Risky Curves: From Unobservable Utility to Observable Opportunity Sets

Abstract

Most theories of risky choice postulate that a decision maker maximizes the expectation of a Bernoulli (or utility or similar) function. We tour 60 years of empirical search and conclude that no such functions have yet been found that are useful for out-of-sample prediction. Nor do we find practical applications of Bernoulli functions in major risk-based industries such as finance, insurance and gambling. We sketch an alternative approach to modeling risky choice that focuses on potentially observable opportunities rather than on unobservable Bernoulli functions.

Keywords: expected utility, risk aversion, St. Petersburg Paradox, decisions under uncertainty, option theory

JEL Classification: C91, C93, D11, D81, G11, G12, G22, L83