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

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  • Tim Bollerslev
  • Michael Gibson
  • Hao Zhou

    ()
    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

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.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2007-16.

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Length: 46
Date of creation: 16 Aug 2007
Date of revision:
Handle: RePEc:aah:create:2007-16

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Stochastic Volatility Risk Premium; Model-Free Implied Volatility; Model-Free Realized Volatility; Black-Scholes; GMM Estimation; Return Predictability;

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References

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