Learning to be Risk Averse?

Robert Marks

No 2014-10, Discussion Papers from School of Economics, The University of New South Wales

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: D81 (search for similar items in EconPapers)
Pages: 6 pages
Date: 2014-01
New Economics Papers: this item is included in nep-upt
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Persistent link: https://EconPapers.repec.org/RePEc:swe:wpaper:2014-10

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