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Parametric estimation for partially hidden diffusion processes sampled at discrete times

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Author Info
Stefano Iacus (Department of Economics, Business and Statistics, University of Milan, IT)
Masayuki Uchida (Departement of Mathematical Sciences, Faculty of Mathematics, Kyushu University, Ropponmatsu, Fukuoka 810-8560, Japan)
Nakahiro Yoshida (Graduate School of Mathematical Sciences, University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8914 Japan)

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Abstract

A one dimensional diffusion process $X=\{X_t, 0\leq t \leq T\}$ is observed only when its path lies over some threshold $\tau$. On the basis of the observable part of the trajectory, the problem is to estimate finite dimensional parameter in both drift and diffusion coefficient under a discrete sampling scheme. It is assumed that the sampling occurs at regularly spaced times intervals of length $h_n$ such that $h_n\cdot n =T$. The asymptotic is considered as $T\to\infty$, $n\to\infty$, $n h_n^2\to 0$. Consistency and asymptotic normality for estimators of parameters in both drift and diffusion coefficient is proved.

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Publisher Info
Paper provided by Universitá degli Studi di Milano in its series UNIMI - Research Papers in Economics, Business, and Statistics with number 1042.

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Date of creation: 12 Nov 2006
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Handle: RePEc:bep:unimip:1042

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Keywords: discrete observations partially observed systems diffusion processes

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