Quasi-Monte Carlo Algorithm for Pricing Options
The purpose of this paper is to compare the use of Quasi-Monte Carlo methods, especially the use of recent developed (t; m; s)-nets, versus classical Monte Carlo method for valuing _nancial derivatives. Some research has indicate that under certain condition Quasi-Monte Carlo is superior than the traditional Monte Carlo in terms of rate of convergence and accuracy. In particular, theoretic results hinted that the so-called (t; m; s)-net suppose to be the most powerful one among all the Quasi-Monte Carlo methods when the problem is "smooth". However, the application of (t; m; s)-net was not included in the exist-ing simulation literatures. In this paper I will introduce the algorithms of generate the most common Quasi-Monte Carlo sequences, then im- plement these sequences in several path-dependent options. Our in- vestigation showed that Quasi-Monte Carlo methods outperform the traditional Monte Carlo.Upon submission of an article, authors are asked to indicate their agreement to abide by an open-access license. The license permits any user to download, print out, extract, archive, and distribute the article, so long as appropriate credit is given to the authors of the work. The license ensures that your article will be as widely available as possible and that your article can be included in any scientific archive. Please read about the Creative Commons Attribution License before submitting your paper.
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