Hedge Funds Allocation with Survival Uncertainty and Investment Constraints

We use an expected utility framework to integrate the hedge funds survival uncertainty into an asset allocation optimizartion model. The addition of investment constraints complicates the resolution of the optimal allocation problem. It is solved using a genetic algorithm that mimics the mechanism of natural evolution and is designed to handle a set of non-linear investment constraints. We apply the genetic algorithm to analyze the impact of the optimal allocation and on the certainty equivalent of hedge funds portfolios. We observe that the portfolio weights are significantly affected by the survival uncertainty.