Forecasting Realized Volatility from Option Prices: A Structural Approach

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: We incorporate structural risk preferences into option-implied volatility forecasts to predict S&P 500 realized volatility, demonstrating that constant relative risk preference models consistently outperform the risk-neutral benchmark (VIX). Despite a parsimonious single-parameter specification, these models exhibit predictive power comparable to, and occasionally stronger than, conventional time-series models. Furthermore, they pass the expectation hypothesis test at all but shorter horizons. Cumulant decompositions reveal that this robust performance stems from dynamically correcting the systematic upward bias in the risk-neutral variance and adjusting for the left-skewness, particularly during recessions. Moreover, the structurally implied variance risk premium instantaneously incorporates market shocks, remaining strictly positive during crashes to resolve a critical anomaly inherent in time-series models. This premium exhibits a robust positive association with future excess returns and serves as an effective signal for variance swap trading. The predictive power of our framework extends to other major international equity markets. 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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