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We study the problem of stationarity and ergodicity for autoregressive multinomial logistic time series models which possibly include a latent process and are defined by a GARCH-type recursive equation. We improve considerably upon the…

Statistics Theory · Mathematics 2018-10-02 Konstantinos Fokianos , Lionel Truquet

The first motivation of this paper is to study stationarity and ergodic properties for a general class of time series models defined conditional on an exogenous covariates process. The dynamic of these models is given by an autoregressive…

Statistics Theory · Mathematics 2020-07-16 Paul Doukhan , Michael H. Neumann , Lionel Truquet

A class of nonlinear ARCH processes is introduced and studied. The existence of a strictly stationary and $\beta$-mixing solution is established under a mild assumption on the density of the underlying independent process. We give…

Probability · Mathematics 2007-05-23 Youssef Sa\"{ı}di , Jean-Michel Zako\"{ı}an

In this article, after recalling and discussing the conventional extremality, local extremality, stationarity and approximate stationarity properties of collections of sets and the corresponding (extended) extremal principle, we focus on…

Optimization and Control · Mathematics 2018-05-15 Hoa T. Bui , Alexander Y. Kruger

This paper examines some probabilistic properties of the class of periodic GARCH processes (PGARCH) which feature periodicity in conditional heteroskedasticity. In these models, the parameters are allowed to switch between different…

Probability · Mathematics 2007-09-20 Abdelouahab Bibi , Abdelhakim Aknouche

In time-series analyses, particularly for finance, generalized autoregressive conditional heteroscedasticity (GARCH) models are widely applied statistical tools for modelling volatility clusters (i.e., periods of increased or decreased…

Methodology · Statistics 2023-10-24 Philipp Otto , Wolfgang Schmid

We provide conditions for the existence and the unicity of strictly stationary solutions of the usual Dynamic Conditional Correlation GARCH models (DCC-GARCH). The proof is based on Tweedie's (1988) criteria, after having rewritten…

Mathematical Finance · Quantitative Finance 2016-03-30 Jean-David Fermanian , Hassan Malongo

The AutoRegressive Conditional Heteroskedasticity (ARCH) and its generalized version (GARCH) family of models have grown to encompass a wide range of specifications, each of them is designed to enhance the ability of the model to capture…

Data Analysis, Statistics and Probability · Physics 2007-05-23 G. R. Jafari , A. Bahraminasab , P. Norouzzadeh

There is a serious and long-standing restriction in the literature on heavy-tailed phenomena in that moment conditions, which are unrealistic, are almost always assumed in modelling such phenomena. Further, the issue of stability is often…

Methodology · Statistics 2024-10-02 Yuxin Tao , Dong Li

Conditions for the existence of strictly stationary multivariate GARCH processes in the so-called BEKK parametrisation, which is the most general form of multivariate GARCH processes typically used in applications, and for their geometric…

Probability · Mathematics 2011-08-02 Farid Boussama , Florian Fuchs , Robert Stelzer

Orthogonal Generalized Autoregressive Conditional Heteroskedasticity model (OGARCH) is widely used in finance industry to produce volatility and correlation forecasts. We show that the classic OGARCH model, nevertheless, tends to be too…

Methodology · Statistics 2019-09-27 Yufan Li

This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on multiplicative volatility dynamics without positivity constraints. We compare the main probabilistic properties (strict…

Statistics Theory · Mathematics 2013-04-11 Christian Francq , Olivier Wintenberger , Jean-Michel Zakoïan

This paper introduces a spatiotemporal exponential generalised autoregressive conditional heteroscedasticity (spatiotemporal E-GARCH) model, extending traditional spatiotemporal GARCH models by incorporating asymmetric volatility…

Applications · Statistics 2025-11-10 Ariane Nidelle Meli Chrisko , Philipp Otto , Wolfgang Schmid

We derive mixing properties for a broad class of Poisson count time series satisfying a certain contraction condition. Using specific coupling techniques, we prove absolute regularity at a geometric rate not only for stationary…

Probability · Mathematics 2021-04-08 Paul Doukhan , Anne Leucht , Michael H Neumann

It is now widely accepted that volatility models have to incorporate the so-called leverage effect in order to to model the dynamics of daily financial returns.We suggest a new class of multivariate power transformed asymmetric models. It…

Statistics Theory · Mathematics 2019-10-17 Yacouba Boubacar Maïnassara , Othman Kadmiri , Bruno Saussereau

The Lyapounov exponent and sharp conditions for geometric ergodicity are determined of a time series model with both a threshold autoregression term and threshold autoregressive conditional heteroscedastic (ARCH) errors. The conditions…

Probability · Mathematics 2016-09-07 Daren B. H. Cline , Huay-min H. Pu

One of the important and widely used classes of models for non-Gaussian time series is the generalized autoregressive model average models (GARMA), which specifies an ARMA structure for the conditional mean process of the underlying time…

Methodology · Statistics 2021-05-13 Tingguo Zheng , Han Xiao , Rong Chen

This paper studies goodness of fit tests and specification tests for an extension of the log-GARCH model which is stable by scaling. A Lagrange-Multiplier test is derived for testing the null assumption of extended log-GARCH against more…

Statistics Theory · Mathematics 2016-06-07 Christian Francq , Olivier Wintenberger , Jean-Michel Zakoïan

This article aims to introduced a new distribution named as extended xgamma (EXg) distribution. This generalization is derived from xgamma distribution (Xg), a special finite mixture of exponential and gamma distributions [see, Sen et al.…

Statistics Theory · Mathematics 2019-09-04 Mahendra Saha , Abhimanyu Singh Yadav , Arvind Pandey , Shivanshi Shukla , Sudhansu S Maiti

Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financial data. To address this gap, we propose a…

Methodology · Statistics 2023-06-09 Cheng Yu , Dong Li , Feiyu Jiang , Ke Zhu
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