Forecasting the KOSPI200 spot volatility using various volatility measures

Dohyun Chun, Hoon Cho and Doojin Ryu

Physica A: Statistical Mechanics and its Applications, 2019, vol. 514, issue C, 156-166

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.

Keywords: Encompassing regression; GARCH; Implied volatility; Volatility forecasting; VKOSPI (search for similar items in EconPapers)
JEL-codes: C52 C53 G14 G15 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:514:y:2019:i:c:p:156-166

DOI: 10.1016/j.physa.2018.09.027

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