Author(s)

Maria Kyriacou¹, Jose Olmo^2*, Marius Strittmatter¹

¹Economics Department, University of Southampton, Southampton, UK.
²Department of Economic Analysis, Universidad de Zaragoza, Zaragoza, Spain.

This paper explores the dynamics of risk aversion of a representative agent with an iso-elastic utility function. In contrast to most of the existing literature, we estimate the coefficient of relative risk aversion from option prices. To do this, we transform the risk-neutral density function obtained from a cross-section of option prices to an objective distribution function that reflects individuals’ risk aversion through a CRRA utility function. The dynamics of the relative risk-aversion coefficient are obtained by repeating the same estimation procedure over rolling windows. This procedure uncovers strong variation in risk aversion over time. We also propose a simulation procedure to construct confidence intervals for the risk-aversion coefficient in each period. We assess the robustness of these confidence intervals under different assumptions on the data generating process of stock prices. The results imply a strong influence of volatility on the variation of risk aversion. In an empirical application, we compare the forecasting performance of our approach based on our risk-aversion estimates against the method proposed in [1]. Overall, we find that our simulation based approach obtains better forecasting results than bootstrap methods.

Simulation Based Risk-Aversion, Empirical Pricing Kernel, Index Options, Risk-Transformations

Kyriacou, M. , Olmo, J. and Strittmatter, M. (2019) Uncovering the Distribution of Option Implied Risk Aversion. Journal of Mathematical Finance, 9, 81-104. doi: 10.4236/jmf.2019.92006.