Filtered Likelihood for Point Processes

K. Giesecke, G. Schwenkler
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引用次数: 20

Abstract

Point processes are widely used in finance and economics to model the timing of defaults, market transactions, unemployment spells, births, and a range of other events. We develop and analyze likelihood estimators for the parameters of a marked point process and incompletely observed explanatory factors that influence the arrival intensity and mark distribution. We establish an approximation to the likelihood and analyze the convergence and large-sample properties of the associated estimators. Numerical results illustrate the behavior of our estimators.
点过程的过滤似然
点过程在金融和经济学中被广泛用于对违约、市场交易、失业、出生和一系列其他事件的时间进行建模。我们开发并分析了标记点过程参数的似然估计,以及影响到达强度和标记分布的未完全观察到的解释因素。我们建立了似然估计的近似,并分析了相关估计的收敛性和大样本性质。数值结果说明了估计器的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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