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Forecasting global stock market implied volatility indices

Citations

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Cited by:

  1. 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.
  2. Gongyue Jiang & Gaoxiu Qiao & Lu Wang & Feng Ma, 2024. "Hybrid forecasting of crude oil volatility index: The cross‐market effects of stock market jumps," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2378-2398, September.
  3. Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024. "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper 122899, University Library of Munich, Germany.
  4. Dimitris Anastasiou & Apostolos Katsafados & Christos Tzomakas, 2026. "Banks’ stock price crash risk prediction with textual analysis: a machine learning approach," Annals of Operations Research, Springer, vol. 357(1), pages 89-111, February.
  5. Mardi Dungey & Moses Kangogo & Vladimir Volkov, 2022. "Dynamic effects of network exposure on equity markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 569-629, December.
  6. 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.
  7. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.
  8. Gong, Jue & Wang, Gang-Jin & Zhou, Yang & Xie, Chi, 2025. "Cross-market volatility forecasting with attention-based spatial–temporal graph convolutional networks," Journal of Empirical Finance, Elsevier, vol. 83(C).
  9. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
  10. Orkhan Rustamov & Fuzuli Aliyev & Richard Ajayi & Elchin Suleymanov, 2024. "A New Approach to Build a Successful Straddle Strategy: The Analytical Option Navigator," Risks, MDPI, vol. 12(7), pages 1-17, July.
  11. Vasiliki Skintzi & Stavroula P. Fameliti, 2025. "Combining realized volatility estimators based on economic performance," Journal of Asset Management, Palgrave Macmillan, vol. 26(7), pages 819-846, December.
  12. Yu, Miao & Song, Jinguo, 2018. "Volatility forecasting: Global economic policy uncertainty and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 316-323.
  13. Panagiotis Delis & Stavros Degiannakis & Konstantinos Giannopoulos, 2023. "What Should be Taken into Consideration when Forecasting Oil Implied Volatility Index?," The Energy Journal, , vol. 44(5), pages 231-250, September.
  14. Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
  15. Tissaoui, Kais & Zaghdoudi, Taha, 2021. "Dynamic connectedness between the U.S. financial market and Euro-Asian financial markets: Testing transmission of uncertainty through spatial regressions models," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 481-492.
  16. Degiannakis, Stavros & Filis, George, 2023. "Oil price assumptions for macroeconomic policy," Energy Economics, Elsevier, vol. 117(C).
  17. 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.
  18. Degiannakis, Stavros & Kafousaki, Eleftheria, 2025. "Disaggregating VIX," International Journal of Forecasting, Elsevier, vol. 41(4), pages 1559-1588.
  19. 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.
  20. Bumho Son & Yunyoung Lee & Seongwan Park & Jaewook Lee, 2023. "Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1539-1559, November.
  21. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
  22. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
  23. Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
  24. Lucas Schneider & Johannes Stübinger, 2020. "Dispersion Trading Based on the Explanatory Power of S&P 500 Stock Returns," Mathematics, MDPI, vol. 8(9), pages 1-22, September.
  25. Ghani, Maria & Qin, Quande, 2025. "Forecasting climate-sensitive industries' volatility: A regime-switching GARCH-MIDAS approach with multiple climate risk indicators," International Review of Financial Analysis, Elsevier, vol. 105(C).
  26. George Filis & Stavros Degiannakis & Zacharias Bragoudakis, 2022. "Forecasting macroeconomic indicators for Eurozone and Greece: How useful are the oil price assumptions?," Working Papers 296, Bank of Greece.
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