Optimal discretization of hedging strategies with jumps

Statistics and Modeling for Complex Data

In this work, we consider the hedging error due to discrete trading in models with jumps. We propose a framework enabling to (asymptotically) optimize the discretization times. More precisely, a strategy is said to be optimal if for a given cost function, no strategy has (asymptotically) a lower mean square error for a smaller cost. We focus on strategies based on hitting times and give explicit expressions for the optimal strategies. This is joint work with Peter Tankov.