Infinitesimal Robustness for Diffusions
Journal
Journal of the American Statistical Association
Type
journal article
Date Issued
2010-03-03
Author(s)
Abstract
We develop infinitesimally robust statistical procedures for the general diffusion processes. We first prove the existence and uniqueness of the times-series influence function of conditionally unbiased M-estimators for ergodic and stationary diffusions, under weak conditions on the (martingale) estimating function used. We then characterize the robustness of M-estimators for diffusions and derive a class of conditionally unbiased optimal robust estimators. To compute these estimators, we propose a general algorithm, which exploits approximation methods for diffusions in the computation of the robust estimating function. Monte Carlo simulation shows a good performance of our robust estimators and an application to the robust estimation of the exchange rate dynamics within a target zone illustrates the methodology in a real-data application.
Language
English
Keywords
Diffusion processes
Eigenexpansion
Infinitesimal generator
Influence function
M-estimators
Saddlepoint approximation
HSG Classification
contribution to scientific community
Refereed
No
Publisher
Taylor & Francis
Volume
490
Number
105
Start page
703
End page
712
Pages
10
Subject(s)
Division(s)
Eprints ID
229744