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.
| Original language | English |
|---|---|
| Pages (from-to) | 156-166 |
| Number of pages | 11 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 514 |
| DOIs | |
| State | Published - 15 Jan 2019 |
Keywords
- Encompassing regression
- GARCH
- Implied volatility
- VKOSPI
- Volatility forecasting
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