On the maximization of financial performance measures within mixture models

We introduce mixtures of probability distributions to model empirical distributions of financial asset returns. In this framework, we examine the problem of maximizing performance measures. For this purpose, we consider a large class of reward/risk ratios such as the Kappa measures and in particular the Omega ratio. This latter measure is associated to a downside risk measure based on a put component. All these measures can take account of the asymmetry of the probability distribution, which is important when dealing with mixture of distributions. We examine first a fundamental example: the ranking and maximization of Gaussian mixture distributions, according to the Omega performance measure. Then we provide a general result for the maximization of mixture distributions with respect to a very large family of performance measures, including Kappa measures.