Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities

Tim Bollerslev, Michael Gibson and Hao Zhou

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: This paper proposes a method for constructing a volatility risk premium, or investor risk aversion, index. The method is intuitive and simple to implement, relying on the sample moments of the recently popularized model-free realized and option-implied volatility measures. A small-scale Monte Carlo experiment confirms that the procedure works well in practice. Implementing the procedure with actual S&P500 option-implied volatilities and high-frequency five-minute-based realized volatilities indicates significant temporal dependencies in the estimated stochastic volatility risk premium, which we in turn relate to a set of macro-finance state variables. We also find that the extracted volatility risk premium helps predict future stock market returns.

Keywords: Stochastic Volatility Risk Premium; Model-Free Implied Volatility; Model-Free Realized Volatility; Black-Scholes; GMM Estimation; Return Predictability (search for similar items in EconPapers)
JEL-codes: C51 C52 G12 G13 (search for similar items in EconPapers)
Pages: 46
Date: 2007-08-16
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fmk, nep-mst and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2011)
Journal Article: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2005)
Working Paper: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2004)
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