Optimal Portfolio Allocation Under Higher Moments

We evaluate how departure from normality may affect the allocation of assets. A Taylor series expansion of the expected utility allows to focus on certain moments and to compute numerically the optimal portfolio allocation. A decisive advantage of this approach is that it remains operational even if a large number of assets is involved. We show that under moderate non-normality the mean-variance criterion provides a good approximation of the expected utility maximization. In contrast, under large departure from normality (as found in some stocks in mature markets or in some stock indices in emerging markets), the mean-variance criterion may fail to approximate the expected utility correctly. In such cases, the three-moment or four-moment optimization strategies may provide a good approximation of the expected utility.