The Informational Content of High-Frequency Option Prices

We propose the option realized variance as an observable variable to summarize the information from high-frequency option data. This variable aggregates intraday option returns from midquote prices to compute an option's total variability for a given day, providing additional information about the jump activity in the data generating process. Using the S&P 500 index time series and options data, this paper documents the performance of this realized measure in predicting the index realized variance as well as the equity and variance risk premiums. We estimate an option pricing model and analyze its parameter estimates. Our results show that excluding high-frequency option information produces significant differences in variance jump parameters, estimated risk premiums, and option pricing errors.

Automated summary

This paper proposes the use of option realized variance as an observable variable to summarize the information from high-frequency option data. It shows that this measure performs well in predicting index realized variance, equity, and variance risk premiums.