Portfolio selection under parameter uncertainty using a predictive distribution

We propose a portfolio selection model based on a generalized hyperbolic predictive distribution. This distribution incorporates uncertainties in mean and volatility of market returns. We then select an optimal portfolio with expected utility calculated tinder the predictive distribution. We demonstrate the performance of the new approach by applying it to simulated and real market data.