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Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes

Citations

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Cited by:

  1. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
  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. 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.
  5. Degiannakis, Stavros & Filis, George & Klein, Tony & Walther, Thomas, 2022. "Forecasting realized volatility of agricultural commodities," International Journal of Forecasting, Elsevier, vol. 38(1), pages 74-96.
  6. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "Investor Happiness and Predictability of the Realized Volatility of Oil Price," Sustainability, MDPI, vol. 12(10), pages 1-11, May.
  7. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
  8. 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.
  9. repec:uts:finphd:39 is not listed on IDEAS
  10. S. Valeyre & D. S. Grebenkov & S. Aboura, 2018. "Emergence of correlations between securities at short time scales," Papers 1807.05015, arXiv.org.
  11. Nagapetyan, Artur, 2019. "Precondition stock and stock indices volatility modeling based on market diversification potential: Evidence from Russian market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 45-61.
  12. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
  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. 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.
  15. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
  16. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
  17. Aït-Sahalia, Yacine & Xiu, Dacheng, 2019. "A Hausman test for the presence of market microstructure noise in high frequency data," Journal of Econometrics, Elsevier, vol. 211(1), pages 176-205.
  18. Juan M. Londono & Mehrdad Samadi, 2023. "The Price of Macroeconomic Uncertainty: Evidence from Daily Options," International Finance Discussion Papers 1376, Board of Governors of the Federal Reserve System (U.S.).
  19. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2021. "Forecasting the volatility of asset returns: The informational gains from option prices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 862-880.
  20. 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.
  21. Gianluca Cubadda & Alain Hecq, 2022. "Dimension Reduction for High‐Dimensional Vector Autoregressive Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1123-1152, October.
  22. Eleftheria Kafousaki & Stavros Degiannakis, 2023. "Forecasting VIX: the illusion of forecast evaluation criteria," Economics and Business Letters, Oviedo University Press, vol. 12(3), pages 231-240.
  23. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
  24. Xu, Weiju & Ma, Feng & Chen, Wang & Zhang, Bing, 2019. "Asymmetric volatility spillovers between oil and stock markets: Evidence from China and the United States," Energy Economics, Elsevier, vol. 80(C), pages 310-320.
  25. 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.
  26. 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.
  27. Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen, 2023. "Jump forecasting in foreign exchange markets: A high‐frequency analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 578-624, April.
  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. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
  30. 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).
  31. 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.
  32. Eric Ghysels & Giang Nguyen, 2019. "Price Discovery of a Speculative Asset: Evidence from a Bitcoin Exchange," JRFM, MDPI, vol. 12(4), pages 1-26, October.
  33. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
  34. Heath, Davidson & Ringgenberg, Matthew C. & Samadi, Mehrdad & Werner, Ingrid M., 2019. "Reusing Natural Experiments," Working Paper Series 2019-21, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
  35. Antonio Naimoli & Giuseppe Storti, 2021. "Forecasting Volatility and Tail Risk in Electricity Markets," JRFM, MDPI, vol. 14(7), pages 1-17, June.
  36. 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).
  37. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
  38. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," Post-Print hal-01943883, HAL.
  39. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
  40. 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).
  41. Timo Dimitriadis & Roxana Halbleib & Jeannine Polivka & Jasper Rennspies & Sina Streicher & Axel Friedrich Wolter, 2022. "Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models," Papers 2212.11833, arXiv.org, revised Dec 2023.
  42. Francesco Lautizi, 2015. "Large Scale Covariance Estimates for Portfolio Selection," CEIS Research Paper 353, Tor Vergata University, CEIS, revised 07 Aug 2015.
  43. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
  44. Marcello Rambaldi & Emmanuel Bacry & Jean-Franc{c}ois Muzy, 2018. "Disentangling and quantifying market participant volatility contributions," Papers 1807.07036, arXiv.org.
  45. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
  46. Davide De Gaetano, 2016. "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre' 0208, Department of Economics - University Roma Tre.
  47. Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
  48. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
  49. Luo, Jiawen & Klein, Tony & Walther, Thomas & Ji, Qiang, 2021. "Forecasting Realized Volatility of Crude Oil Futures Prices based on Machine Learning," QBS Working Paper Series 2021/04, Queen's University Belfast, Queen's Business School.
  50. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
  51. 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.
  52. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
  53. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
  54. 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.
  55. Malinská, Barbora, 2022. "Time-varying pricing of risk in sovereign bond futures returns," Finance Research Letters, Elsevier, vol. 47(PA).
  56. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
  57. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
  58. Bollerslev, Tim & Patton, Andrew J. & Zhang, Haozhe, 2022. "Equity clusters through the lens of realized semicorrelations," Economics Letters, Elsevier, vol. 211(C).
  59. 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.
  60. 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.
  61. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
  62. Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, CEPII research center, issue 157, pages 179-202.
  63. Elena Ivona Dumitrescu & Georgiana-Denisa Banulescu, 2019. "Do High-frequency-based Measures Improve Conditional Covariance Forecasts?," Post-Print hal-03331122, HAL.
  64. Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers 1912.05228, arXiv.org, revised Dec 2021.
  65. 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.
  66. 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).
  67. Chorro, Christophe & Ielpo, Florian & Sévi, Benoît, 2020. "The contribution of intraday jumps to forecasting the density of returns," Journal of Economic Dynamics and Control, Elsevier, vol. 113(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.
  69. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
  70. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
  71. Warshaw, Evan, 2020. "Asymmetric volatility spillover between European equity and foreign exchange markets: Evidence from the frequency domain," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 1-14.
  72. Korkusuz, Burak & Kambouroudis, Dimos & McMillan, David G., 2023. "Do extreme range estimators improve realized volatility forecasts? Evidence from G7 Stock Markets," Finance Research Letters, Elsevier, vol. 55(PB).
  73. 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).
  74. Dimos Kambouroudis & David McMillan & Katerina Tsakou, 2019. "Forecasting Realized Volatility: The role of implied volatility, leverage effect, overnight returns and volatility of realized volatility," Working Papers 2019-03, Swansea University, School of Management.
  75. 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.
  76. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
  77. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.
  78. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
  79. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Alexandros Garefalakis & Nikolaos Sariannidis, 2020. "Greek sovereign crisis and European exchange rates: effects of news releases and their providers," Annals of Operations Research, Springer, vol. 294(1), pages 515-536, November.
  80. 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.
  81. Gianluca Cubadda & Alain Hecq & Antonio Riccardo, 2018. "Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector," CEIS Research Paper 445, Tor Vergata University, CEIS, revised 30 Oct 2018.
  82. 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.
  83. František Čech & Jozef Baruník, 2019. "Panel quantile regressions for estimating and predicting the value‐at‐risk of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1167-1189, September.
  84. G.M. Gallo & D. Lacava & E. Otranto, 2023. "Volatility jumps and the classification of monetary policy announcements," Working Paper CRENoS 202306, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  85. 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.
  86. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  87. Wang, Ling, 2022. "The dynamics of money supply determination under asset purchase programs: A market-based versus a bank-based financial system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
  88. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
  89. Mete Kilic & Ivan Shaliastovich, 2019. "Good and Bad Variance Premia and Expected Returns," Management Science, INFORMS, vol. 67(6), pages 2522-2544, June.
  90. 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.
  91. Damian Clarke & Joseph P. Romano & Michael Wolf, 2020. "The Romano–Wolf multiple-hypothesis correction in Stata," Stata Journal, StataCorp LP, vol. 20(4), pages 812-843, December.
  92. 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).
  93. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
  94. Tang, Yusui & Ma, Feng, 2023. "The volatility of natural resources implications for sustainable development: Crude oil volatility prediction based on the multivariate structural regime switching," Resources Policy, Elsevier, vol. 83(C).
  95. Jérôme Lahaye & Christopher Neely, 2020. "The Role of Jumps in Volatility Spillovers in Foreign Exchange Markets: Meteor Shower and Heat Waves Revisited," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 410-427, April.
  96. Peter Van Tassel, 2018. "Equity Volatility Term Premia," Staff Reports 867, Federal Reserve Bank of New York.
  97. Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018. "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper 94289, University Library of Munich, Germany.
  98. Cheng, Tingting & Liu, Junli & Yao, Wenying & Zhao, Albert Bo, 2022. "The impact of COVID-19 pandemic on the volatility connectedness network of global stock market," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
  99. 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.
  100. Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li, 2023. "A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 60-75, January.
  101. 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.
  102. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
  103. 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.
  104. 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.
  105. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
  106. 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.
  107. 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.
  108. Adam E. Clements & Neda Todorova, 2016. "Information Flow, Trading Activity and Commodity Futures Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(1), pages 88-104, January.
  109. Aganin, Artem, 2017. "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 48, pages 63-84.
  110. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
  111. 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.
  112. Ao Kong & Hongliang Zhu & Robert Azencott, 2021. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 416-438, April.
  113. Manh Cuong Dong & Cathy W. S. Chen & Manabu Asai, 2023. "Bayesian non‐linear quantile effects on modelling realized kernels," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 981-995, January.
  114. Sebastien Valeyre & Denis S Grebenkov & Sofiane Aboura, 2019. "Emergence of correlations between securities at short time scales," Post-Print hal-02343888, HAL.
  115. Yehuda Izhakian & David Yermack & Jaime F. Zender, 2022. "Ambiguity and the Tradeoff Theory of Capital Structure," Management Science, INFORMS, vol. 68(6), pages 4090-4111, June.
  116. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
  117. Moawia Alghalith & Christos Floros & Konstantinos Gkillas, 2020. "Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility," Risks, MDPI, vol. 8(2), pages 1-15, April.
  118. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
  119. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
  120. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
  121. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
  122. Zhang, Yaojie & Ma, Feng & Liao, Yin, 2020. "Forecasting global equity market volatilities," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1454-1475.
  123. 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.
  124. 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.
  125. Ao Kong & Robert Azencott & Hongliang Zhu & Xindan Li, 2020. "Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis," Papers 2011.04939, arXiv.org, revised Feb 2021.
  126. Sentana, Enrique, 2018. "Volatility, diversification and contagion," CEPR Discussion Papers 12824, C.E.P.R. Discussion Papers.
  127. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  128. Richard T. Baillie & Dooyeon Cho & Seunghwa Rho, 2023. "Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility," Empirical Economics, Springer, vol. 64(6), pages 2911-2937, June.
  129. Liu, Yifan & Popova, Ivilina, 2023. "Threats to central bank independence and exchange rate volatility: High-frequency identification with Trump’s Fed tweets," Finance Research Letters, Elsevier, vol. 53(C).
  130. Jin, Daxiang & He, Mengxi & Xing, Lu & Zhang, Yaojie, 2022. "Forecasting China's crude oil futures volatility: How to dig out the information of other energy futures volatilities?," Resources Policy, Elsevier, vol. 78(C).
  131. 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.
  132. T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, vol. 12(1).
  133. Kaminska, Iryna & Roberts-Sklar, Matt, 2015. "A global factor in variance risk premia and local bond pricing," Bank of England working papers 576, Bank of England.
  134. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
  135. repec:hal:wpaper:hal-01943883 is not listed on IDEAS
  136. 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.
  137. 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.
  138. 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.
  139. 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.
  140. Morten Risstad & Airin Thodesen & Kristian August Thune & Sjur Westgaard, 2023. "On the Exchange Rate Dynamics of the Norwegian Krone," JRFM, MDPI, vol. 16(7), pages 1-18, June.
  141. 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.
  142. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
  143. 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).
  144. 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.
  145. David Ardia & Cl'ement Aymard & Tolga Cenesizoglu, 2023. "Fast and Furious: A High-Frequency Analysis of Robinhood Users' Trading Behavior," Papers 2307.11012, arXiv.org.
  146. Chuliá, Helena & Koser, Christoph & Uribe, Jorge M., 2020. "Uncovering the time-varying relationship between commonality in liquidity and volatility," International Review of Financial Analysis, Elsevier, vol. 69(C).
  147. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
  148. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  149. 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.
  150. 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.
  151. 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.
  152. Alizadeh, Amir H. & Huang, Chih-Yueh & Marsh, Ian W., 2021. "Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach," Energy Economics, Elsevier, vol. 93(C).
  153. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2017. "Inference on Self‐Exciting Jumps in Prices and Volatility Using High‐Frequency Measures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 504-532, April.
  154. 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).
  155. Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
  156. 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.
  157. 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.
  158. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
  159. Martin D. Gould & Nikolaus Hautsch & Sam D. Howison & Mason A. Porter, 2020. "Counterparty Credit Limits: The Impact of a Risk-Mitigation Measure on Everyday Trading," Applied Mathematical Finance, Taylor & Francis Journals, vol. 27(6), pages 520-548, November.
  160. Peter Reinhard Hansen & Zhuo Huang & Chen Tong & Tianyi Wang, 2021. "Realized GARCH, CBOE VIX, and the Volatility Risk Premium," Papers 2112.05302, arXiv.org.
  161. 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.
  162. Peng, Zhe & Yang, Yahui & Wu, Renshui, 2022. "The Luckin Coffee scandal and short selling attacks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
  163. 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).
  164. Chen, Jilong & Xu, Liao & Xu, Hao, 2022. "The impact of COVID-19 on commodity options market: Evidence from China," Economic Modelling, Elsevier, vol. 116(C).
  165. 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.
  166. Zhiyuan Pan & Yudong Wang & Li Liu & Qing Wang, 2019. "Improving volatility prediction and option valuation using VIX information: A volatility spillover GARCH model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 744-776, June.
  167. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
  168. Rui Fan & Oleksandr Talavera & Vu Tran, 2023. "Social media and price discovery: The case of cross‐listed firms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 151-167, February.
  169. Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
  170. 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.
  171. Kakinaka, Shinji & Umeno, Ken, 2022. "Asymmetric volatility dynamics in cryptocurrency markets on multi-time scales," Research in International Business and Finance, Elsevier, vol. 62(C).
  172. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
  173. Morelli, Giacomo & Santucci de Magistris, Paolo, 2019. "Volatility tail risk under fractionality," Journal of Banking & Finance, Elsevier, vol. 108(C).
  174. Jie Cheng, 2023. "Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies," Empirical Economics, Springer, vol. 65(2), pages 899-924, August.
  175. 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).
  176. Niu, Zilong, 2020. "Essays in empirical asset pricing and international finance," Other publications TiSEM 986cefd5-4d2b-4d5f-be7a-2, Tilburg University, School of Economics and Management.
  177. Ao Kong & Hongliang Zhu & Robert Azencott, 2019. "Predicting intraday jumps in stock prices using liquidity measures and technical indicators," Papers 1912.07165, arXiv.org.
  178. 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.
  179. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised Sep 2023.
  180. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
  181. Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.
  182. Chen, Cathy W.S. & Watanabe, Toshiaki & Lin, Edward M.H., 2023. "Bayesian estimation of realized GARCH-type models with application to financial tail risk management," Econometrics and Statistics, Elsevier, vol. 28(C), pages 30-46.
  183. 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.
  184. 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.
  185. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.
  186. Rhenan G. S. Queiroz & Sergio A. David, 2023. "Performance of the Realized-GARCH Model against Other GARCH Types in Predicting Cryptocurrency Volatility," Risks, MDPI, vol. 11(12), pages 1-13, December.
  187. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
  188. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
  189. Wang, Jying-Nan & Liu, Hung-Chun & Hsu, Yuan-Teng, 2020. "Time-of-day periodicities of trading volume and volatility in Bitcoin exchange: Does the stock market matter?," Finance Research Letters, Elsevier, vol. 34(C).
  190. 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.
  191. 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.
  192. 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.
  193. Castro, Carlos & Agudelo, Diego A. & Preciado, Sergio, 2020. "Measuring the effectiveness of volatility auctions," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 566-581.
  194. Martin, Vance L. & Tang, Chrismin & Yao, Wenying, 2018. "News and expected returns in East Asian equity markets: The RV-GARCHM model," Journal of Asian Economics, Elsevier, vol. 57(C), pages 36-52.
  195. 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).
  196. 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.
  197. Mauricio Zevallos, 2019. "A Note on Forecasting Daily Peruvian Stock Market VolatilityRisk Using Intraday Returns," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(84), pages 94-101.
  198. Todorova, Neda & Clements, Adam E., 2018. "The volatility-volume relationship in the LME futures market for industrial metals," Resources Policy, Elsevier, vol. 58(C), pages 111-124.
  199. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
  200. Alfeus, Mesias & Nikitopoulos, Christina Sklibosios, 2022. "Forecasting volatility in commodity markets with long-memory models," Journal of Commodity Markets, Elsevier, vol. 28(C).
  201. Lahaye, Jerome & Shaw, Philip, 2014. "Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV," Economics Letters, Elsevier, vol. 125(1), pages 43-46.
  202. Peng, Huan & Chen, Ruoxun & Mei, Dexiang & Diao, Xiaohua, 2018. "Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 78-85.
  203. 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.
  204. Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.
  205. Zhang, Yaojie & Ma, Feng & Wei, Yu, 2019. "Out-of-sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches," Energy Economics, Elsevier, vol. 81(C), pages 1109-1120.
  206. Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020. "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 1-12.
  207. Huang, Darien & Schlag, Christian & Shaliastovich, Ivan & Thimme, Julian, 2018. "Volatility-of-volatility risk," SAFE Working Paper Series 210, Leibniz Institute for Financial Research SAFE.
  208. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
  209. Gao, Shang & Zhang, Zhikai & Wang, Yudong & Zhang, Yaojie, 2023. "Forecasting stock market volatility: The sum of the parts is more than the whole," Finance Research Letters, Elsevier, vol. 55(PA).
  210. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
  211. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
  212. Sylvain Barde, 2015. "A fast algorithm for finding the confidence set of large collections of models," Studies in Economics 1519, School of Economics, University of Kent.
  213. Buncic, Daniel & Gisler, Katja I.M., 2017. "The role of jumps and leverage in forecasting volatility in international equity markets," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 1-19.
  214. Liang, Chao & Li, Yan & Ma, Feng & Wei, Yu, 2021. "Global equity market volatilities forecasting: A comparison of leverage effects, jumps, and overnight information," International Review of Financial Analysis, Elsevier, vol. 75(C).
  215. 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.).
  216. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
  217. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
  218. 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.
  219. Chen Liu & Chao Wang & Minh-Ngoc Tran & Robert Kohn, 2023. "Deep Learning Enhanced Realized GARCH," Papers 2302.08002, arXiv.org, revised Oct 2023.
  220. 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.
  221. 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.
  222. Daniel Borup & Martin Thyrsgaard, 2017. "Statistical tests for equal predictive ability across multiple forecasting methods," CREATES Research Papers 2017-19, Department of Economics and Business Economics, Aarhus University.
  223. 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.
  224. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
  225. Juho Kanniainen & Ye Yue, 2019. "The Arrival of News and Return Jumps in Stock Markets: A Nonparametric Approach," Papers 1901.02691, arXiv.org.
  226. Bouri, Elie & Harb, Etienne, 2022. "The size of good and bad volatility shocks does matter for spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
  227. Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
  228. 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).
  229. Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
  230. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
  231. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
  232. 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.
  233. 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.
  234. Qiu, Yue & Wang, Yifan & Xie, Tian, 2021. "Forecasting Bitcoin realized volatility by measuring the spillover effect among cryptocurrencies," Economics Letters, Elsevier, vol. 208(C).
  235. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
  236. 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.
  237. 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).
  238. 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).
  239. 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).
  240. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
  241. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
  242. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
  243. 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.
  244. Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.
  245. Gould, Martin D. & Hautsch, Nikolaus & Howison, Sam D. & Porter, Mason A., 2017. "Counterparty credit limits: An effective tool for mitigating counterparty risk?," CFS Working Paper Series 581, Center for Financial Studies (CFS).
  246. repec:uts:finphd:38 is not listed on IDEAS
  247. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).
  248. Chen, Yixiang & Ma, Feng & Zhang, Yaojie, 2019. "Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets," Energy Economics, Elsevier, vol. 81(C), pages 52-62.
  249. 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.
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