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Related papers: On martingale approximations

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In this paper, we develop necessary and sufficient conditions for the validity of a martingale approximation for the partial sums of a stationary process in terms of the maximum of consecutive errors. Such an approximation is useful for…

Probability · Mathematics 2011-02-11 Mikhail Gordin , Magda Peligrad

In this note, we study a condition introduced by Gordin and Lif{\v s}ic in 1981 to establish the Central Limit Theorem for additive functionals of stationary Markov chains with normal transition operator. In the more general setting of…

Probability · Mathematics 2025-10-24 Jèrôme Dedecker , Florence Merlevède

Approximations to sums of stationary and ergodic sequences by martingales are investigated. Necessary and sufficient conditions for such sums to be asymptotically normal conditionally given the past up to time 0 are obtained. It is first…

Probability · Mathematics 2007-05-23 Wei Biao Wu , Michael Woodroofe

Consider a Markov chain $\{X_n\}_{n\ge 0}$ with an ergodic probability measure $\pi$. Let $\Psi$ a function on the state space of the chain, with $\alpha$-tails with respect to $\pi$, $\alpha\in (0,2)$. We find sufficient conditions on the…

Probability · Mathematics 2009-12-15 Milton Jara , Tomasz Komorowski , Stefano Olla

In this paper, we obtain sufficient conditions in terms of projective criteria under which the partial sums of a stationary process with values in ${\mathcal{H}}$ (a real and separable Hilbert space) admits an approximation, in…

Probability · Mathematics 2014-02-27 Christophe Cuny , Florence Merlevède

We consider the decreasing and the increasing $r$-excessive functions $\varphi_r$ and $\psi_r$ that are associated with a one-dimensional conservative regular continuous strong Markov process $X$ with values in an interval with endpoints…

Probability · Mathematics 2016-12-28 Mikhail Urusov , Mihail Zervos

This paper is devoted to the study of quantitative weighted norm estimates for martingale square functions in both scalar-weighted and matrix-weighted settings. In particular, we introduce the martingale square functions $S_W$ via matrix…

Probability · Mathematics 2026-05-12 Wei Chen , Yong Jiao , Xingyan Quan , Lian Wu

In this paper we survey the almost sure central limit theorem and its functional form (quenched) for stationary and ergodic processes. For additive functionals of a stationary and ergodic Markov chain these theorems are known under the…

Probability · Mathematics 2013-04-17 Magda Peligrad

In this paper we estimate the rest of the approximation of a stationary process by a martingale in terms of the projections of partial sums. Then, based on this estimate, we obtain almost sure approximation of partial sums by a martingale…

Probability · Mathematics 2011-05-05 Florence Merlevède , Costel Peligrad , Magda Peligrad

We obtain a necessary and sufficient condition for the orthomartingale-coboundary decomposition. We establish a sufficient condition for the approximation of the partial sums of a strictly stationary random fields by those of stationary…

Probability · Mathematics 2020-03-10 Davide Giraudo

In this paper we survey and further study partial sums of a stationary process via approximation with a martingale with stationary differences. Such an approximation is useful for transferring from the martingale to the original process the…

Probability · Mathematics 2011-05-24 Magda Peligrad

We study limit theorems for partial sums of instantaneous functions of a homogeneous Markov chain on a general state space. The summands are heavy-tailed and the limits are stable distributions. The conditions imposed on the transition…

Probability · Mathematics 2018-08-14 Mohamed El Machkouri , Adam Jakubowski , Dalibor Volný

Let $(X_i)$ be a stationary and ergodic Markov chain with kernel $Q$, $f$ an $L^2$ function on its state space. If $Q$ is a normal operator and $f = (I-Q)^{1/2}g$ (which is equivalent to the convergence of $\sum_{n=1}^\infty…

Probability · Mathematics 2009-12-16 Dalibor Volný

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2015-11-06 Loïc Hervé , James Ledoux

In this paper we provide necessary and sufficient conditions for the mean square approximation of a random field with an ortho-martingale. The conditions are formulated in terms of projective criteria. Applications are given to linear and…

Probability · Mathematics 2017-08-30 Magda Peligrad , Na Zhang

Whereas classical invariance principles for ergodic Markov chains address the situation in which the time horizon of observations is much larger than the mixing time, the quality of approximation is questionable when this is not the case…

Probability · Mathematics 2026-05-12 Gabriele Bellerino , Angelika Rohde

We consider a sequence of additive functionals {\phi_n}, set on a sequence of Markov chains {X_n} that weakly converges to a Markov process X. We give sufficient condition for such a sequence to converge in distribution, formulated in terms…

Probability · Mathematics 2007-05-23 Yuri N. Kartashov , Alexey M. Kulik

Consider a real-valued branching random walk in the boundary case. Using the techniques developed by A\"id\'ekon and Shi [5], we give two integral tests which describe respectively the lower limits for the minimal position and the upper…

Probability · Mathematics 2015-07-01 Yueyun Hu

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2016-01-15 Loïc Hervé , James Ledoux

We prove that for a so-called sticky process $S$ there exists an equivalent probability $Q$ and a $Q$-martingale $\tilde{S}$ that is arbitrarily close to $S$ in $L^p(Q)$ norm. For continuous $S$, $\tilde{S}$ can be chosen arbitrarily close…

Mathematical Finance · Quantitative Finance 2017-03-03 Miklós Rásonyi , Hasanjan Sayit
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