New Acceleration Schemes with the Asymptotic Expansion in Monte Carlo Simulation
In the present paper, we propose a new computational technique with the Asymptotic Expansion (AE) approach to achieve variance reduction of the Monte-Carlo integration appearing especially in finance. We extend the algorithm developed by Takahashi and Yoshida (2003) to the second order asymptotics. Moreover, we apply the AE to approximate time dependent differentials of the target value in Newton (1994)'s scheme. Our numerical examples include pricing of average, basket and swap options when the underlying state variables follow Constant Elasticity of Variance (CEV) processes.
|Date of creation:||Sep 2004|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.cirje.e.u-tokyo.ac.jp/index.htmlEmail:
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:tky:fseres:2004cf298. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CIRJE administrative office)
If references are entirely missing, you can add them using this form.