The University of Southampton
University of Southampton Institutional Repository

Uncovering the distribution of option implied risk aversion

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
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), 81-104. (doi:10.4236/jmf.2019.92006).

Record type: Article

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.

Text
JMF_2019031316105941 - Accepted Manuscript
Download (2MB)
Text
JMF_2019031316105941 - Version of Record
Available under License Creative Commons Attribution.
Download (2MB)

More information

Accepted/In Press date: 11 March 2019
e-pub ahead of print date: 14 March 2019
Published date: May 2019

Identifiers

Local EPrints ID: 429247
URI: https://eprints.soton.ac.uk/id/eprint/429247
PURE UUID: aec1481f-88c8-4f99-8a77-e172ef8f9258
ORCID for Jose Olmo: ORCID iD orcid.org/0000-0002-0437-7812

Catalogue record

Date deposited: 25 Mar 2019 17:30
Last modified: 27 Jul 2019 00:31

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×