Risk Preferences and Loss Aversion in Portfolio Optimization

Traditionally, portfolio optimization is associated with finding the ideal trade-off between return and risk by maximizing the expected utility. Investor’s preferences are commonly assumed to follow a quadratic or power utility function, and asset returns are often assumed to follow a Gaussian distribution. Investment analysis has therefore long been focusing on the first two moments of the distribution, mean and variance. However, empirical asset returns are not normally distributed, and neither utility function captures investors’ true attitudes towards losses. This contribution investigates the impact of these specification errors under realistic assumptions. As traditional optimization techniques cannot deal reliably with the extended problem, we suggest the use of a heuristic approach. We find that loss aversion has a substantial impact on what investors consider to be an efficient portfolio and that mean-variance analysis alone can be utterly misguiding.