Prospect Utility Portfolio Optimization

Abstract: Portfolio choice theory have in the last decades seen a rise in utilising more advanced utility functions for finding optimal portfolios. This is partly a consequence of the relatively simplistic nature of the quadratic utility, which is often assumed in the classical mean-variance framework. There have been some suggestions on how to find optimal portfolios in ac- cordance to more realistic utility functions gathered from Prospect theory. However, some of these methods suffer from practical drawbacks. This paper proposes a method consisting of a mixture between two op- timization techniques, in order to find a portfolio allocation that is optimal in relation to the first four moments. In the empirical implementation, we utilise the S-shaped and Bilinear utility functions gathered from Prospect Theory. Results hold in an in-sample testing environment. Improving ex- pected utility, and the first three moments when tested against a standard benchmark method, as well as in measurement of the Sharpe Ratio.