Paper #597

Title:

Variance reduction methods for simulation of densities on Wiener space

Authors:

Arturo Kohatsu and Roger Pettersson

Date:

January 2002

Abstract:

We develop a general error analysis framework for the Monte Carlo simulation of densities for functionals in Wiener space. We also study variance reduction methods with the help of Malliavin derivatives. For this, we give some general heuristic principles which are applied to diffusion processes. A comparison with kernel density estimates is made.

Keywords:

Stochastic differential equations, weak approximation, variance reduction, kernel density estimation

JEL codes:

G13

Area of Research:

Statistics, Econometrics and Quantitative Methods

Published in:

SIAM Journal of Numerical Analysis, 12, (2002) pp.423-476

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