Article ID: | iaor2008815 |
Country: | United States |
Volume: | 54 |
Issue: | 2 |
Start Page Number: | 217 |
End Page Number: | 231 |
Publication Date: | Mar 2006 |
Journal: | Operations Research |
Authors: | Broadie Mark, Kaya zgr |
Keywords: | simulation: applications |
The stochastic differential equations for affine jump diffusion models do not yield exact solutions that can be directly simulated. Discretization methods can be used for simulating security prices under these models. However, discretization introduces bias into the simulation results, and a large number of time steps may be needed to reduce the discretization bias to an acceptable level. This paper suggests a method for the exact simulation of the stock price and variance under Heston's stochastic volatility model and other affine jump diffusion processes. The sample stock price and variance from the exact distribution can then be used to generate an unbiased estimator of the price of a derivative security. We compare our method with the more conventional Euler discretization method and demonstrate the faster convergence rate of the error in our method. Specifically, our method achieves an