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Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models

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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. 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.
  3. 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.
  4. Ziyi Zhang & Wai Keung Li, 2019. "An Experiment on Autoregressive and Threshold Autoregressive Models with Non-Gaussian Error with Application to Realized Volatility," Economies, MDPI, vol. 7(2), pages 1-11, June.
  5. Barbara Będowska-Sójka, 2018. "Is intraday data useful for forecasting VaR? The evidence from EUR/PLN exchange rate," Risk Management, Palgrave Macmillan, vol. 20(4), pages 326-346, November.
  6. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
  7. 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.
  8. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark Wohar, 2020. "Volatility forecasting with bivariate multifractal models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 155-167, March.
  9. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
  10. 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.
  11. Ewald, Christian & Hadina, Jelena & Haugom, Erik & Lien, Gudbrand & Størdal, Ståle & Yahya, Muhammad, 2023. "Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures," Finance Research Letters, Elsevier, vol. 58(PA).
  12. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2024. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," Finance Research Letters, Elsevier, vol. 67(PB).
  13. 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.
  14. Ioannis Chatziantoniou & Stavros Degiannakis & George Filis & Tim Lloyd, 2021. "Oil Price Volatility is Effective in Predicting Food Price Volatility. Or is it?," The Energy Journal, , vol. 42(6), pages 25-48, November.
  15. 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.
  16. Ye, Wuyi & Xia, Wenjing & Wu, Bin & Chen, Pengzhan, 2022. "Using implied volatility jumps for realized volatility forecasting: Evidence from the Chinese market," International Review of Financial Analysis, Elsevier, vol. 83(C).
  17. Zhi Dong & Tien Foo Sing, 2021. "Do Investors Overreact for Property and Financial Service Sectors?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(1), pages 79-123, April.
  18. Slim, Skander & Dahmene, Meriam & Boughrara, Adel, 2020. "How informative are variance risk premium and implied volatility for Value-at-Risk prediction? International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 22-37.
  19. Xunfa Lu & Zhitao Ye & Kin Keung Lai & Hairong Cui & Xiao Lin, 2022. "Time-Varying Causalities in Prices and Volatilities between the Cross-Listed Stocks in Chinese Mainland and Hong Kong Stock Markets," Mathematics, MDPI, vol. 10(4), pages 1-19, February.
  20. 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).
  21. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2017. "Do Bivariate Multifractal Models Improve Volatility Forecasting in Financial Time Series? An Application to Foreign Exchange and Stock Markets," Working Papers 201728, University of Pretoria, Department of Economics.
  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. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
  24. Božović, Miloš, 2024. "VIX-managed portfolios," International Review of Financial Analysis, Elsevier, vol. 95(PA).
  25. Chen, An-Sing & Chang, Hung-Chou & Cheng, Lee-Young, 2019. "Time-varying Variance Scaling: Application of the Fractionally Integrated ARMA Model," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 1-12.
  26. Ji‐Eun Choi & Dong Wan Shin, 2022. "Parallel architecture of CNN‐bidirectional LSTMs for implied volatility forecast," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1087-1098, September.
  27. 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.
  28. Choudhary, Sangita & Jain, Anshul & Biswal, Pratap Chandra, 2024. "Dynamic linkages among bitcoin, equity, gold and oil: An implied volatility perspective," Finance Research Letters, Elsevier, vol. 62(PB).
  29. Qiao, Gaoxiu & Yang, Jiyu & Li, Weiping, 2020. "VIX forecasting based on GARCH-type model with observable dynamic jumps: A new perspective," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
  30. 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).
  31. Weiwei ZHANG & Tiezhu SUN & Yechi MA & Zilong WANG, 2021. "New Evidence on the Information Content of Implied Volatility of S&P 500: Model-Free versus Model-Based," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 109-121, December.
  32. Stavroula P. Fameliti & Vasiliki D. Skintzi, 2020. "Predictive ability and economic gains from volatility forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 200-219, March.
  33. 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.
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