Uncovering the distribution of option implied risk aversion
Uncovering the distribution of option implied risk aversion
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.
81-104
Kyriacou, Maria
6234587e-81f1-4e1d-941d-395996f8bda7
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Strittmatter, Marius
036254b5-0ec6-4c14-ada2-e53fa5971091
May 2019
Kyriacou, Maria
6234587e-81f1-4e1d-941d-395996f8bda7
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Strittmatter, Marius
036254b5-0ec6-4c14-ada2-e53fa5971091
Kyriacou, Maria, Olmo, Jose and Strittmatter, Marius
(2019)
Uncovering the distribution of option implied risk aversion.
Journal of Mathematical Finance, 9 (2), , [9].
(doi:10.4236/jmf.2019.92006).
Abstract
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.
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JMF_2019031316105941
- Accepted Manuscript
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JMF_2019031316105941
- Version of Record
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Accepted/In Press date: 11 March 2019
e-pub ahead of print date: 14 March 2019
Published date: May 2019
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Local EPrints ID: 429247
URI: http://eprints.soton.ac.uk/id/eprint/429247
PURE UUID: aec1481f-88c8-4f99-8a77-e172ef8f9258
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Date deposited: 25 Mar 2019 17:30
Last modified: 07 Oct 2020 02:03
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