Quasi-Monte Carlo Algorithm for Pricing Options

Authors

Keywords:

Quasi-Monte Carlo, Monte Carlo simulation, (t, m, s)-nets, option pricing, path-dependent options, numerical integration

Abstract

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 financial 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 existing simulation literatures. In this paper I will introduce the algorithms of generate the most common Quasi-Monte Carlo sequences, then implement these sequences in several path-dependent options. Our investigation showed that Quasi-Monte Carlo methods outperform the traditional Monte Carlo.

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Author Biography

Jenny X. Li, Pennsylvania State University

Department of Mathematics and Economics, Pennsylvania State University

References

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Published

2000-04-30

How to Cite

Li, J. X. (2000). Quasi-Monte Carlo Algorithm for Pricing Options. Economic Analysis Review, 15(1), 111–119. Retrieved from https://www.rae-ear.org/index.php/rae/article/view/100

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