Quasi-Monte Carlo Algorithm for Pricing Options

  • Jenny X. Li Pennsylvania State University


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.

Author Biography

Jenny X. Li, Pennsylvania State University
Department of Mathematics and Economics, Pennsylvania State University
How to Cite
Li, J. X. (1). 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