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

Tim Bollerslev, Michael S. Gibson and Hao Zhou
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Michael S. Gibson: https://www.federalreserve.gov/econres/michael-s-gibson.htm

No 2004-56, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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.

Keywords: Stochastic analysis; Risk; Uncertainty (search for similar items in EconPapers)
Date: 2004
New Economics Papers: this item is included in nep-ets, nep-fin and nep-rmg
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Citations: View citations in EconPapers (23)

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Related works:
Journal Article: Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities (2011)
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)
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