Improving Return Predictability Using Variance-of-Variance Premiums

Posted: 30 Sep 2015

See all articles by Yang-Ho Park

Yang-Ho Park

Board of Governors of the Federal Reserve System

Date Written: September 29, 2015

Abstract

This paper reports that the variance-of-variance premium (VVP), the difference between the risk-neutral and physical measures of variance-of-variance, has strong predictability for stock returns, especially at very short horizons. Furthermore, pooling both information on the VVP and the variance premium (VP) can deliver a large amount of statistical and economic gain compared to using either of them alone. These results corroborate the finding of Bollerslev, Tauchen, and Zhou (2009) that volatility-of-volatility risk is a critical driver of time-varying risk premiums. Finally, the results hold in the international stock markets and are robust to traditional predictors, investor sentiment proxies, and funding constraints.

Keywords: return forecasting; risk premiums; VIX derivatives; volatility-of-volatility

JEL Classification: C53; G12

Suggested Citation

Park, Yang-Ho, Improving Return Predictability Using Variance-of-Variance Premiums (September 29, 2015). Available at SSRN: https://ssrn.com/abstract=2667194 or http://dx.doi.org/10.2139/ssrn.2667194

Yang-Ho Park (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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