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Inférence de modèles conditionnellement hétéroscédastiques avec variables exogènes

Abstract : This PhD Dissertation is dedicated to the study of probabilistic and statistical properties of volatility models augmented with exogenous variables. It consists of two parts which are summarized below. In the first part of this work, we study asymptotic behavior of the QMLE for the versatile class of the semi-strong PGARCH models augmented with exogenous variables. The main assumptions on the exogenous variables are the stationarity and the non-colinearity with the other explanatory variables of the volatility. For the asymptotic distribution of the QMLE, we investigated four different situations corresponding to strong or semi-strong models, and to parameters inside or at the boundary of the parameter space. When the GARCH-X parameter belongs to the interior of the parameter space, the asymptotic distribution of the QMLE is normal, whereas it is the projection of a normal distribution on a convex cone when one or several coefficients are equal to zero. For models with positive GARCH coefficients, the asymptotic distribution is obtained under very mild conditions, in particular, without any moment condition on the observed process. When the GARCH parameter stands at the boundary, fourth-order moment conditions are required for the information matrix to be finite. Our asymptotic results are obtained under conditions that are only marginally stronger than these optimal moment conditions, which extends and improves the results that existed for GARCH models without covariables. The second part is devoted to studying the influence of exogenous variables on the conditional covariance matrix of asset returns. Specifically, we consider BEKK models augmented with exogenous variables. The parameters are estimated by two methods which are called the variance targeting estimation and equation by equation estimation. Both methods allow us to reduce the curse of dimensionality which appears when modeling a conditional covariance matrix, particularly in the presence of exogenous variables. The consistency and the asymptotic distribution of these estimators are established under mild assumptions. In particular, the innovation is assumed to be a martingale difference instead of iid. Our results are illustrated by Monte Carlo experiences and the applications on real series.
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  • HAL Id : tel-01527888, version 1


Le Quyen Thieu. Inférence de modèles conditionnellement hétéroscédastiques avec variables exogènes. Statistiques [math.ST]. Université Pierre et Marie Curie - Paris VI, 2016. Français. ⟨NNT : 2016PA066260⟩. ⟨tel-01527888⟩



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