Variance reduction techniques and quasi-Monte Carlo methods

Variance Reduction Techniques in Monte Carlo Methods

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the introduction of computers. This increased computer power has stimulated simulation analysts to develo...

A Computational Approach to Financial Option Pricing Using Quasi Monte Carlo Methods via Variance Reduction Techniques

In this paper, we consider two types of pricing option in financial markets using quasi Monte Carlo algorithm with variance reduction procedures. We evaluate Asian-style and European-style options pricing based on Black-Scholes model. Finally, some numerical results presented.

Monte Carlo and quasi-Monte Carlo methods

Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~^), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Ca...

Monte Carlo calculation of specific absorbed fractions: variance reduction techniques.

The purpose of the present work is to calculate specific absorbed fractions using variance reduction techniques and assess the effectiveness of these techniques in improving the efficiency (i.e. reducing the statistical uncertainties) of simulation results in cases where the distance between the source and the target organs is large and/or the target organ is small. The variance reduction techn...

Monte Carlo Integration and Variance Reduction