Infinitesimal Robustness for Diffusions

Davide La Vecchia () and Fabio Trojani ()

University of St. Gallen Department of Economics working paper series 2008 from Department of Economics, University of St. Gallen

Abstract: We develop infinitesimally robust statistical procedures for general diffusion processes. We first prove existence and uniqueness of the times series influence function of conditionally unbiased M–estimators for ergodic and stationary dffusions, 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 dffusions 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.

Keywords: Dffusion processes; Eigenexpansion; Influence Function; Infinitesimal Generator; M–Estimators; Saddle– point Approximation. (search for similar items in EconPapers)
JEL-codes: C13 C22 C32 (search for similar items in EconPapers)
Pages: 53 pages
Date: 2008-04
New Economics Papers: this item is included in nep-cba and nep-ecm
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Related works:
Journal Article: Infinitesimal Robustness for Diffusions (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:usg:dp2008:2008-09

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