ABSTRACT RECENT ADVANCES IN SIMULATION FOR SECURITY PRICING

Abstract

Computational methods play an important role in modern finance. Through the theory of arbitragefree pricing, the price of a derivative security can be expressed as the expected value of its payouts under a particular probability measure. The resulting in-tegral becomes quite complicated if there are several state variables or if payouts are path-dependent. Sim-ulation has proved to be a valuable tool for these calculations. This paper summarizes some of the recent applications and developments of the Monte Carlo method to security pricing problems.