The Impact of Optimistic and Pessimistic Preferences on Decision Making

Abstract

The notion of optimism or pessimism is defined in the psychology literature in terms of forecasting where the term is used more generally than in statistics. Here we use the theory of loss aversion combined with Bayesian forecasting to propose rather precise definitions of optimism and pessimism. Put simply, optimists are those who condition their Bayesian state probabilities on optimistic forecasts whilst pessimists condition their Bayesian state probabilities on pessimistic forecasts. This simple structure leads to closed-form results in asset allocation problems which can be seen as a solution of more general dichotomous problems. Our results with loss aversion utility show that a slightly optimistic (or pessimistic) preference would have a huge impact on the optimal asset allocation.