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Infinitesimal robustness for diffusions

Publication St. Gallen: Department of Economics, University of St. Gallen, 2008
Description 49 p.
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.
Keywords Diffusion processesEigenexpansionInfinitesimal generatorInfluence functionM-estimatorsSaddle point approximation
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LA VECCHIA, Davide, TROJANI, Fabio. Infinitesimal robustness for diffusions. 2008 https://archive-ouverte.unige.ch/unige:75158

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Deposited on : 2015-09-13

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