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

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

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Unformatted text preview: Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities Tim Bollerslev, Michael Gibson, and Hao Zhou 2004-56 NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities * Tim Bollerslev Michael Gibson Hao Zhou First Draft: September 2004 * The work of Bollerslev was supported by a grant from the National Science Foundation to the NBER. We would like to thank Nellie Liang for useful discussions during this project. The views presented here are solely those of the authors and do not necessarily represent those of the Federal Reserve Board or its staff. Matthew Chesnes provided excellent research assistance. Department of Economics, Duke University, Post Office Box 90097, Durham NC 27708, and NBER, USA, Email boller@econ.duke.edu, Phone 919-660-1846, Fax 919-684-8974. Division of Research and Statistics, Federal Reserve Board, Mail Stop 91, Washington DC 20551 USA, E-mail michael.s.gibson@frb.gov, Phone 202-452-2495, Fax 202-728-5887. Division of Research and Statistics, Federal Reserve Board, Mail Stop 91, Washington DC 20551 USA, E-mail hao.zhou@frb.gov, Phone 202-452-3360, Fax 202-728-5887. 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 sam- ple 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&P500 option-implied volatilities and high-frequency five-minute-based realized volatilities results in significant temporal depen- dencies 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. JEL Classification: G12, G13, C51, C52....
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Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and real

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