Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities
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. © 2010 Elsevier B.V. All rights reserved.
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- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics