Model risk in the over-the-counter market

Abstract

We propose a methodology to measure the parameter estimation risk and model specification risk of pricing models, as well as model selection risk of model classes, based on realized payoffs, for products in the over-the-counter market. Lévy jump models and affine jump-diffusion models are applied in estimating the fair variance strikes of variance swaps and forward starting option prices. Our results show that both parameter estimation risk and model specification risk are significant for variance swaps, while model specification risk is dominant when pricing forward starting options. We also find that the size of the model selection risk is substantial for both products.