Non-parametric adaptive estimation of the drift for a jump diffusion process

In this article, we consider a jump diffusion process (Xt)t≥0 observed at discrete times t=0,Δ,…,nΔ. The sampling interval Δ tends to 0 and nΔ tends to infinity. We assume that (Xt)t≥0 is ergodic, strictly stationary and exponentially β-mixing. We use a penalised least-square approach to compute two adaptive estimators of the drift function b. We provide bounds for the risks of the two estimators.

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Year of publication:	2014
Authors:	Schmisser, Émeline
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 124.2014, 1, p. 883-914
Publisher:	Elsevier
Subject:	Jump diffusions \| Nonparametric estimation \| Drift estimation \| Model selection

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011065125