Exploring the Variance Risk Premium Across Assets

38 Pages Posted: 4 Mar 2023

See all articles by Steven L. Heston

Steven L. Heston

University of Maryland - Department of Finance

Karamfil Todorov

Bank for International Settlements

Date Written: February 28, 2023


This paper explores the variance risk premium in option returns across twenty different futures, including equities, bonds, currencies, and commodities (energy, metals, and grains). We implement a novel model-free methodology that constructs tradable option portfolios, which replicate realized variance. In the period 2006–2020, most assets had significant variance risk premiums, but the realized S&P 500 variance risk premium was not significantly different from zero. Within a particular asset, option prices across different strikes are related to the level of volatility and the correlation of volatility with futures returns. Returns to variance are not associated with systematic risk, but are related to fat tails, consistent with option dealers demanding a premium for holding idiosyncratic volatility risk. Contrary to Bollerslev et al. (2009), we find that option-implied variance does not positively predict underlying futures returns for the majority of assets. However, implied variance does predict returns to variance-sensitive option portfolios.

Keywords: VIX, variance risk premium, commodities, volatility, futures, COVID

JEL Classification: G1, G12, G13, G23

Suggested Citation

Heston, Steven L. and Todorov, Karamfil, Exploring the Variance Risk Premium Across Assets (February 28, 2023). Available at SSRN: https://ssrn.com/abstract=4373509 or http://dx.doi.org/10.2139/ssrn.4373509

Steven L. Heston

University of Maryland - Department of Finance ( email )

Robert H. Smith School of Business
Van Munching Hall
College Park, MD 20742
United States

Karamfil Todorov (Contact Author)

Bank for International Settlements ( email )

Centralbahnplatz 2
Basel, Basel-Stadt 4002

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics