Variance Reduction and Efficiency of Monte Carlo Simulation in Financial Model

Abstract

In recent years, finance specialists have described several phenomena and they are developing calculation methods thanks to mathematical tools that are becoming more and more sophisticated. Thus, our research aims to use in a practical way the main operating techniques of the Monte Carlo simulation applied to finance. This article presents the Monte Carlo method as part of the simulation of the stochastic model in finance. Note that the use of this method often represents an extra cost in calculation that should be taken into account in the study of performance. Indeed, the method is not effective when the variance is too high. A technique of variance reduction is the solution to reduce the variability of the estimators and consequently reduce the simulation time. A reduction of the variance can only be accomplished by means of knowledge of information, which can be quantitative or qualitative on the studied phenomenon. The more information we have, the lower the variability of the estimator is likely to be.