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

被引：200
作者：
Bollerslev, Tim [1 ,2 ]
Gibson, Michael [3 ]
Zhou, Hao [3 ]
机构：
[1] Duke Univ, Dept Econ, Durham, NC 27708 USA
[2] NBER, Cambridge, MA 02138 USA
[3] Fed Reserve Board, Risk Anal Sect, Washington, DC 20551 USA
来源：
JOURNAL OF ECONOMETRICS | 2011年 / 160卷 / 01期
基金：
美国国家科学基金会; 新加坡国家研究基金会;
关键词：
Stochastic volatility risk premium; Model-free implied volatility; Model-free realized volatility; Black-Scholes; GMM estimation; Return predictability; STOCHASTIC VOLATILITY; STOCK RETURNS; PRICES; VARIANCE; CONSUMPTION; COVARIANCE; MOMENTS; SAMPLE; NOISE; JUMPS;
D O I：
10.1016/j.jeconom.2010.03.033
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
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. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：235 / 245
页数：11
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