We study the gains from using short-dated options for volatility measurement and forecasting. Using option portfolios, we estimate nonparametrically spot volatility under weak assumptions for the underlying asset. This volatility estimator complements existing ones constructed from high-frequency returns. We show empirically, using the market index and Dow 30 stocks, that combining optimally return and option data can lead to nontrivial gains for volatility forecasting. These gains are due to “diversification” of the measurement error in the two volatility proxies. The information content of short-dated options, not spanned by the current spot volatility, is of limited relevance for volatility forecasting.
- high-frequency data
- nonparametric volatility estimation
- return predictability
- volatility forecasting
ASJC Scopus subject areas
- Social Sciences (miscellaneous)
- Economics and Econometrics