Infinitesimal robustness for diffusions
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La Vecchia, Davide
Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
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Trojani, Fabio
Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
Published in:
- Journal of the american statistical association. - American statistical association. - 2010, vol. 105, no. 490, p. 703–712
English
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.
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Economics
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License undefined
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green
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https://n2t.net/ark:/12658/srd1318381
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