Learning to be Risk Averse?

6 Pages Posted: 26 Feb 2014

See all articles by Robert E. Marks

Robert E. Marks

UNSW Australia Business School, School of Economics

Date Written: February 18, 2014


The purpose of this research is to search for the best (highest performing) risk profile of agents who successively choose among risky prospects. An agent’s risk profile is his attitude to perceived risk, which can vary from risk preferring to risk neutral (an expected-value decision maker) to risk averse. We use the Genetic Algorithm to search in the complex stochastic space of repeated lotteries. We find that agents with a CARA utility function learn to possess risk-neutral risk profiles. Since CARA utility functions are wealth-independent, this is not surprising. When agents have wealth-dependent, CRRA utility functions, however, they also learn to possess risk profiles that are about risk neutral (from slightly risk-averse to even slightly risk-preferring), which is surprising.

Keywords: risk profile, decision-making under uncertainty, simulation

JEL Classification: D810

Suggested Citation

Marks, Robert E., Learning to be Risk Averse? (February 18, 2014). UNSW Australian School of Business Research Paper No. 2014-10, Available at SSRN: https://ssrn.com/abstract=2400766 or http://dx.doi.org/10.2139/ssrn.2400766

Robert E. Marks (Contact Author)

UNSW Australia Business School, School of Economics ( email )

High Street
Sydney, NSW 2052
+61 2 9931 9271 (Phone)

HOME PAGE: http://www.agsm.edu.au/bobm

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