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LAMN property for hidden processes: the case of integrated diffusions

2 July 2007
A. Gloter
E. Gobet
ArXiv (abs)PDFHTML
Abstract

In this paper we prove the Local Asymptotic Mixed Normality (LAMN) property for the statistical model given by the observation of local means of a diffusion process XXX. Our data are given by ∫01Xs+in\ddμ(s) \int_0^1 X_{\frac{s+i}{n}} \dd \mu (s)∫01​Xns+i​​\ddμ(s) for i=0,...,n−1i=0,...,n-1i=0,...,n−1 and the unknown parameter appears in the diffusion coefficient of the process XXX only. Although the data are nor Markovian neither Gaussian we can write down, with help of Malliavin calculus, an explicit expression for the log-likelihood of the model, and then study the asymptotic expansion. We actually find that the asymptotic information of this model is the same one as for a usual discrete sampling of XXX.

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