Beating a moving target: Optimal portfolio strategies for outperforming a stochastic benchmark

We consider the portfolio problem in continuous-time where the objective of the investor or money manager is to exceed the performance of a given stochastic benchmark, as is often the case in institutional money management. The benchmark is driven by a stochastic process that need not be perfectly correlated with the investment opportunities, and so the market is in a sense incomplete. We first solve a variety of investment problems related to the achievement of goals: for example, we find the portfolio strategy that maximizes the probability that the return of the investor's portfolio beats the return of the benchmark by a given percentage without ever going below it by another predetermined percentage. We also consider objectives related to the minimization of the expected time until the investor beats the benchmark. We show that there are two cases to consider, depending upon the relative favorability of the benchmark to the investment opportunity the investor faces. The problem of maximizing the expected discounted reward of outperforming the benchmark, as well as minimizing the discounted penalty paid upon being outperformed by the benchmark is also discussed. We then solve a more standard expected utility maximization problem which allows new connections to be made between some specific utility functions and the nonstandard goal problems treated here.