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Tous les séminaires

Jeudi 28 Mai 2015

16h15 : Dennis KRISTENSEN (Univ. College London)
"Diffusion-Based Copulas : Identification and Inference"

 

17H30 : Sébastien LAURENT (AMSE-Aix Marseille Université)
Long Memory Through Marginalization of Large Systems and Hidden Cross-Section Dependence

  1. Dennis KRISTENSEN (Univ. College London)

DIFFUSION-BASED COPULAS : IDENTIFICATION AND INFERENCE


A new semiparametric approach for modelling nonlinear univariate diffusions is proposed, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class of semiparametric Markov diffusion models with parametric dynamic copulas and nonparametric marginal distributions. We provide primitive conditions for the identification of the UPD parameters together with the unknown transformation given a discrete sample. Semiparametric likelihood-based estimators of the UPD parameters are developed and we show that under regularity conditions both the parametric and nonparametric components converge with parametric rate towards Normal distributions.  

 

17H30 : Sébastien LAURENT (AMSE-Aix Marseille Université)

“LONG MEMORY THROUGH MARGINALIZATION OF LARGE SYSTEMS AND HIDDEN CROSS-SECTION DEPENDENCE”

This paper shows that large dimensional vector autoregressive (VAR) models of finite order can generate long memory in the marginalized univariate series. We derive high-level assumptions under which the final equation representation of a VAR(1) leads to univariate fractional white noises and verify the validity of these assumptions for two specific models. We consider the implications of our findings for the variances of asset returns where the so-called golden-rule of realized variances states that they tend always to exhibit fractional integration of a degree close to 0.4.