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The estimation of multivariate GARCH time series models is a difficult task mainly due to the significant overparameterization exhibited by the problem and usually referred to as the "curse of dimensionality". For example, in the case of…

Computational Finance · Quantitative Finance 2011-01-31 Stéphane Chrétien , Juan-Pablo Ortega

The asymptotic theory of various estimators based on Gaussian likelihood has been developed for the unit root and near unit root cases of a first-order moving average model. Previous studies of the MA(1) unit root problem rely on the…

Statistics Theory · Mathematics 2012-03-13 Richard A. Davis , Li Song

In this paper, we prove the moderate deviations principle (MDP) for a general system of slow-fast dynamics. We provide a unified approach, based on weak convergence ideas and stochastic control arguments, that cover both the averaging and…

Probability · Mathematics 2017-06-02 Matthew R. Morse , Konstantinos Spiliopoulos

In this paper we study the conditional limit theorems for critical continuous-state branching processes with branching mechanism $\psi(\lambda)=\lambda^{1+\alpha}L(1/\lambda)$ where $\alpha\in [0,1]$ and $L$ is slowly varying at $\infty$.…

Probability · Mathematics 2015-06-17 Yan-Xia Ren , Ting Yang , Guo-Huan Zhao

In the present paper, we consider the linear autoregressive model in $\rr$, $$ X_{k,n}=\theta_n X_{k,n-1}+\xi_k, k=0,1,...,n, n\ge 1$$ where $\theta_n\in [0,1)$ is unknown, $(\xi_k)_{k\in\zz}$ is a sequence of centered i.i.d. r.v. valued in…

Probability · Mathematics 2012-07-18 Yu Miao , Yanling Wang , Guangyu Yang

The density-dependent Markov chain (DDMC) introduced in \cite{Kurtz1978} is a continuous time Markov process applied in fields such as epidemics, chemical reactions and so on. In this paper, we give moderate deviation principles of paths of…

Probability · Mathematics 2020-05-26 Xiaofeng Xue

This paper considers a semiparametric generalized autoregressive conditional heteroskedasticity (S-GARCH) model. For this model, we first estimate the time-varying long run component for unconditional variance by the kernel estimator, and…

Methodology · Statistics 2020-10-05 Feiyu Jiang , Dong Li , Ke Zhu

Consider the product $G_{n}=g_{n} ... g_{1}$ of the random matrices $g_{1},...,g_{n}$ in $GL(d,\mathbb{R}) $ and the random process $ G_{n}v=g_{n}... g_{1}v$ in $\mathbb{R}^{d}$ starting at point $v\in \mathbb{R}^{d}\smallsetminus \{0\} .$…

Probability · Mathematics 2024-12-23 Ion Grama , Emile Le Page , Marc Peigné

For any 0 < alpha <2, a truncated symmetric alpha-stable process is a symmetric Levy process in R^d with a Levy density given by c|x|^{-d-alpha} 1_{|x|< 1} for some constant c. In this paper we study the potential theory of truncated…

Probability · Mathematics 2007-05-23 Panki Kim , Renming Song

We present limit theorems for a sequence of Piecewise Deterministic Markov Processes (PDMPs) taking values in a separable Hilbert space. This class of processes provides a rigorous framework for stochastic spatial models in which discrete…

Probability · Mathematics 2012-04-13 Martin G. Riedler , Michèle Thieullen , Gilles Wainrib

The limiting behavior of Toeplitz type quadratic forms of stationary processes has received much attention through decades, particularly due to its importance in statistical estimation of the spectrum. In the present paper we study such…

Probability · Mathematics 2018-08-20 Mikkel Slot Nielsen , Jan Pedersen

For the multivariate COGARCH(1,1) volatility process we show sufficient conditions for the existence of a unique stationary distribution, for the geometric ergodicity and for the finiteness of moments of the stationary distribution by a…

Probability · Mathematics 2019-10-01 Robert Stelzer , Johanna Vestweber

This paper develops a unified finite-time theory for the ordinary least squares estimation of possibly unstable and even slightly explosive vector autoregressive models under linear restrictions, with the applicable region $\rho(A)\leq…

Statistics Theory · Mathematics 2020-05-19 Yao Zheng , Guang Cheng

In this paper, we prove a central limit theorem and estabilish a moderate deviation principle for stochastic models of incompressible second fluids. The weak convergence method inreoduced by [4] plays an important role.

Probability · Mathematics 2016-08-01 Jianliang Zhai , Tusheng Zhang , Wuting Zheng

This paper is devoted to establish an invariance principle where the limit process is a multifractional Gaussian process with a multifractional function which takes its values in $(1/2,1)$. Some properties, such as regularity and local…

Probability · Mathematics 2009-09-29 Serge Cohen , Renaud Marty

This paper studies one-dimensional Ornstein-Uhlenbeck processes, with the distinguishing feature that they are reflected on a single boundary (put at level 0) or two boundaries (put at levels 0 and d>0). In the literature they are referred…

Probability · Mathematics 2014-07-03 Gang Huang , Michel Mandjes , Peter Spreij

We are interested in a fragmentation process. We observe fragments frozen when their sizes are less than $\epsilon$ ($\epsilon$ > 0). Is is known ([BM05]) that the empirical measure of these fragments converges in law, under some…

Probability · Mathematics 2019-07-30 Sylvain Rubenthaler

We study moderate deviations of suprema of parametrized sequences of sample bounded Gaussian processes $\{X _x(t), t\in T _x\}$, and first present recent sharp bounds in simple cases. In the almost periodic case, we prove an approximation…

Probability · Mathematics 2026-01-22 Michel Weber

We extend the spectral method for proving limit theorems to random non-uniformly expanding dynamical systems. This yields the CLT and moderate deviations principles (MDP). We show that as the amount of non-uniformity decreases the CLT rates…

Dynamical Systems · Mathematics 2024-08-14 Yeor Hafouta

We prove a law of large numbers and functional central limit theorem for a class of multivariate Hawkes processes with time-dependent reproduction rate. We address the difficulties induced by the use of non-convolutive Volterra processes by…

Probability · Mathematics 2025-01-30 Thomas Deschatre , Pierre Gruet , Antoine Lotz