Mean–variance hedging with model risk

Abstract

This paper studies a hedging problem of a derivative security in a one-period model when there is the model risk. The hedging error is measured by a quadratic criterion. The model risk means that the true model is uncertain and there are many candidates for the true model. The true model is assumed to be in a set of models. We study an optimal strategy which minimizes the worst-case hedging error over all models in the set. We show how to calculate an optimal strategy and the minimum hedging error effectively. Finally we give some numerical examples to demonstrate the usefulness of our method.