S&P Volatility, VIX, and Asymptotic Volatility Estimates

16 Pages Posted: 2 May 2022

See all articles by Rohan Anthony Christie-David

Rohan Anthony Christie-David

affiliation not provided to SSRN

Yosef Bonaparte

University of Colorado at Denver - Department of Finance

Arjun Chatrath

affiliation not provided to SSRN

Abstract

We examine the efficacy with which the CBOE Volatility Index (VIX) predicts future (30 day forward) S&P realized volatility. We find that the VIX’s accuracy is about 63%. An alternative framework that we present, built on asymptotic distribution theory, predicts this volatility with an accuracy of about 91%. The regression adjusted R-square adjudicates for accuracy. Our methodology outperforms the option-based VIX index because (a) the option market does not fully represent the stock market, and (b) our methodology accounts more comprehensively for idiosyncratic risk. Collectively, our findings suggest it is better to employ the model we present than the VIX index if the objective is to predict S&P realized volatility.

Keywords: VIX, realized volatility, asymptotic distribution theory

Suggested Citation

Christie-David, Rohan Anthony and Bonaparte, Yosef and Chatrath, Arjun, S&P Volatility, VIX, and Asymptotic Volatility Estimates. Available at SSRN: https://ssrn.com/abstract=4098833 or http://dx.doi.org/10.2139/ssrn.4098833

Rohan Anthony Christie-David (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Yosef Bonaparte

University of Colorado at Denver - Department of Finance ( email )

United States

Arjun Chatrath

affiliation not provided to SSRN ( email )

No Address Available

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
112
Abstract Views
335
Rank
441,967
PlumX Metrics