    24. Niels Haldrup & Robinson Kruse, 2014. "Discriminating between fractional integration and spurious long memory," CREATES Research Papers 2014-19, Department of Economics and Business Economics, Aarhus University.
    25. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    26. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Consistent Inference for Predictive Regressions in Persistent Economic Systems," NBER Working Papers 28568, National Bureau of Economic Research, Inc.
    27. Yao, Xingzhi & Izzeldin, Marwan & Li, Zhenxiong, 2019. "Modelling systems with a mixture of I(d) and I(0) variables using the fractionally co-integrated VAR model," Economics Letters, Elsevier, vol. 181(C), pages 160-163.
    28. Tobias Adrian & Richard K. Crump & Erik Vogt, 2019. "Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds," Journal of Finance, American Finance Association, vol. 74(4), pages 1931-1973, August.
    29. Vera-Valdés, J. Eduardo, 2022. "The persistence of financial volatility after COVID-19," Finance Research Letters, Elsevier, vol. 44(C).
    30. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    31. Bechir Raggad & Elie Bouri, 2023. "Quantile Dependence between Crude Oil Returns and Implied Volatility: Evidence from Parametric and Nonparametric Tests," Mathematics, MDPI, vol. 11(3), pages 1-23, January.
    32. Javier Haulde & Morten Ørregaard Nielsen, 2022. "Fractional integration and cointegration," CREATES Research Papers 2022-02, Department of Economics and Business Economics, Aarhus University.
    33. He, Xue-Zhong & Zheng, Huanhuan, 2016. "Trading heterogeneity under information uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 64-80.
    34. Adam Goliński & João Madeira & Dooruj Rambaccussing, 2015. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices," Dundee Discussion Papers in Economics 284, Economic Studies, University of Dundee.
    35. Golinski, Adam & Madeira, Joao & Rambaccussing, Dooruj, 2014. "Fractional Integration of the Price-Dividend Ratio in a Present-Value Model," MPRA Paper 58554, University Library of Munich, Germany.
    36. Tse, Chin-Bun & Rodgers, Timothy & Niklewski, Jacek, 2014. "The 2007 financial crisis and the UK residential housing market: Did the relationship between interest rates and house prices change?," Economic Modelling, Elsevier, vol. 37(C), pages 518-530.
    37. Gong, Xu & Lin, Boqiang, 2019. "Modeling stock market volatility using new HAR-type models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 194-211.
    38. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2015. "Financial connectedness among European volatility risk premia," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0058, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    39. Daniel Borup & Bent Jesper Christensen & Yunus Emre Ergemen, 2019. "Assessing predictive accuracy in panel data models with long-range dependence," CREATES Research Papers 2019-04, Department of Economics and Business Economics, Aarhus University.
    40. Qiu, Rui & Liu, Jing & Li, Yan, 2023. "Long-term adjusted volatility: Powerful capability in forecasting stock market returns," International Review of Financial Analysis, Elsevier, vol. 86(C).
    41. Lee, Ji Hyung & Linton, Oliver & Whang, Yoon-Jae, 2020. "Quantilograms Under Strong Dependence," Econometric Theory, Cambridge University Press, vol. 36(3), pages 457-487, June.
    42. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.
    43. Conrad, Christian & Loch, Karin, 2015. "The Variance Risk Premium and Fundamental Uncertainty," Working Papers 0583, University of Heidelberg, Department of Economics.
    44. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    45. Dai, Zhifeng & Zhou, Huiting & Kang, Jie & Wen, Fenghua, 2021. "The skewness of oil price returns and equity premium predictability," Energy Economics, Elsevier, vol. 94(C).
    46. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    47. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022. "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 384-401.
    48. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    49. Kaczmarek, Tomasz & Będowska-Sójka, Barbara & Grobelny, Przemysław & Perez, Katarzyna, 2022. "False Safe Haven Assets: Evidence From the Target Volatility Strategy Based on Recurrent Neural Network," Research in International Business and Finance, Elsevier, vol. 60(C).
    50. José Carlos Vides & Antonio A. Golpe & Jesús Iglesias, 2018. "How did the Sovereign debt crisis affect the Euro financial integration? A fractional cointegration approach," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(4), pages 685-706, November.
    51. Erik Vogt, 2014. "Option-implied term structures," Staff Reports 706, Federal Reserve Bank of New York.
    52. Andreas Noack Jensen & Morten Ørregaard Nielsen, 2014. "A Fast Fractional Difference Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 428-436, August.
    53. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.
    54. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    55. Josselin Garnier & Knut Solna, 2015. "Correction to Black-Scholes formula due to fractional stochastic volatility," Papers 1509.01175, arXiv.org, revised Mar 2017.
    56. Dutta, Anupam & Nikkinen, Jussi & Rothovius, Timo, 2017. "Impact of oil price uncertainty on Middle East and African stock markets," Energy, Elsevier, vol. 123(C), pages 189-197.
    57. Yunus Emre Ergemen, 2016. "System Estimation of Panel Data Models under Long-Range Dependence," CREATES Research Papers 2016-02, Department of Economics and Business Economics, Aarhus University.
    58. Kangogo, Moses & Volkov, Vladimir, 2022. "Detecting signed spillovers in global financial markets: A Markov-switching approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
    59. Ahmed, Walid M.A., 2020. "Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin," Journal of Economics and Business, Elsevier, vol. 108(C).
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    61. Vortelinos, Dimitrios I. & Lakshmi, Geeta, 2015. "Market risk of BRIC Eurobonds in the financial crisis period," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 295-310.
    62. Zhishui Hu & Ioannis Kasparis & Qiying Wang, 2020. "Locally trimmed least squares: conventional inference in possibly nonstationary models," Papers 2006.12595, arXiv.org.
    63. Grace Yap & Wen Cheong Chin, 2016. "Spectral bandwidth selection for long memory," Modern Applied Science, Canadian Center of Science and Education, vol. 10(8), pages 1-63, August.
    64. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," Discussion Papers 19/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    65. Yang, Jen-Wei & Chiu, Shih-Yung & Yen, Kuang-Chieh, 2023. "Does the realized distribution-based measure dominate particular moments? Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    66. Cathy Yi-Hsuan Chen & Thomas C. Chiang & Wolfgang Karl Härdle, 2016. "Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries," SFB 649 Discussion Papers SFB649DP2016-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    67. Ana Monteiro & Nuno Silva & Helder Sebastião, 2023. "Industry return lead-lag relationships between the US and other major countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-48, December.
    68. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Department of Economics 0047, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    69. Andrea Cipollini & Iolanda Lo Cascio & Silvia Muzzioli, 2014. "Volatility risk premia and financial connectedness," Center for Economic Research (RECent) 109, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
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    71. Minxian Yang, 2014. "The Risk Return Relationship: Evidence from Index Return and Realised Variance Series," Discussion Papers 2014-16, School of Economics, The University of New South Wales.
    72. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    73. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  17. Tim Bollerslev & Viktor Todorov, 2011. "Tails, Fears, and Risk Premia," Journal of Finance, American Finance Association, vol. 66(6), pages 2165-2211, December.
    See citations under working paper version above.
  18. Tim Bollerslev & Natalia Sizova & George Tauchen, 2011. "Volatility in Equilibrium: Asymmetries and Dynamic Dependencies," Review of Finance, European Finance Association, vol. 16(1), pages 31-80.
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    Cited by:

    1. Imane El Ouadghiri & Remzi Uctum, 2016. "Jumps in equilibrium prices and asymmetric news in foreign exchange markets," Post-Print hal-01386027, HAL.
    2. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    3. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    4. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    5. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    6. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    7. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    8. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
    9. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Dehua Shen & Andrew Urquhart & Pengfei Wang, 2020. "Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks," European Financial Management, European Financial Management Association, vol. 26(5), pages 1294-1323, November.
    11. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    12. Özbekler, Ali Gencay & Kontonikas, Alexandros & Triantafyllou, Athanasios, 2020. "Volatility Forecasting in European Government Bond Markets," Essex Finance Centre Working Papers 27362, University of Essex, Essex Business School.
    13. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    14. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    15. Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
    16. Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2008. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," BIS Working Papers 249, Bank for International Settlements.
    17. Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
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    31. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    32. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
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    34. Su, Fei & Wang, Xinyi & Yuan, Yulin, 2022. "The intraday dynamics and intraday price discovery of bitcoin," Research in International Business and Finance, Elsevier, vol. 60(C).
    35. Christoffersen, Peter & Pan, Xuhui (Nick), 2018. "Oil volatility risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 5-26.
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    37. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    38. Hugh Christensen & Simon Godsill & Richard E Turner, 2020. "Hidden Markov Models Applied To Intraday Momentum Trading With Side Information," Papers 2006.08307, arXiv.org.
    39. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
    40. Ma, Feng & Li, Yu & Liu, Li & Zhang, Yaojie, 2018. "Are low-frequency data really uninformative? A forecasting combination perspective," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 92-108.
    41. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne 17006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    42. Vladimír Holý & Petra Tomanová, 2023. "Streaming Approach to Quadratic Covariation Estimation Using Financial Ultra-High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 463-485, June.
    43. Diego Amaya & Peter Christoffersen & Kris Jacobs & Aurelio Vasquez, 2013. "Does Realized Skewness Predict the Cross-Section of Equity Returns?," CREATES Research Papers 2013-41, Department of Economics and Business Economics, Aarhus University.
    44. Tianlun Fei & Xiaoquan Liu & Conghua Wen, 2023. "Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1594-1621, November.
    45. Jim Griffin & Jia Liu & John M. Maheu, 2021. "Bayesian Nonparametric Estimation of Ex Post Variance [Out of Sample Forecasts of Quadratic Variation]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 823-859.
    46. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
    47. Xin Zhang & Donggyu Kim & Yazhen Wang, 2016. "Jump Variation Estimation with Noisy High Frequency Financial Data via Wavelets," Econometrics, MDPI, vol. 4(3), pages 1-26, August.
    48. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    49. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    50. Victor Bello Accioly & Beatriz Vaz de Melo Mendes, 2016. "Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil," Brazilian Business Review, Fucape Business School, vol. 13(2), pages 1-26, March.
    51. Ruwei Zhao & Xiong Xiong & Dehua Shen & Wei Zhang, 2019. "Investor Structure and Stock Price Crash Risk in a Continuous Double Auction Market: An Agent-Based Perspective," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 695-715, March.
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    55. Valentina Corradi & Norman Swanson & Walter Distaso, 2006. "Predictive Density Estimators for Daily Volatility Based on the Use of Realized Measures," Departmental Working Papers 200620, Rutgers University, Department of Economics.
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    57. Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
    58. Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets," Working papers 46, Red Investigadores de Economía.
    59. Yafeng Shi & Tingting Ying & Yanlong Shi & Chunrong Ai, 2020. "A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1025-1034, November.
    60. Kalnina, Ilze & Linton, Oliver, 2008. "Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error," Journal of Econometrics, Elsevier, vol. 147(1), pages 47-59, November.
    61. Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
    62. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    63. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2016. "Exploiting the errors: A simple approach for improved volatility forecasting," Journal of Econometrics, Elsevier, vol. 192(1), pages 1-18.
    64. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
    65. Alfred Mbairadjim Moussa & Jules Sadefo Kamdem & Michel Terraza, 2012. "Fuzzy risk adjusted performance measures: application to Hedge funds," Working Papers 12-24, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    66. Leandro Maciel, 2020. "Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model," Empirical Economics, Springer, vol. 58(4), pages 1513-1540, April.
    67. A. Mbairadjim Moussa & J. Sadefo Kamdem & M. Terraza, 2014. "Fuzzy value-at-risk and expected shortfall for portfolios with heavy-tailed returns," Post-Print hal-02901791, HAL.
    68. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
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    71. Ahmed BenSaïda, 2021. "The Good and Bad Volatility: A New Class of Asymmetric Heteroskedastic Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 540-570, April.
    72. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    73. Bonart, Julius & Lillo, Fabrizio, 2018. "A continuous and efficient fundamental price on the discrete order book grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 698-713.
    74. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2014. "Identifying periods of financial stress in Asian currencies: the role of high frequency financial market data," Working Papers 2014-12, University of Tasmania, Tasmanian School of Business and Economics.
    75. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
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  24. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
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  27. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
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  28. Lin Peng & Wei Xiong & Tim Bollerslev, 2007. "Investor Attention and Time‐varying Comovements," European Financial Management, European Financial Management Association, vol. 13(3), pages 394-422, June.

    Cited by:

    1. Manuel Ammann & Rachel Berchtold & Ralf Seiz, 2011. "Demographic Change and Pharmaceuticals' Stock Returns," European Financial Management, European Financial Management Association, vol. 17(4), pages 726-754, September.
    2. Castro, F. Henrique & Santana, Verônica, 2018. "Informativeness of stock prices after IFRS adoption in Brazil," Journal of Multinational Financial Management, Elsevier, vol. 47, pages 46-59.
    3. Medha Kulkarni & Leena B. Dam & Feeroj Nasirkhan Pathan & Vaibhav V. Vasundekar, 2024. "Evaluating Efficacy of Statutory Disclaimers of Mutual Funds on Novice and Seasoned Investors," Business Perspectives and Research, , vol. 12(1), pages 113-132, January.
    4. Kwangyong Park, 2019. "Uncertainty, Attention Allocation and Monetary Policy Asymmetry," Working Papers 2019-5, Economic Research Institute, Bank of Korea.
    5. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    6. Peltomäki, Jarkko & Vähämaa, Emilia, 2015. "Investor attention to the Eurozone crisis and herding effects in national bank stock indexes," Finance Research Letters, Elsevier, vol. 14(C), pages 111-116.
    7. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    8. Xun Zhang & Fengbin Lu & Rui Tao & Shouyang Wang, 2021. "The time-varying causal relationship between the Bitcoin market and internet attention," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-19, December.
    9. Owain Ap Gwilym & Iftekhar Hasan & Qingwei Wang & Ru Xie, 2016. "In Search of Concepts: The Effects of Speculative Demand on Stock Returns," European Financial Management, European Financial Management Association, vol. 22(3), pages 427-449, June.
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    3. Daniel O. Beltran & Deepa Dhume Datta & Thiago Revil T. Ferreira & Matteo Iacoviello & Mohammad Jahan-Parvar & Canlin Li & Juan M. Londono & Marius del Giudice Rodriguez & John H. Rogers & Bo Sun, 2017. "Taxonomy of Global Risk, Uncertainty, and Volatility Measures," International Finance Discussion Papers 1216, Board of Governors of the Federal Reserve System (U.S.).
    4. Turan G. Bali & Armen Hovakimian, 2009. "Volatility Spreads and Expected Stock Returns," Management Science, INFORMS, vol. 55(11), pages 1797-1812, November.
    5. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    6. Asai, M. & McAleer, M.J. & Medeiros, M.C., 2010. "Asymmetry and Long Memory in Volatility Modelling," Econometric Institute Research Papers EI 2010-60, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
    2. Angela Abbate & Sandra Eickmeier & Wolfgang Lemke & Massimiliano Marcellino, 2016. "The Changing International Transmission of Financial Shocks: Evidence from a Classical Time‐Varying FAVAR," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 573-601, June.

  36. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2005. "Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities," Econometrica, Econometric Society, vol. 73(1), pages 279-296, January.

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    3. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
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    5. Leonidas Tsiaras, 2010. "The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks," CREATES Research Papers 2010-34, Department of Economics and Business Economics, Aarhus University.
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    30. Gagnon, Marie-Hélène & Gimet, Céline, 2013. "The impacts of standard monetary and budgetary policies on liquidity and financial markets: International evidence from the credit freeze crisis," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4599-4614.
    31. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    32. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2014. "The Impact of Oil Price Shocks on the Stock Market Return and Volatility Relationship," CAMA Working Papers 2014-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Wang, Kent & Liu, Junwei & Liu, Zhi, 2013. "Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1777-1786.
    34. Prasad, Nalin & Grant, Andrew & Kim, Suk-Joong, 2018. "Time varying volatility indices and their determinants: Evidence from developed and emerging stock markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 115-126.
    35. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    36. Johannes W. Fedderke, 2020. "Is the Phillips curve framework still useful for understanding inflation dynamics in South Africa," Working Papers 10142, South African Reserve Bank.
    37. Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
    38. Denisa BANULESCU-RADU & Elena Ivona DUMITRESCU, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," LEO Working Papers / DR LEO 2709, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    39. Vassilios G. Papavassiliou, 2016. "Allowing For Jump Measurements In Volatility: A High-Frequency Financial Data Analysis Of Individual Stocks," Bulletin of Economic Research, Wiley Blackwell, vol. 68(2), pages 124-132, April.
    40. Gael M. Martin & Andrew Reidy & Jill Wright, 2006. "Assessing the Impact of Market Microstructure Noise and Random Jumps on the Relative Forecasting Performance of Option-Implied and Returns-Based Volatility," Monash Econometrics and Business Statistics Working Papers 10/06, Monash University, Department of Econometrics and Business Statistics.
    41. Turan G. Bali & Lin Peng, 2006. "Is there a risk–return trade‐off? Evidence from high‐frequency data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1169-1198, December.
    42. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    43. Martens, Martin & van Dijk, Dick & de Pooter, Michiel, 2009. "Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements," International Journal of Forecasting, Elsevier, vol. 25(2), pages 282-303.
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    46. Erlin Guo & Cuixia Li & Fengqin Tang, 2023. "The Convergence Rates of Large Volatility Matrix Estimator Based on Noise, Jumps, and Asynchronization," Mathematics, MDPI, vol. 11(6), pages 1-11, March.
    47. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
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    Cited by:

    1. Weiyi Liu & Song‐Ping Zhu, 2019. "Pricing variance swaps under the Hawkes jump‐diffusion process," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 635-655, June.

  38. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2004. "Analytical Evaluation Of Volatility Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(4), pages 1079-1110, November.
    See citations under working paper version above.
  39. Bollerslev, Tim & Zhang, Benjamin Y. B., 2003. "Measuring and modeling systematic risk in factor pricing models using high-frequency data," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 533-558, December.

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    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Ginger Wu, 2006. "Realized Beta: Persistence and Predictability," Advances in Econometrics, in: Econometric Analysis of Financial and Economic Time Series, pages 1-39, Emerald Group Publishing Limited.
    6. Victor Olkhov, 2018. "Econophysics Beyond General Equilibrium: the Business Cycle Model," Papers 1804.04721, arXiv.org.
    7. Fulvio Corsi & Francesco Audrino, 2012. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 591-616, September.
    8. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
    9. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    10. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
    11. Zhang, Congshan & Li, Jia & Todorov, Viktor & Tauchen, George, 2022. "Variation and efficiency of high-frequency betas," Journal of Econometrics, Elsevier, vol. 228(1), pages 156-175.
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    13. Olkhov, Victor, 2018. "Economic Transactions Govern Business Cycles," MPRA Paper 88531, University Library of Munich, Germany, revised 19 Aug 2018.
    14. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2017. "How to Estimate Beta?," Hannover Economic Papers (HEP) dp-617, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
    16. Bollerslev, Tim & Li, Sophia Zhengzi & Todorov, Viktor, 2016. "Roughing up beta: Continuous versus discontinuous betas and the cross section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 120(3), pages 464-490.
    17. Victor Olkhov, 2020. "Business Cycles as Collective Risk Fluctuations," Papers 2012.04506, arXiv.org.
    18. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    19. Michela Verardo & Andrew Patton, 2009. "Does Beta Move with News? Systematic Risk and Firm-Specific Information Flows," FMG Discussion Papers dp630, Financial Markets Group.
    20. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
    21. Li, Jia & Todorov, Viktor & Tauchen, George, 2017. "Adaptive estimation of continuous-time regression models using high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 36-47.
    22. Todorov, Viktor & Bollerslev, Tim, 2010. "Jumps and betas: A new framework for disentangling and estimating systematic risks," Journal of Econometrics, Elsevier, vol. 157(2), pages 220-235, August.
    23. Griffin, Jim E. & Oomen, Roel C.A., 2011. "Covariance measurement in the presence of non-synchronous trading and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 58-68, January.
    24. Kevin Sheppard & Wen Xu, 2014. "Factor High-Frequency Based Volatility (HEAVY) Models," Economics Series Working Papers 710, University of Oxford, Department of Economics.
    25. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Post-Print hal-04218488, HAL.
    26. Kevin Sheppard & Wen Xu, 2019. "Factor High-Frequency-Based Volatility (HEAVY) Models," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 33-65.
    27. Hearn, Bruce & Phylaktis, Kate & Piesse, Jenifer, 2017. "Expropriation risk by block holders, institutional quality and expected stock returns," Journal of Corporate Finance, Elsevier, vol. 45(C), pages 122-149.
    28. Chincarini, Ludwig B. & Kim, Daehwan & Moneta, Fabio, 2020. "Beta and firm age," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 50-74.
    29. Beetsma, Roel & de Jong, Frank & Giuliodori, Massimo & Widijanto, Daniel, 2017. "Realized (co)variances of eurozone sovereign yields during the crisis: The impact of news and the Securities Markets Programme," Journal of International Money and Finance, Elsevier, vol. 75(C), pages 14-31.
    30. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    31. Bonato, Matteo, 2019. "Realized correlations, betas and volatility spillover in the agricultural commodity market: What has changed?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 184-202.
    32. S. Sanfelici & M. E. Mancino, 2008. "Covariance estimation via Fourier method in the presence of asynchronous trading and microstructure noise," Economics Department Working Papers 2008-ME01, Department of Economics, Parma University (Italy).
    33. Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
    34. Daly, Kevin, 2008. "Financial volatility: Issues and measuring techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2377-2393.
    35. Matteo Bonato & Luca Taschini, 2016. "Comovement and the financialization of commodities," GRI Working Papers 215, Grantham Research Institute on Climate Change and the Environment.
    36. Olkhov, Victor, 2018. "Economic and Financial Transactions Govern Business Cycles," MPRA Paper 93269, University Library of Munich, Germany.
    37. Beetsma, Roel & de Jong, Frank & Giuliodori, Massimo & Widijanto, Daniel, 2014. "The Impact of News and the SMP on Realized (Co)Variances in the Eurozone Sovereign Debt Market," CEPR Discussion Papers 9803, C.E.P.R. Discussion Papers.
    38. Schotman, Peter C & Zalewska, Ania, 2005. "Non-synchronous Trading and Testing for Market Integration in Central European Emerging Markets," CEPR Discussion Papers 5352, C.E.P.R. Discussion Papers.
    39. Papavassiliou, Vassilios G., 2013. "A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 184-197.
    40. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    41. Cosemans, M. & Frehen, R.G.P. & Schotman, P.C. & Bauer, R.M.M.J., 2009. "Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice," MPRA Paper 23557, University Library of Munich, Germany.
    42. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    43. Mohammad Abu Sayeed & Mardi Dungey & Wenying Yao, 2018. "High-frequency Characterisation of Indian Banking Stocks," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 213-238, August.
    44. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2011. "The Merit of High-Frequency Data in Portfolio Allocation," SFB 649 Discussion Papers SFB649DP2011-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    45. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
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    2. Hassan Tanha & Michael Dempsey, 2016. "The Information Content of ASX SPI 200 Implied Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-14, March.
    3. Gabrys Robertas & Hörmann Siegfried & Kokoszka Piotr, 2013. "Monitoring the Intraday Volatility Pattern," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 87-116, July.
    4. Atanda Mustapha Saidi, 2017. "Working Paper 273 - Stock (Mis)pricing and investment dynamics in Africa," Working Paper Series 2390, African Development Bank.
    5. Gau, Yin-Feng, 2005. "Intraday volatility in the Taipei FX market," Pacific-Basin Finance Journal, Elsevier, vol. 13(4), pages 471-487, September.
    6. Lien, Donald & Yang, Li, 2005. "Availability and settlement of individual stock futures and options expiration-day effects: evidence from high-frequency data," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 730-747, September.
    7. BOUDT, Kris & CROUX, Christophe & LAURENT, Sabéastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," LIDAM Reprints CORE 2411, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    5. Audrino, Francesco & Fengler, Matthias, 2013. "Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data," Economics Working Paper Series 1311, University of St. Gallen, School of Economics and Political Science.
    6. Ray Chou & Chun-Chou Wu & Nathan Liu, 2009. "Forecasting time-varying covariance with a range-based dynamic conditional correlation model," Review of Quantitative Finance and Accounting, Springer, vol. 33(4), pages 327-345, November.
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    2. Mohamed Mehanaoui, 2017. "Financial Market Integration: Evidence from Cross-Listed French Firms," JRFM, MDPI, vol. 10(4), pages 1-11, October.
    3. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    4. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    5. Daniel Jubinski & Marc Tomljanovich, 2013. "Do FOMC minutes matter to markets? An intraday analysis of FOMC minutes releases on individual equity volatility and returns," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 86-97, September.
    6. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    7. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    8. John Cotter, 2004. "Realized volatility and minimum capital requirements," Money Macro and Finance (MMF) Research Group Conference 2003 20, Money Macro and Finance Research Group.
    9. Yusaku Nishimura & Yoshiro Tsutsui & Kenjiro Hirayama, 2016. "The Chinese Stock Market Does not React to the Japanese Market: Using Intraday Data to Analyse Return and Volatility Spillover Effects," The Japanese Economic Review, Springer, vol. 67(3), pages 280-294, September.
    10. Yoshiro Tsutsui & Kenjiro Hirayama, 2008. "How Fast Do Tokyo and New York Stock Exchanges Respond to Each Other?: An Analysis with High-Frequency Data," Discussion Papers in Economics and Business 08-32, Osaka University, Graduate School of Economics.
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    6. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
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    36. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
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    7. Min-woo Kang, 2019. "Currency Market Efficiency Revisited: Evidence from Korea," IJFS, MDPI, vol. 7(3), pages 1-17, September.
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    1. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    2. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2012. "GARCH Option Valuation: Theory and Evidence," CREATES Research Papers 2012-50, Department of Economics and Business Economics, Aarhus University.
    3. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    4. Mohamed Fakhfekh & Ahmed Ghorbel & Nadhem Selmi & Nejib Hachicha, 2017. "Dependence between oil price volatility, Islamic and conventional Dow Jones indexes: Implication for portfolio management and hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 18(1), pages 29-48, January.
    5. Stentoft, Lars, 2005. "Pricing American options when the underlying asset follows GARCH processes," Journal of Empirical Finance, Elsevier, vol. 12(4), pages 576-611, September.
    6. Guo, Weiyu, 2004. "Some evidence in the trading and pricing of equity LEAPS," International Review of Economics & Finance, Elsevier, vol. 13(4), pages 407-426.
    7. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    8. Carnero Fernández, María Ángeles & Pérez, Ana & Ruiz Ortega, Esther, 2014. "Identification of asymmetric conditional heteroscedasticity in the presence of outliers," DES - Working Papers. Statistics and Econometrics. WS ws141912, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    10. Michèle Breton & Javier de Frutos, 2010. "Option Pricing Under GARCH Processes Using PDE Methods," Operations Research, INFORMS, vol. 58(4-part-2), pages 1148-1157, August.
    11. Ulrich K. Müller & Mark W. Watson, 2008. "Testing Models of Low-Frequency Variability," Econometrica, Econometric Society, vol. 76(5), pages 979-1016, September.
    12. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, University Library of Munich, Germany.
    13. Cochran, Steven J. & Mansur, Iqbal & Odusami, Babatunde, 2012. "Volatility persistence in metal returns: A FIGARCH approach," Journal of Economics and Business, Elsevier, vol. 64(4), pages 287-305.
    14. Clifford Hurvich & Eric Moulines & Philippe Soulier, 2004. "Estimating Long Memory in Volatility," Econometrics 0412006, University Library of Munich, Germany.
    15. Christoffersen, Peter & Feunou, Bruno & Jacobs, Kris & Meddahi, Nour, 2014. "The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 663-697, June.
    16. Lars Stentoft, 2008. "American Option Pricing Using GARCH Models and the Normal Inverse Gaussian Distribution," Journal of Financial Econometrics, Oxford University Press, vol. 6(4), pages 540-582, Fall.
    17. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
    18. Peter Christoffersen & Redouane Elkamhi & Bruno Feunou & Kris Jacobs, 2009. "Option Valuation with Conditional Heteroskedasticity and Non-Normality," CIRANO Working Papers 2009s-32, CIRANO.
    19. Pérez, Ana & Ruiz Ortega, Esther, 2001. "Modelos de memoria larga para series económicas y financieras," DES - Documentos de Trabajo. Estadística y Econometría. DS ds010101, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Mohamed El Hedi Arouri & Shawkat Hammoudeh & Amine Lahiani & Duc Khuong Nguyen, 2013. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," Working Papers hal-00798033, HAL.
    21. Zlotnik, Andrey, 2007. "An Empirical Study of the Stability of Hurst Exponent Behavior Applied to Russian and American Stock Markets," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 5(1), pages 20-29.
    22. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    23. Yi Xue & Ramazan Gencay, 2009. "Trading Frequency and Volatility Clustering," Working Paper series 31_09, Rimini Centre for Economic Analysis.
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    29. González-Pla, Francisco & Lovreta, Lidija, 2019. "Persistence in firm’s asset and equity volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    30. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
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    42. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai & Yintian Wang, 2008. "Option Valuation with Long-run and Short-run Volatility Components," CREATES Research Papers 2008-11, Department of Economics and Business Economics, Aarhus University.
    43. Federico M. Bandi & Benoit Perron, 2006. "Long Memory and the Relation Between Implied and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 636-670.
    44. Rasheed O. Alao & Abdulkareem Alhassan & Saheed Alao & Ifedolapo O. Olanipekun & Godwin O. Olasehinde-Williams & Ojonugwa Usman, 2023. "Symmetric and asymmetric GARCH estimations of the impact of oil price uncertainty on output growth: evidence from the G7," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-14, December.
    45. Shahid Ali & Junrui Zhang & Mazhar Abbas & Muhammad Umar Draz & Fayyaz Ahmad, 2019. "Symmetric and Asymmetric GARCH Estimations and Portfolio Optimization: Evidence From G7 Stock Markets," SAGE Open, , vol. 9(2), pages 21582440198, May.
    46. Len, Angel & Vaello-Sebasti, Antoni, 2009. "American GARCH employee stock option valuation," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1129-1143, June.
    47. Hayette Gatfaoui, 2004. "Idiosyncratic Risk, Systematic Risk and Stochastic Volatility: An Implementation of Merton's Credit Risk Valuation," Research Paper Series 123, Quantitative Finance Research Centre, University of Technology, Sydney.
    48. Jensen Mark J., 2016. "Robust estimation of nonstationary, fractionally integrated, autoregressive, stochastic volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 455-475, September.
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    50. Pedro J. F. de Lima & Michelle L. Barnes, 2000. "Modeling Financial Volatility: Extreme Observations, Nonlinearities and Nonstationarities," School of Economics and Public Policy Working Papers 2000-05, University of Adelaide, School of Economics and Public Policy.
    51. Peter Christoffersen & Kris Jacobs, 2004. "Which GARCH Model for Option Valuation?," Management Science, INFORMS, vol. 50(9), pages 1204-1221, September.
    52. Beatriz Vaz de Melo Mendes, 2005. "Computing Conditional VaR using Time-varying CopulasComputing Conditional VaR using Time-varying Copulas," Brazilian Review of Finance, Brazilian Society of Finance, vol. 3(2), pages 251-265.
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    54. Rania Jammazi & Chaker Aloui, 2014. "Cyclical components and dual long memory in the foreign exchange rate dynamics: the Tunisian case," Working Papers 2014-198, Department of Research, Ipag Business School.
    55. Masato Ubukata & Toshiaki Watanabe, 2011. "Pricing Nikkei 225 Options Using Realized Volatility," IMES Discussion Paper Series 11-E-18, Institute for Monetary and Economic Studies, Bank of Japan.
    56. 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.
    57. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    58. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc.
    59. Hatem Ben-Ameur & Michèle Breton & Juan-Manuel Martinez, 2009. "Dynamic Programming Approach for Valuing Options in the GARCH Model," Management Science, INFORMS, vol. 55(2), pages 252-266, February.
    60. Garvey, John & Gallagher, Liam A., 2013. "The economics of data: Using simple model-free volatility in a high-frequency world," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 370-379.
    61. Rodríguez, Julio & Ruiz Ortega, Esther, 2003. "A powerful test for conditional heteroscedasticity for financial time series with highly persistent volatilities," DES - Working Papers. Statistics and Econometrics. WS ws036716, Universidad Carlos III de Madrid. Departamento de Estadística.
    62. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    63. Michel Beine & Agnes Bénassy-Quéré & Christelle Lecourt, 2002. "Central Bank intervention and foreign exchange rates: new evidence from FIGARCH estimations," ULB Institutional Repository 2013/10445, ULB -- Universite Libre de Bruxelles.
    64. Masato Ubukata & Toshiaki Watanabe, 2013. "Pricing Nikkei 225 Options Using Realized Volatility," Global COE Hi-Stat Discussion Paper Series gd12-273, Institute of Economic Research, Hitotsubashi University.
    65. Maheu John, 2005. "Can GARCH Models Capture Long-Range Dependence?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-43, December.
    66. Jian Zhou & Zhixin Kang, 2011. "A Comparison of Alternative Forecast Models of REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 275-294, April.
    67. Bentes, Sonia R., 2015. "Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: New evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 355-364.
    68. Michel Beine & Agnès Bénassy-Quéré & Christelle Lecourt, 1999. "The Impact of Foreign Exchange Interventions: New Evidence from FIGARCH Estimations," Working Papers 1999-14, CEPII research center.
    69. Jiang, George J. & Tian, Yisong S., 2010. "Forecasting Volatility Using Long Memory and Comovements: An Application to Option Valuation under SFAS 123R," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 503-533, April.
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    1. Aßmuth, Pascal, 2015. "Stock price related financial fragility and growth patterns," Center for Mathematical Economics Working Papers 539, Center for Mathematical Economics, Bielefeld University.
    2. Luis A. Gil-Alana & Rangan Gupta, 2013. "Persistence and Cycles in Historical Oil Prices Data," Working Papers 201375, University of Pretoria, Department of Economics.
    3. Torben G. Andersen & Oleg Bondarenko & Albert S. Kyle & Anna A. Obizhaeva, 2020. "Intraday Trading Invariance in the E-mini S&P 500 Futures Market," Working Papers w0272, New Economic School (NES).
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
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    3. Dye, Ronald A., 2001. "An evaluation of "essays on disclosure" and the disclosure literature in accounting," Journal of Accounting and Economics, Elsevier, vol. 32(1-3), pages 181-235, December.
    4. Alemany, Nuria & Aragó, Vicent & Salvador, Enrique, 2020. "The distribution of index futures realised volatility under seasonality and microstructure noise," Economic Modelling, Elsevier, vol. 93(C), pages 398-414.
    5. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    6. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.

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    2. Szabolcs Mike & J. Doyne Farmer, 2007. "An empirical behavioral model of liquidity and volatility," Papers 0709.0159, arXiv.org.
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    4. J. Doyne Farmer & John Geanakoplos, 2008. "The Virtues and Vices of Equilibrium and the Future of Financial Economics," Levine's Working Paper Archive 122247000000002067, David K. Levine.
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    6. J. Doyne Farmer & Paolo Patelli & Ilija I. Zovko, 2003. "The Predictive Power of Zero Intelligence in Financial Markets," Papers cond-mat/0309233, arXiv.org, revised Feb 2004.
    7. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
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    14. Jim Gatheral & Roel Oomen, 2010. "Zero-intelligence realized variance estimation," Finance and Stochastics, Springer, vol. 14(2), pages 249-283, April.
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    20. Wang, Jianxin, 1999. "Asymmetric information and the bid-ask spread: an empirical comparison between automated order execution and open outcry auction," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(2), pages 115-128, April.
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    22. Hugh Luckock, 2003. "A steady-state model of the continuous double auction," Quantitative Finance, Taylor & Francis Journals, vol. 3(5), pages 385-404.
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  60. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
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    4. Mohamed Mehanaoui, 2017. "Financial Market Integration: Evidence from Cross-Listed French Firms," JRFM, MDPI, vol. 10(4), pages 1-11, October.
    5. Elgammal, Mohammed M. & Ahmed, Walid M.A. & Alshami, Abdullah, 2021. "Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    6. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    7. Rohit Deo & Clifford Hurvich & Yi Lu, 2005. "Forecasting Realized Volatility Using a Long Memory Stochastic Volatility Model: Estimation, Prediction and Seasonal Adjustment," Econometrics 0501002, University Library of Munich, Germany.
    8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    9. Tim Bollerslev & Viktor Todorov, 2010. "Tails, Fears and Risk Premia," Working Papers 10-33, Duke University, Department of Economics.
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    12. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
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    7. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.
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    9. Gurnain Pasricha, 2010. "Bank Competition and International Financial Integration: Evidence Using a New Index," Staff Working Papers 10-35, Bank of Canada.
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    24. Shusheng Ding & Tianxiang Cui & Yongmin Zhang & Jiawei Li, 2021. "Liquidity effects on oil volatility forecasting: From fintech perspective," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-21, November.
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    30. Hautsch, Nikolaus & Pohlmeier, Winfried, 2001. "Econometric Analysis of Financial Transaction Data: Pitfalls and Opportunities," CoFE Discussion Papers 01/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    31. Ulibarri, Carlos A. & Anselmo, Peter & Hovsepian, Karen & Florescu, Ionut & Tolk, Jacob, 2008. "'Noise trader risk' and Bayesian market making in FX derivatives: rolling loaded dice?," MPRA Paper 14814, University Library of Munich, Germany.
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    1. Joanna Olbrys, 2013. "Asymmetric impact of innovations on volatility in the case of the US and CEEC-3 markets: EGARCH based approach," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 13, pages 33-50.
    2. Mun, Kyung-Chun & Morgan, George Emir, 2003. "Risk premia on foreign exchange: a direct approach," Journal of Multinational Financial Management, Elsevier, vol. 13(3), pages 231-250, July.
    3. Sinha, Pankaj & Mathur, Kritika, 2012. "Evolution of security transaction tax in India," MPRA Paper 40165, University Library of Munich, Germany.
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    5. Li, Dandan & Ghoshray, Atanu & Morley, Bruce, 2012. "Measuring the risk premium in uncovered interest parity using the component GARCH-M model," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 167-176.
    6. Kritika Mathur & Nidhi Kaicker & Raghav Gaiha & Katsushi Imai & Ganesh Thapa, 2013. "Financialisation of Food Commodity Markets, Price Surge and Volatility: New Evidence," Economics Discussion Paper Series 1312, Economics, The University of Manchester.
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    Cited by:

    1. Baffoe-Bonnie, J. & Khayum, M., 1995. "Economic Development, Life Cycle Consumption, and Planning Horizons," Papers 4-95-1-ces, Pennsylvania State - Department of Economics.

Chapters

  1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    See citations under working paper version above.
  2. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    See citations under working paper version above.
  3. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.

    Cited by:

    1. Márcio Gomes Pinto Garcia & Marcelo Cunha Medeiros & Francisco Eduardo de Luna e Almeida Santos, 2014. "Economic gains of realized volatility in the Brazilian stock market," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(3), pages 319-349.
    2. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    3. Davide Pettenuzzo & Konstantinos Metaxoglou & Aaron Smith, 2016. "Option-Implied Equity Premium Predictions via Entropic TiltinG," Working Papers 99R, Brandeis University, Department of Economics and International Business School, revised Aug 2016.
    4. Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
    5. Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 volatility using ultra-high frequency data," Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
    6. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    7. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2017. "Trends in distributional characteristics : Existence of global warming," UC3M Working papers. Economics 24121, Universidad Carlos III de Madrid. Departamento de Economía.
    8. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    9. Lucien Boulet, 2021. "Forecasting High-Dimensional Covariance Matrices of Asset Returns with Hybrid GARCH-LSTMs," Papers 2109.01044, arXiv.org.
    10. Davide Pettenuzzo & Francesco Ravazzolo, 2014. "Optimal portfolio choice under decision-based model combinations," Working Paper 2014/15, Norges Bank.
    11. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    12. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    13. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. Dong Hwan Oh & Andrew J. Patton, 2015. "High-Dimensional Copula-Based Distributions with Mixed Frequency Data," Finance and Economics Discussion Series 2015-50, Board of Governors of the Federal Reserve System (U.S.).
    15. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    16. Olkhov, Victor, 2018. "Expectations, Price Fluctuations and Lorenz Attractor," MPRA Paper 89105, University Library of Munich, Germany.
    17. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
    18. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    19. Tim Bollerslev & Hao Zhou, 2006. "Expected stock returns and variance risk premia," Finance and Economics Discussion Series 2007-11, Board of Governors of the Federal Reserve System (U.S.).
    20. Politis, Dimitris N & Thomakos, Dimitrios D, 2008. "NoVaS Transformations: Flexible Inference for Volatility Forecasting," University of California at San Diego, Economics Working Paper Series qt982208kx, Department of Economics, UC San Diego.
    21. Francis X. Diebold & Georg Strasser, 2013. "On the Correlation Structure of Microstructure Noise: A Financial Economic Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(4), pages 1304-1337.
    22. Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2008. "Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan," MPRA Paper 19488, University Library of Munich, Germany.
    23. Victor Olkhov, 2022. "Price and Payoff Autocorrelations in a Multi-Period Consumption-Based Asset Pricing Model," Papers 2204.07506, arXiv.org, revised Mar 2024.
    24. Victor Olkhov, 2022. "Market-Based Price Autocorrelation," Papers 2202.09323, arXiv.org, revised Feb 2024.
    25. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," BIS Working Papers 374, Bank for International Settlements.
    26. Haakon Kavli & Kevin Kotzé, 2014. "Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 209-238, June.
    27. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    28. Bollerslev, Tim & Medeiros, Marcelo C. & Patton, Andrew J. & Quaedvlieg, Rogier, 2022. "From zero to hero: Realized partial (co)variances," Journal of Econometrics, Elsevier, vol. 231(2), pages 348-360.
    29. Davide Pettenuzzo & Antonio Gargano & Allan Timmermann, 2014. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Working Papers 75, Brandeis University, Department of Economics and International Business School.
    30. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
    31. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    32. Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
    33. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    34. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    35. Julien Chevallier & Benoît Sévi, 2013. "A Fear Index to Predict Oil Futures Returns," Working Papers 2013.62, Fondazione Eni Enrico Mattei.
    36. Ewing, Bradley T. & Malik, Farooq, 2017. "Modelling asymmetric volatility in oil prices under structural breaks," Energy Economics, Elsevier, vol. 63(C), pages 227-233.
    37. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
    38. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    39. Timmermann, Allan & Elliott, Graham, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers.
    40. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    41. Kevin Sheppard & Andrew J. Patton, 2008. "Evaluating Volatility and Correlation Forecasts," Economics Series Working Papers 2008fe22, University of Oxford, Department of Economics.
    42. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    43. Christoph Aymanns & J. Doyne Farmer, 2014. "The dynamics of the leverage cycle," Papers 1407.5305, arXiv.org, revised Aug 2014.
    44. Olkhov, Victor, 2022. "The Market-Based Asset Price Probability," MPRA Paper 115382, University Library of Munich, Germany, revised 16 Nov 2022.
    45. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    46. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    47. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    48. Torben G. Andersen & Tim Bollerslev & Xin Huang, 2007. "A Reduced Form Framework for Modeling Volatility of Speculative Prices based on Realized Variation Measures," CREATES Research Papers 2007-14, Department of Economics and Business Economics, Aarhus University.
    49. Stefano d'Addona & Axel H. Kind, 2005. "International Stock-Bond Correlations in a Simple Affine Asset Pricing Model," Finance 0502018, University Library of Munich, Germany.
    50. Leopoldo Catania & Stefano Grassi, 2017. "Modelling Crypto-Currencies Financial Time-Series," CEIS Research Paper 417, Tor Vergata University, CEIS, revised 11 Dec 2017.
    51. Diebold, Francis X. & Strasser, Georg H., 2008. "On the correlation structure of microstructure noise in theory and practice," CFS Working Paper Series 2008/32, Center for Financial Studies (CFS).
    52. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    53. Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
    54. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    55. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2021. "Option pricing with conditional GARCH models," European Journal of Operational Research, Elsevier, vol. 289(1), pages 350-363.
    56. Rexford Abaidoo & Elvis Kwame Agyapong, 2022. "Commodity price volatility, inflation uncertainty and political stability," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 69(3), pages 351-381, September.
    57. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    58. Johannes W. Fedderke, 2020. "Is the Phillips curve framework still useful for understanding inflation dynamics in South Africa," Working Papers 10142, South African Reserve Bank.
    59. Yun-Tao Shi & Xiang Xiang & Li Wang & Yuan Zhang & De-Hui Sun, 2018. "Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System," Energies, MDPI, vol. 11(1), pages 1-20, January.
    60. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    61. Sattarhoff, Cristina & Lux, Thomas, 2021. "Forecasting the Variability of Stock Index Returns with the Multifractal Random Walk Model for Realized Volatilities," Economics Working Papers 2021-02, Christian-Albrechts-University of Kiel, Department of Economics.
    62. Carl Lönnbark, 2016. "Asymmetry with respect to the memory in stock market volatilities," Empirical Economics, Springer, vol. 50(4), pages 1409-1419, June.
    63. Li, Xingyi & Zakamulin, Valeriy, 2020. "The term structure of volatility predictability," International Journal of Forecasting, Elsevier, vol. 36(2), pages 723-737.
    64. Juan, He & Xianglin, Jiang & Jian, Wang & Daoli, Zhu & Lei, Zhen, 2012. "VaR methods for the dynamic impawn rate of steel in inventory financing under autocorrelative return," European Journal of Operational Research, Elsevier, vol. 223(1), pages 106-115.
    65. Peter Christoffersen & Kris Jacobs & Bo Young Chang, 2011. "Forecasting with Option Implied Information," CREATES Research Papers 2011-46, Department of Economics and Business Economics, Aarhus University.
    66. Pan, Ging-Ginq & Shiu, Yung-Ming & Wu, Tu-Cheng, 2022. "Can risk-neutral skewness and kurtosis subsume the information content of historical jumps?," Journal of Financial Markets, Elsevier, vol. 57(C).
    67. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2020. "Sequential forecasting of downside extreme risk during overnight and daytime: Evidence from the Chinese Stock Market☆," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    68. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
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    211. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    212. Pelster, Matthias & Vilsmeier, Johannes, 2016. "The determinants of CDS spreads: Evidence from the model space," Discussion Papers 43/2016, Deutsche Bundesbank.
    213. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.
    214. Sander Barendse, 2017. "Interquantile Expectation Regression," Tinbergen Institute Discussion Papers 17-034/III, Tinbergen Institute.
    215. Cipollini, Fabrizio & Gallo, Giampiero M. & Palandri, Alessandro, 2021. "A dynamic conditional approach to forecasting portfolio weights," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1111-1126.
    216. Gatfaoui, Hayette, 2013. "Translating financial integration into correlation risk: A weekly reporting's viewpoint for the volatility behavior of stock markets," Economic Modelling, Elsevier, vol. 30(C), pages 776-791.
    217. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
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    Cited by:

    1. Jose A. Lopez & Christian Walter, 2000. "Is implied correlation worth calculating? Evidence from foreign exchange options and historical data," Working Paper Series 2000-02, Federal Reserve Bank of San Francisco.
    2. Antonio Rubia & Trino-Manuel Ñíguez, 2006. "Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 439-458.
    3. Yue Fang & John Zhang, 1999. "Performance of control charts for autoregressive conditional heteroscedastic processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 701-714.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    5. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    6. E. Ruiz & M.A. Carnero & D. Pereira, 2004. "Effects of Level Outliers on the Identification and Estimation of GARCH Models," Econometric Society 2004 Australasian Meetings 21, Econometric Society.
    7. Bottazzi, Giulio & Devetag, Giovanna & Pancotto, Francesca, 2011. "Does volatility matter? Expectations of price return and variability in an asset pricing experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 77(2), pages 124-146, February.
    8. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    9. MEDDAHI, Nour & RENAULT, Éric, 1998. "Aggregations and Marginalization of GARCH and Stochastic Volatility Models," Cahiers de recherche 9818, Universite de Montreal, Departement de sciences economiques.
    10. Torben G. Anderson & Tim Bollerslev & Ashish Das, 1998. "Testing for Market Microstructure Effects in Intraday Volatility: A Reassessment of the Tokyo FX Experiment," NBER Working Papers 6666, National Bureau of Economic Research, Inc.
    11. Don U. A. Galagedera & Robert Faff, 2005. "Modeling The Risk And Return Relation Conditional On Market Volatility And Market Conditions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 75-95.
    12. L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, July.
    13. Linton, Oliver & Mammen, E. & Nielsen, J., 1999. "The existence and asymptotic properties of a backfitting projection algorithm under weak conditions," LSE Research Online Documents on Economics 300, London School of Economics and Political Science, LSE Library.
    14. Victoria Saporta & Kamhon Kan, 1997. "The effects of Stamp Duty on the Level and Volatility of Equity Prices," Bank of England working papers 71, Bank of England.
    15. Carl Chiarella & Xue-Zhong He & Duo Wang, 2004. "A Behavioural Asset Pricing Model with a Time-Varying Second Moment," Research Paper Series 141, Quantitative Finance Research Centre, University of Technology, Sydney.
    16. Alessandro Rossi & Giampiero M. Gallo, 2002. "Volatility Estimation via Hidden Markov Models," Econometrics Working Papers Archive wp2002_14, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    17. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002. "Parametric and Nonparametric Volatility Measurement," Center for Financial Institutions Working Papers 02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
    18. Wolff, Christian & Lehnert, Thorsten, 2001. "Modelling Scale-Consistent VaR with the Truncated Lévy Flight," CEPR Discussion Papers 2711, C.E.P.R. Discussion Papers.
    19. Kai-Li Wang & Christopher Fawson & Christopher B. Barrett & James B. McDonald, 2001. "A flexible parametric GARCH model with an application to exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 521-536.
    20. H. Peter Boswijk, 2001. "Testing for a Unit Root with Near-Integrated Volatility," Tinbergen Institute Discussion Papers 01-077/4, Tinbergen Institute.
    21. Luis Fernando Melo Velandia & Oscar Reinaldo Becerra Camargo, 2006. "Una aproximación a la dinámica de las tasas de interés de corto plazo en Colombia a través de modelos GARCH multivariados," Borradores de Economia 366, Banco de la Republica de Colombia.
    22. Jurgen A. Doornik & Marius Ooms, 2003. "Multimodality in the GARCH Regression Model," Economics Papers 2003-W20, Economics Group, Nuffield College, University of Oxford.
    23. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2003. "Detecting level shifts in the presence of conditional heteroscedasticity," DES - Working Papers. Statistics and Econometrics. WS ws036313, Universidad Carlos III de Madrid. Departamento de Estadística.
    24. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "(Understanding, Optimizing, Using and Forecasting) Realized Volatility and Correlation," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-061, New York University, Leonard N. Stern School of Business-.
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    26. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
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    29. Luis Fernando Melo Velandia & Oscar reinaldo Becerra Camargo, 2005. "Medidas de Riesgo, Características y Técnicas de Medición: Una Aplicación del VAR y el ES a la Tasa Interbancaria de Colombia," Borradores de Economia 343, Banco de la Republica de Colombia.
    30. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    31. Jurgen A. Doornik & Marius Ooms, 2005. "Outlier Detection in GARCH Models," Economics Papers 2005-W24, Economics Group, Nuffield College, University of Oxford.
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    39. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    40. Emma Iglesias & Jean Marie Dufour, 2004. "Finite Sample and Optimal Inference in Possibly Nonstationary ARCH Models with Gaussian and Heavy-Tailed Errors," Econometric Society 2004 North American Summer Meetings 161, Econometric Society.
    41. Viviana Fernández, 2003. "Interest Rate Volatility and Nominalization," Documentos de Trabajo 153, Centro de Economía Aplicada, Universidad de Chile.
    42. Juan Carlos Gómez-Sala, 2001. "Rentabilidad y liquidez alrededor de la fecha de desdoblamiento de las acciones," Investigaciones Economicas, Fundación SEPI, vol. 25(1), pages 171-202, January.
    43. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600.
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    45. Tina Hviid Rydberg & Neil Shephard, 2000. "BIN Models for Trade-by-Trade Data. Modelling the Number of Trades in a Fixed Interval of Time," Econometric Society World Congress 2000 Contributed Papers 0740, Econometric Society.
    46. Massimiliano Cecconi & Giampiero M. Gallo & Marco J. Lombardi, 2002. "GARCH-based Volatility Forecasts for Market Volatility Indices," Econometrics Working Papers Archive wp2002_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    47. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    48. Jurgen A. Doornik and Marius Ooms, 2001. "Multimodality and the GARCH Likelihood," Computing in Economics and Finance 2001 76, Society for Computational Economics.
    49. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
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    51. Celso Brunetti & Roberto S. Mariano & Chiara Scotti & Augustine H. H. Tan, 2003. "Markov Switching Garch Models of Currency Crises in Southeast Asia," PIER Working Paper Archive 03-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    52. Sanghoon Lee, 2004. "Approximation of A Jump-Diffusion Process," Econometric Society 2004 Far Eastern Meetings 412, Econometric Society.
    53. Tim Bollerslev & Jonathan H. Wright, 1999. "High frequency data, frequency domain inference and volatility forecasting," International Finance Discussion Papers 649, Board of Governors of the Federal Reserve System (U.S.).
    54. Elena Andreou & Eric Ghysels, 2003. "Test for Breaks in the Conditional Co-Movements of Asset Returns," University of Cyprus Working Papers in Economics 3-2003, University of Cyprus Department of Economics.
    55. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
    56. Amir Alizadeh & Manolis Kavussanos & David Menachof, 2004. "Hedging against bunker price fluctuations using petroleum futures contracts: constant versus time-varying hedge ratios," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1337-1353.
    57. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689, December.
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    59. MEDDAHI, Nour & RENAULT, Éric, 1998. "Quadratic M-Estimators for ARCH-Type Processes," Cahiers de recherche 9814, Universite de Montreal, Departement de sciences economiques.
    60. Neil Shephard & Gabriele Fiorentini & Enrique Sentana, 2003. "Likelihood-based estimation of latent generalised ARCH structures," FMG Discussion Papers dp453, Financial Markets Group.
    61. Young-Hye Cho & Robert F. Engle, 1999. "Time-Varying Betas and Asymmetric Effect of News: Empirical Analysis of Blue Chip Stocks," NBER Working Papers 7330, National Bureau of Economic Research, Inc.
    62. Degiannakis, Stavros, 2004. "Volatility Forecasting: Evidence from a Fractional Integrated Asymmetric Power ARCH Skewed-t Model," MPRA Paper 96330, University Library of Munich, Germany.
    63. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 2002. "Alternative Models for Stock Price Dynamics," CIRANO Working Papers 2002s-58, CIRANO.
    64. Thomas J. Flavin & Michele G. Limosani, 2000. "Explaining European Short-term Interest Rate Differentials: An Application of Tobin's Portfolio Theory," Economics Department Working Paper Series n1000500, Department of Economics, National University of Ireland - Maynooth.
    65. Fornari, F. & Mele, A., 1998. "ARCH Models and Option Pricing: The Continuous Time Connection," Papers 9830, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..
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    72. Roland Shami & Don U.A. Galagedera, 2004. "Beta Risk and Regime Shift in Market Volatility," Finance 0406012, University Library of Munich, Germany.
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Books

  1. Bollerslev, Tim & Russell, Jeffrey & Watson, Mark (ed.), 2010. "Volatility and Time Series Econometrics: Essays in Honor of Robert Engle," OUP Catalogue, Oxford University Press, number 9780199549498.

    Cited by:

    1. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2019. "Forecasting Realized Volatility of Agricultural Commodities," MPRA Paper 96267, University Library of Munich, Germany.
    2. Poncela, Pilar & Ruiz Ortega, Esther, 2012. "More is not always better : back to the Kalman filter in dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS ws122317, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    4. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    5. Neil R. Ericsson, 2015. "Eliciting GDP Forecasts from the FOMC’s Minutes Around the Financial Crisis," International Finance Discussion Papers 1152, Board of Governors of the Federal Reserve System (U.S.).
    6. Chen, Xiaoyu & Chiang, Thomas C., 2020. "Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market," Research in International Business and Finance, Elsevier, vol. 53(C).
    7. Duran-Vazquez, Rocio & Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2013. "Un modelo GARCH con asimetria condicional autorregresiva para modelar series de tiempo: Una aplicacion para los rendimientos del Indice de Precios y Cotizaciones de la BMV [A GARCH model with autor," MPRA Paper 46328, University Library of Munich, Germany.
    8. Pieterse-Bloem, M., 2011. "The effect of Emu on bond market integration and investor portfolio allocations," Other publications TiSEM 3c6ce80d-9260-424a-b889-b, Tilburg University, School of Economics and Management.
    9. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    10. Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2011. "Modelación de los rendimientos bursátiles mexicanos mediante los modelos TGARCH y EGARCH: Un estudio econométrico para 30 acciones y el Índice de Precios y Cotizaciones [Modeling Mexican stock retu," MPRA Paper 36872, University Library of Munich, Germany.
    11. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    12. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2021. "Option pricing with conditional GARCH models," European Journal of Operational Research, Elsevier, vol. 289(1), pages 350-363.
    13. Andrew B. Martinez, 2011. "Comparing Government Forecasts of the United States’ Gross Federal Debt," Working Papers 2011-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    14. Stona, Filipe & Morais, Igor A.C. & Triches, Divanildo, 2018. "Economic dynamics during periods of financial stress: Evidences from Brazil," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 130-144.
    15. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, Department of Economics and Business Economics, Aarhus University.
    16. Ruben Hernandez-Murillo & Michael T. Owyang & Margarita Rubio, 2013. "Clustered housing cycles," Working Papers 2013-021, Federal Reserve Bank of St. Louis.
    17. Nicholas Apergis & Arusha Cooray, 2013. "Forecasting fiscal variables: Only a strong growth plan can sustain the Greek austerity programs - Evidence from simultaneous and structural models," CAMA Working Papers 2013-25, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. Viktor Koval & Olga Laktionova & Iryna Udovychenko & Piotr Olczak & Svitlana Palii & Liudmyla Prystupa, 2022. "Environmental Taxation Assessment on Clean Technologies Reducing Carbon Emissions Cost-Effectively," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    19. Wang, Chengyang & Nishiyama, Yoshihiko, 2015. "Volatility forecast of stock indices by model averaging using high-frequency data," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 324-337.
    20. Axel A. Araneda, 2021. "Asset volatility forecasting:The optimal decay parameter in the EWMA model," Papers 2105.14382, arXiv.org.
    21. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    22. Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2009. "On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models," Cahiers de recherche 0948, CIRPEE.
    23. Pešta, Michal & Okhrin, Ostap, 2014. "Conditional least squares and copulae in claims reserving for a single line of business," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 28-37.
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