Paper #597

Título:

Variance reduction methods for simulation of densities on Wiener space

Autores:

Arturo Kohatsu y Roger Pettersson

Fecha:

Enero 2002

Resumen:

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.

Palabras clave:

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

Códigos JEL:

G13

Área de investigación:

Estadística, Econometría y Métodos Cuantitativos

Publicado en:

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

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