Forecasting Realized Volatility from Option Prices

Kenichiro Shiraya, Tomohisa Yamakami and Akira Yamazaki
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Kenichiro Shiraya: Graduate School of Economics, The University of Tokyo
Tomohisa Yamakami: Graduate School of Economics, The University of Tokyo
Akira Yamazaki: Graduate School of Business Administration, Hosei University

No CARF-F-603, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo

Abstract: This paper provides a comprehensive evaluation of volatility forecasters, each reflecting a distinct risk preference, for predicting realized volatility of the S&P 500 index from option prices. These forecasters are benchmarked against a risk-neutral counterpart, corresponding to the VIX index. Our empirical analysis shows that the forecaster drawn from Chabi-Yo and Loudis (2020) consistently delivers the strongest performance: it forms rational expectations for realized volatility, achieves superior out-of-sample predictive accuracy, and substantially improves trading outcomes in variance swap strategies. The remaining forecasters also provide effective predictors, whereas the risk-neutral benchmark exhibits relatively weak predictive performance. Incorporating skewness and kurtosis fails to enhance out-of-sample performance, suggesting that the original predictors are sufficient. This paper is available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5371578

Date: 2025-07
New Economics Papers: this item is included in nep-opm and nep-upt
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