Dynamic latent factor models for intensity processes

Luc Bauwens and Nikolaus Hautsch

No 2003103, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: This paper introduces a new framework for the dynamic modelling of univariate and multivariate point processes. The so-called latent factor intensity (LFI) model is based on the assumption that the intensity function consists of univariate or multivariate observation driven dynamic components and a univariate dynamic latent factor. In this sense, the model corresponds to a dynamic extension of a doubly stochastic Poisson process. We illustrate alternative parameterizations of the observation driven component based on autoregressive conditional intensity (ACI) specifications, as well as Hawkes types models. Based on simulation studies, it is shown that the proposed model provides a flexible tool to capture the joint dynamics of multivariate point processes. Since the latent component has to be integrated out, the model is estimated by simulated maximum likelihood based upon efficient importance sampling techniques. Applications of univariate and bivariate LFI models to transaction data extracted from the German XETRA trading system provide evidence for an improvement of the econometric specification when observable as well as unobservable dynamic components are taken into account.

Keywords: multivariate point process; latent factor; transaction durations; efficient importance sampling (search for similar items in EconPapers)
JEL-codes: C22 C32 C41 (search for similar items in EconPapers)
Date: 2003-12
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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