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Forecasting the KOSPI200 spot volatility using various volatility measures

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  • Chun, Dohyun
  • Cho, Hoon
  • Ryu, Doojin

Abstract

This study examines the volatility forecasting performance of various historical and implied volatility measures. We compare the informational efficiency of lagged realized volatility, GARCH-family volatilities, out-of-the-money (OTM) and at-the-money (ATM) implied volatilities, and the market volatility index (VKOSPI) using univariate and encompassing regression analyses. We find that historical and implied volatility both have good predictive ability, but are biased estimators of future volatility. Furthermore, the information content of the implied volatility constructed from slightly OTM options encompasses that of the deep OTM and ATM options. In general, the VKOSPI exhibits the best forecasting performance among the volatility measures analyzed in this study. However, incorporating GJR–GARCH volatility, which exhibits the best performance among the GARCH-family volatilities, in the prediction model possibly improves the explanatory power of the VKOSPI.

Suggested Citation

  • Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:156-166
    DOI: 10.1016/j.physa.2018.09.027
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    Cited by:

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    4. Jungmu Kim & Yuen Jung Park, 2020. "Predictability of OTC Option Volatility for Future Stock Volatility," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    5. Lee, Jaeram & Lee, Geul & Ryu, Doojin, 2019. "The difference in the intraday return-volume relationships of spot and futures: A quantile regression approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-38.
    6. Guidolin, Massimo & Wang, Kai, 2023. "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    7. Doojin Ryu & Jinyoung Yu, 2021. "Informed options trading around holidays," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 658-685, May.
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    9. Daehyeon Park & Jiyeon Park & Doojin Ryu, 2020. "Volatility Spillovers between Equity and Green Bond Markets," Sustainability, MDPI, vol. 12(9), pages 1-12, May.

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    More about this item

    Keywords

    Encompassing regression; GARCH; Implied volatility; Volatility forecasting; VKOSPI;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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