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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

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 suggests that the procedure works well in practice. Implementing the procedure with actual S&P 500 option-implied volatilities and high-frequency five-minute-based realized volatilities results in significant temporal dependencies in the estimated stochastic volatility risk premium, which we in turn relate to a set of underlying 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 Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2004-56.

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Date of creation: 2004
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Handle: RePEc:fip:fedgfe:2004-56

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Keywords: Stochastic analysis ; Risk ; Uncertainty;

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