Sensitivities for Bermudan Options by Regression Methods

Abstract

In this article, we propose several pathwise and finite difference-based methods for calculating sensitivities of Bermudan options using regression methods and Monte Carlo simulation. These methods rely on conditional probabilistic representations that allow, in combination with a regression approach, for efficient simultaneous computation of sensitivities at many initial positions. Assuming that the price of a Bermudan option can be evaluated sufficiently accurate, we develop a method for constructing deltas based on least squares. We finally propose a testing procedure for assessing the performance of the developed methods and give a numerical illustration. © 2009 Springer-Verlag.