Publication Date: August 2011
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.
Expected utility, Risk aversion, St. Petersburg Paradox, Decisions under uncertainty, Option theory
JEL Classification Codes: C91, C93, D11, D81, G11, G12, G22, L83