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Two-stage non Gaussian QML estimation of GARCH models and testing the efficiency of the Gaussian QMLE

Francq, Christian; Lepage, Guillaume; Zakoïan, Jean-Michel - In: Journal of Econometrics 165 (2011) 2, pp. 246-257

In generalized autoregressive conditional heteroskedastic (GARCH) models, the standard identifiability assumption that …

Persistent link: https://www.econbiz.de/10011052290

Inference in non stationary asymmetric garch models

Francq, Christian; Zakoian, Jean-Michel - Volkswirtschaftliche Fakultät, … - 2013

This paper considers the statistical inference of the class of asymmetric power-transformed GARCH(1,1) models in …

Persistent link: https://www.econbiz.de/10011114151

Strict stationarity testing and estimation of explosive ARCH models

Francq, Christian; Zakoian, Jean-Michel - Volkswirtschaftliche Fakultät, … - 2010

tests developed for the ARCH(1) model are able to detect non-stationarity in more general GARCH models. A numerical …

Persistent link: https://www.econbiz.de/10008560969

Messung des Marktrisikos mit generalisierter autoregressiver bedingter heteroskedastischer Modellierung der Volatilität: Ein Vergleich univariater und multivariater Konzepte

Krasnosselski, Nikolai; Cremers, Heinz; Sanddorf, Walter - 2014

GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …

Persistent link: https://www.econbiz.de/10010331352

Messung des Marktrisikos mit generalisierter autoregressiver bedingter heteroskedastischer Modellierung der Volatilität: Ein Vergleich univariater und multivariater Konzepte

Krasnosselski, Nikolai; Cremers, Heinz; Sanddorf, Walter - Frankfurt School of Finance and Management - 2014

GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …

Persistent link: https://www.econbiz.de/10010985133

High frequency vs. daily resolution: The economic value of forecasting volatility models 2nd ed

Lilla, Francesca - 2017

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Persistent link: https://www.econbiz.de/10011819006

Messung des Marktrisikos mit generalisierter autoregressiver bedingter heteroskedastischer Modellierung der Volatilität : ein Vergleich univariater und multivariater Konzepte

Krasnosselski, Nikolai; Cremers, Heinz; Sanddorf, Walter - 2014

GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …

Persistent link: https://www.econbiz.de/10010237661

High frequency vs. daily resolution : the economic value of forecasting volatility models

Lilla, Francesca - 2016

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

Persistent link: https://www.econbiz.de/10011730304

High frequency vs. daily resolution : the economic value of forecasting volatility models 2nd ed

Lilla, Francesca - 2017

Persistent link: https://www.econbiz.de/10011674479

QML estimation of a class of multivariate GARCH models without moment conditions on the observed process

Francq, Christian; Zakoian, Jean-Michel - Volkswirtschaftliche Fakultät, … - 2010

parameters of a class of multivariate GARCH processes. The conditions are mild and coincide with the minimal ones in the … univariate case. In particular, contrary to the current literature on the estimation of multivariate GARCH models, no moment …

Persistent link: https://www.econbiz.de/10008615632