Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities

Tim Bollerslev, Michael Gibson and Hao Zhou

Journal of Econometrics, 2011, vol. 160, issue 1, 235-245

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)
Date: 2011
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Citations: View citations in EconPapers (196)

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Related works:
Working Paper: Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities (2007)
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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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:160:y:2011:i:1:p:235-245

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