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 School of Economics and Management, University of Aarhus

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: G12 G13 C51 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fmk, nep-mst and nep-upt
Date: 2007-08-16
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ftp://ftp.econ.au.dk/creates/rp/07/rp07_16.pdf (application/pdf)

Related works:
Working Paper: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2004)
Journal Article: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2005)
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Persistent link: http://EconPapers.repec.org/RePEc:aah:create:2007-16

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