ROBUSTNESS OF QUADRATIC HEDGING STRATEGIES IN FINANCE VIA BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS WITH JUMPS

Abstract

We consider a backward stochastic di erential equation with jumps (BSDEJ) which is driven by a Brownian motion and a Poisson random measure. We present two candidate-approximations to this BSDEJ and we prove that the solution of each candidateapproximation converges to the solution of the original BSDEJ in a space which we specify. We use this result to investigate in further detail the consequences of the choice of the model to (partial) hedging in incomplete markets in nance. As an application, we consider models in which the small variations in the price dynamics are modeled with a Poisson random measure with in nite activity and models in which these small variations are modeled with a Brownian motion. Using the convergence results on BSDEJs, we show that quadratic hedging strategies are robust towards the choice of the model and we derive an estimation of the model risk.