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arXiv 1402.4956math.PR
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带跳线性模型的LAN性质

LAN property for a linear model with jumps

Arturo Kohatsu-Higa, Eulalia Nualart, Ngoc Khue Tran

摘要:

本文考虑了一个由布朗运动和补偿泊松过程驱动的带跳的线性模型,模型的漂移和扩散系数及其强度均为未知参数.假设该过程在高频下离散观测,我们得到了局部渐近正态性(LAN)性质。为了得到这个结果,Malliavin演算和Girsanov定理被应用,以便将对数似然比写成条件期望的和,其中三角形阵列的中心极限定理可以被应用。

英文摘要:

In this paper, we consider a linear model with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its intensity are unknown parameters. Supposing that the process is observed discretely at high frequency we derive the local asymptotic normality (LAN) property. In order to obtain this result, Malliavin calculus and Girsanov's theorem are applied in order to write the log-likelihood ratio in terms of sums of conditional expectations, for which a central limit theorem for triangular arrays can be applied.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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