Imagen de Portada
Código QR

Asymptotic properties of Monte Carlo estimators of diffusion processes.

This paper studies the limit distributions of Monte Carlo estimators of diffusion processes. We examine two types of estimators based on the Euler scheme, one applied to the original processes, the other to a Doss transformation of the processes. We show that the transformation increases the speed o...

Descripción completa

Publicado en:Journal of Econometrics Vol. 134; no. 1; pp. 1 - 69
Autores principales: Detemple, Jérôme, Garcia, René, Rindisbacher, Marcel
Formato: Artículo
Publicado: Elsevier Science September 2006
Materias:
Difference equations
Estimation theory
Monte Carlo method
Mathematical transformations
Diffusion processes
Acceso en línea:Ver este registro en EBSCOhost
Sumario:This paper studies the limit distributions of Monte Carlo estimators of diffusion processes. We examine two types of estimators based on the Euler scheme, one applied to the original processes, the other to a Doss transformation of the processes. We show that the transformation increases the speed of convergence of the Euler scheme. We also study estimators of conditional expectations of diffusions. After characterizing expected approximation errors, we construct second-order bias-corrected estimators. We also derive new convergence results for the Mihlstein scheme. Illustrations of the results are provided in the context of simulation-based estimation of diffusion processes. Copyright (c) 2006 Elsevier B.V.