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Variance Reduction Techniques of Importance Sampling Monte Carlo Methods for Pricing Options
School of Finance, Shanghai University of Finance and Economics, Shanghai, China
School of Finance, Shanghai University of Finance and Economics, Shanghai, China
Department of Applied Mathematics, Shanghai University of Finance and Economics, Shanghai, China
- 1 School of Finance, Shanghai University of Finance and Economics, Shanghai, China
- 2 School of Finance, Shanghai University of Finance and Economics, Shanghai, China
- 3 Department of Applied Mathematics, Shanghai University of Finance and Economics, Shanghai, China
Journal of Mathematical Finance·Volume 03 (2013)·Pages 431–436·Published 17 October 2013·DOI10.4236/jmf.2013.34045
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Abstract
In this paper we discuss the importance sampling Monte Carlo methods for pricing options. The classical importance sampling method is used to eliminate the variance caused by the linear part of the logarithmic function of payoff. The variance caused by the quadratic part is reduced by stratified sampling. We eliminate both kinds of variances just by importance sampling. The corresponding space for the eigenvalues of the Hessian matrix of the logarithmic function of payoff is enlarged. Computational Simulation shows the high efficiency of the new method.
KeywordsMonte Carlo MethodImportance SamplingVariance ReductionOption Pricing
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