Portfolio optimization with optimal expected utility risk measures

Optimal portfolio with vector expected utility

We study the optimal portfolio selected by an investor who conforms to Siniscalchi (2009)’s Vector Expected Utility’s (VEU) axioms and who is ambiguity averse. To this end, we derive a mean-variance preference generalised to ambiguity from the second-order Taylor-Young expansion of the VEU certainty equivalent. We apply this Mean Variance Variability preference to the static two-assets portfoli...

Tractable Robust Expected Utility and Risk Models for Portfolio Optimization

Expected utility models in portfolio optimization is based on the assumption of complete knowledge of the distribution of random returns. In this paper, we relax this assumption to the knowledge of only the mean, covariance and support information. No additional assumption on the type of distribution such as normality is made. The investor’s utility is modeled as a piecewise-linear concave func...

Portfolio Optimization with Higher Moment Risk Measures

The paper considers modeling of risk-averse preferences in stochastic programming problems using risk measures. We utilize the axiomatic foundation of coherent risk measures and deviation measures in order to develop simple representations that express risk measures via solutions of specially constructed stochastic programming problems. Using the developed representations, we introduce a new fa...

Portfolio Optimization with Quasiconvex Risk Measures

Portfolio optimization with quantile-based risk measures

In this thesis we analyze Portfolio Optimization risk-reward theory, a generalization of the mean-variance theory, in the cases where the risk measures are quantile-based (such as the Value at Risk (V aR) and the shortfall). We show, using multicriteria theory arguments, that if the measure of risk is convex and the measure of reward concave with respect to the allocation vector, then the expec...