Hedging Derivatives with Recalibration and Model Risk

This paper studies the hedging of derivatives whose pricing formulas are periodically recalibrated in the presence of model risk. We assume that the price and implied parameter processes are observed in the market but the true model of these processes is unknown. Given multiple candidates for the true model, we define a model set of candidates for the true model. We study the minimum hedging error and an optimal strategy under the worst situation and show the procedure for their calculation. Furthermore some numerical examples are provided to illustrate the impact of model risk on the optimal hedging.