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Infinitesimal robustness for diffusions

Publication Zürich: NCCR FINRISK National Centre of Competence in Research - Financial Valuation and Risk Management, 2008
Description 45 p.
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 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 processesEigenexpansionInfluence functionInfinitesimal generatorM-estimatorsSaddle point approximation
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LA VECCHIA, Davide, TROJANI, Fabio. Infinitesimal robustness for diffusions. 2008 https://archive-ouverte.unige.ch/unige:75159

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Deposited on : 2015-09-13

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