Article ID: | iaor20135232 |
Volume: | 38 |
Issue: | 3 |
Start Page Number: | 591 |
End Page Number: | 616 |
Publication Date: | Aug 2013 |
Journal: | Mathematics of Operations Research |
Authors: | Chen Nan, Huang Zhengyu |
Keywords: | differential equations |
Generating sample paths of stochastic differential equations (SDE) using the Monte Carlo method finds wide applications in financial engineering. Discretization is a popular approximate approach to generating those paths: it is easy to implement but prone to simulation bias. This paper presents a new simulation scheme to exactly generate samples for SDEs. The key observation is that the law of a general SDE can be decomposed into a product of the law of standard Brownian motion and the law of a doubly stochastic Poisson process. An acceptance‐rejection algorithm is devised based on the combination of this decomposition and a localization technique. The numerical results corroborates that the mean‐square error of the proposed method is in the order of