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A comprehensive look at financial volatility prediction by economic variables

Citations

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Cited by:

  1. Saadaoui Mallek, Ray & Albaity, Mohamed & Molyneux, Philip, 2022. "Herding behaviour heterogeneity under economic and political risks: Evidence from GCC," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 345-361.
  2. Jongrim Ha & M. Ayhan Kose & Christopher Otrok & Eswar S. Prasad, 2020. "Global macro-financial cycles and spillovers," CAMA Working Papers 2020-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  3. Thieu, Le Quyen, 2016. "Variance targeting estimation of the BEKK-X model," MPRA Paper 75572, University Library of Munich, Germany.
  4. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
  5. Riza Demirer & Rangan Gupta & Asli Yuksel & Aydin Yuksel, 2020. "The US Term Structure and Return Volatility in Global REIT Markets," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(3), pages 84-109, September.
  6. Beyer, Deborah B. & Fan, Zaifeng S., 2023. "The calming effects of conflict: The impact of partisan conflict on market volatility," International Review of Financial Analysis, Elsevier, vol. 85(C).
  7. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
  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. Singh, Mahendra Kumar & Lence, Sergio H., 2023. "Market Stress in Agricultural Markets: Can Alternative Implied Volatility Measures Predict It?," 2023 Annual Meeting, July 23-25, Washington D.C. 335789, Agricultural and Applied Economics Association.
  10. Christian Urom & Gideon Ndubuisi & Jude Ozor, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, CEPII research center, issue 165, pages 51-66.
  11. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
  12. 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).
  13. Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye, 2023. "Forecasting stock volatility with a large set of predictors: A new forecast combination method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1622-1647, November.
  14. Bevilacqua, Mattia & Morelli, David & Tunaru, Radu, 2019. "The determinants of the model-free positive and negative volatilities," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 1-24.
  15. Mei, Dexiang & Zeng, Qing & Zhang, Yaojie & Hou, Wenjing, 2018. "Does US Economic Policy Uncertainty matter for European stock markets volatility?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 215-221.
  16. Nektarios Aslanidis & Charlotte Christiansen & Neophytos Lambertides & Christos S. Savva, 2019. "Idiosyncratic volatility puzzle: influence of macro-finance factors," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 381-401, February.
  17. Pan, Zhiyuan & Pettenuzzo, Davide & Wang, Yudong, 2020. "Forecasting stock returns: A predictor-constrained approach," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 200-217.
  18. Dai, Zhifeng & Zhou, Huiting & Wen, Fenghua & He, Shaoyi, 2020. "Efficient predictability of stock return volatility: The role of stock market implied volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  19. Bastianin, Andrea & Manera, Matteo, 2018. "How Does Stock Market Volatility React To Oil Price Shocks?," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 666-682, April.
  20. Andrea Bucci, 2020. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 502-531.
  21. Opschoor, Anne & van Dijk, Dick & van der Wel, Michel, 2014. "Predicting volatility and correlations with Financial Conditions Indexes," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 435-447.
  22. Olkhov, Victor, 2020. "Price, Volatility and the Second-Order Economic Theory," MPRA Paper 102767, University Library of Munich, Germany.
  23. Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  24. Nonejad, Nima, 2022. "An interesting finding about the ability of geopolitical risk to forecast aggregate equity return volatility out-of-sample," Finance Research Letters, Elsevier, vol. 47(PB).
  25. 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.
  26. 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.
  27. Zhuo Huang & Fang Liang & Chen Tong, 2021. "The predictive power of macroeconomic uncertainty for commodity futures volatility," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 989-1012, September.
  28. 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.
  29. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
  30. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
  31. Xianfeng Hao & Yudong Wang, 2023. "Forecasting the stock risk premium: A new statistical constraint," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1805-1822, November.
  32. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
  33. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
  34. 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).
  35. Andersen, Torben G. & Varneskov, Rasmus T., 2021. "Consistent inference for predictive regressions in persistent economic systems," Journal of Econometrics, Elsevier, vol. 224(1), pages 215-244.
  36. Holger Fink & Andreas Fuest & Henry Port, 2018. "The Impact of Sovereign Yield Curve Differentials on Value-at-Risk Forecasts for Foreign Exchange Rates," Risks, MDPI, vol. 6(3), pages 1-19, August.
  37. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
  38. Andrea Bucci, 2020. "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
  39. Çakmaklı, Cem & van Dijk, Dick, 2016. "Getting the most out of macroeconomic information for predicting excess stock returns," International Journal of Forecasting, Elsevier, vol. 32(3), pages 650-668.
  40. Nonejad, Nima, 2019. "Forecasting aggregate equity return volatility using crude oil price volatility: The role of nonlinearities and asymmetries," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  41. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
  42. 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).
  43. 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).
  44. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
  45. Christophe Boucher & Gilles de Truchis & Elena Ivona Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," Working Papers hal-04141651, HAL.
  46. 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.
  47. 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).
  48. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
  49. Gkillas Konstantinos & Gupta Rangan & Vortelinos Dimitrios I., 2023. "Uncertainty and realized jumps in the pound-dollar exchange rate: evidence from over one century of data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(1), pages 25-47, February.
  50. Ames, Matthew & Bagnarosa, Guillaume & Peters, Gareth W., 2017. "Violations of uncovered interest rate parity and international exchange rate dependences," Journal of International Money and Finance, Elsevier, vol. 73(PA), pages 162-187.
  51. Chao, Shih-Wei, 2016. "Do economic variables improve bond return volatility forecasts?," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 10-26.
  52. Kae‐Yih Tzeng, 2023. "The ability of U.S. macroeconomic variables to predict Asian financial market returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3529-3551, October.
  53. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A boosting approach to forecasting the volatility of gold-price fluctuations under flexible loss," Resources Policy, Elsevier, vol. 47(C), pages 95-107.
  54. Hartwell, Christopher A., 2018. "The impact of institutional volatility on financial volatility in transition economies," Journal of Comparative Economics, Elsevier, vol. 46(2), pages 598-615.
  55. Dinh, Theu & Goutte, Stéphane & Nguyen, Duc Khuong & Walther, Thomas, 2022. "Economic drivers of volatility and correlation in precious metal markets," Journal of Commodity Markets, Elsevier, vol. 28(C).
  56. Sévi, Benoît, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Economic Modelling, Elsevier, vol. 31(C), pages 189-197.
  57. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01442618, HAL.
  58. Aslanidis, Nektarios & Christiansen, Charlotte, 2014. "Quantiles of the realized stock–bond correlation and links to the macroeconomy," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 321-331.
  59. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
  60. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
  61. Tran, Thuy Nhung, 2022. "The Volatility of the Stock Market and Financial Cycle: GARCH Family Models," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(1), pages 151-168.
  62. Alomran, Abdulaziz Ahmed & Alsubaiei, Bader Jawid, 2022. "Oil price uncertainty and corporate cash holdings: Global evidence," International Review of Financial Analysis, Elsevier, vol. 81(C).
  63. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
  64. Li, Matthew C., 2016. "US term structure and international stock market volatility: The role of the expectations factor and the maturity premium," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 1-15.
  65. Victor Olkhov, 2020. "Volatility Depend on Market Trades and Macro Theory," Papers 2008.07907, arXiv.org.
  66. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
  67. Aslanidis, Nektarios & Christiansen, Charlotte & Savva, Christos S., 2016. "Risk-return trade-off for European stock markets," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 84-103.
  68. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
  69. Constandina Koki & Loukia Meligkotsidou & Ioannis Vrontos, 2020. "Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 580-598, July.
  70. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
  71. 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).
  72. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
  73. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
  74. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
  75. Guo, Wenjing & Li, Sijie & Xing, Mengyue & Lin, Shengyao, 2023. "Evaluation of the operational quality of China's grain futures market based on the comprehensive information weighting method," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 467-482.
  76. 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.
  77. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
  78. Liyan Han & Xinbei Wei & Sen Yan & Qunzi Zhang, 2022. "Analyst rating matters for index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2084-2100, November.
  79. 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.
  80. 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.
  81. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
  82. Christian Conrad & Melanie Schienle, 2020. "Testing for an Omitted Multiplicative Long-Term Component in GARCH Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 229-242, April.
  83. 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.
  84. Haugom, Erik & Ray, Rina, 2017. "Heterogeneous traders, liquidity, and volatility in crude oil futures market," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 36-49.
  85. Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
  86. Qian, Lihua & Zeng, Qing & Li, Tao, 2022. "Geopolitical risk and oil price volatility: Evidence from Markov-switching model," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 29-38.
  87. 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.
  88. Riza Demirer & Rangan Gupta & Asli Yuksel & Aydin Yuksel, 2020. "The US Term Structure and Return Volatility in Global REIT Markets," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(3), pages 84-109, September.
  89. Wenting Liu & Zhaozhong Gui & Guilin Jiang & Lihua Tang & Lichun Zhou & Wan Leng & Xulong Zhang & Yujiang Liu, 2023. "Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data," Papers 2309.16196, arXiv.org.
  90. 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.
  91. Shamsi Zamenjani, Azam, 2021. "Do financial variables help predict the conditional distribution of the market portfolio?," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 327-345.
  92. Prokopczuk, Marcel & Stancu, Andrei & Symeonidis, Lazaros, 2019. "The economic drivers of commodity market volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
  93. Qingfu Liu & Qian Luo & Yiuman Tse & Yuchi Xie, 2020. "The market quality of commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1751-1766, November.
  94. Kruse, Robinson & Wegener, Christoph, 2020. "Time-varying persistence in real oil prices and its determinant," Energy Economics, Elsevier, vol. 85(C).
  95. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
  96. Zhifeng Dai & Tingyu Li & Mi Yang, 2022. "Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 980-996, August.
  97. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
  98. Lindblad, Annika, 2017. "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper 80266, University Library of Munich, Germany.
  99. 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).
  100. Vladimir Pyrlik & Pavel Elizarov & Aleksandra Leonova, 2021. "Forecasting Realized Volatility Using Machine Learning and Mixed-Frequency Data (the Case of the Russian Stock Market)," CERGE-EI Working Papers wp713, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  101. Dai, Zhifeng & Zhu, Huan & Dong, Xiaodi, 2020. "Forecasting Chinese industry return volatilities with RMB/USD exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
  102. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
  103. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
  104. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
  105. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
  106. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
  107. Becker, Christoph & Schmidt, Wolfgang M., 2013. "Stressing correlations and volatilities — A consistent modeling approach," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 174-194.
  108. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
  109. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
  110. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
  111. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
  112. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
  113. 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).
  114. Bruno Deschamps & Tianlun Fei & Ying Jiang & Xiaoquan Liu, 2022. "Procyclical volatility in Chinese stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1117-1144, April.
  115. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
  116. Li, Yan & Huynh, Luu Duc Toan & Xu, Yongan & Liang, Hao, 2023. "The forecast ability of a belief-based momentum indicator in full-day, daytime, and nighttime volatilities of Chinese oil futures," Energy Economics, Elsevier, vol. 127(PB).
  117. Cheng, Hang & Shi, Yongdong, 2020. "Forecasting China's stock market variance," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
  118. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).
  119. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
  120. Wu, Feng-lin & Zhan, Xu-dong & Zhou, Jia-qi & Wang, Ming-hui, 2023. "Stock market volatility and Russia–Ukraine conflict," Finance Research Letters, Elsevier, vol. 55(PA).
  121. Nan Hu & Jian Li & Alexis Meyer-Cirkel, 2019. "Completing the Market: Generating Shadow CDS Spreads by Machine Learning," IMF Working Papers 2019/292, International Monetary Fund.
  122. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
  123. Ahmed, Walid M.A., 2017. "The impact of foreign equity flows on market volatility during politically tranquil and turbulent times: The Egyptian experience," Research in International Business and Finance, Elsevier, vol. 40(C), pages 61-77.
  124. Liu, Na & Gao, Fumin, 2022. "The world uncertainty index and GDP growth rate," Finance Research Letters, Elsevier, vol. 49(C).
  125. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
  126. Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.
  127. Feng, Jiabao & Wang, Yudong & Yin, Libo, 2017. "Oil volatility risk and stock market volatility predictability: Evidence from G7 countries," Energy Economics, Elsevier, vol. 68(C), pages 240-254.
  128. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
  129. Riedle, Thorsten, 2018. "Using Market BuVaR as countercyclical Value at Risk approach to account for the risks of stock market crashes," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 308-321.
  130. Kirikkaleli, Dervis, 2020. "The effect of domestic and foreign risks on an emerging stock market: A time series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  131. Liu, Li & Pan, Zhiyuan, 2020. "Forecasting stock market volatility: The role of technical variables," Economic Modelling, Elsevier, vol. 84(C), pages 55-65.
  132. Shabbir Aiza & Kousar Farzana & Adeel Amna & Kousar Shazia & Jafar Rana Adeel, 2019. "Investigating the effect of governance on unemployment: a case of South Asian countries," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 55(2), pages 160-181, June.
  133. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
  134. Chu, Xiaojun & Wan, Xinmin & Qiu, Jianying, 2023. "The relative importance of overnight sentiment versus trading-hour sentiment in volatility forecasting," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
  135. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.
  136. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
  137. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
  138. Bernhard Herz & Jochen Keller, 2023. "How Do Regulators Set the Countercyclical Capital Buffer?," International Journal of Central Banking, International Journal of Central Banking, vol. 19(3), pages 99-137, August.
  139. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  140. 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).
  141. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.
  142. 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).
  143. Wang, Yudong & Wei, Yu & Wu, Chongfeng & Yin, Libo, 2018. "Oil and the short-term predictability of stock return volatility," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 90-104.
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