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

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  • Bollerslev, Tim
  • Gibson, Michael
  • Zhou, Hao

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

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 160 (2011)
Issue (Month): 1 (January)
Pages: 235-245

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Handle: RePEc:eee:econom:v:160:y:2011:i:1:p:235-245

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Web page: http://www.elsevier.com/locate/jeconom

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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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