Forecasting Market Index Volatility Using Ross-Recovered Distributions
48 Pages Posted: 26 Oct 2018 Last revised: 31 Mar 2020
Date Written: June 1, 2019
Ross (2015) shows that options data can reveal the market’s true expectations. Adapting this approach to index options (S&P, FTSE, CAC, SMI and DAX), we separate option-implied volatility into Ross-recovered true expected volatility and a risk preference factor. We investigate whether these factors perform better to forecast realized volatility if constructed locally or globally, yielding new insights to understand international dynamics in risk expectations and preferences. We find evidence of significantly improved realized volatility forecasts. Models using Ross-recovered value-weighted global measures of risk preferences have the best forecasting performances across indices. Risk preferences are best measured globally. Overall, the findings suggest that the Recovery Theorem is useful empirically and accurately recovers the true expected returns distribution and its associated pricing kernel.
Keywords: ross recovery; risk-neutral; volatility; forecast; options; international
JEL Classification: G12, G13, G14, G15
Suggested Citation: Suggested Citation