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We investigate a family of discrete-time stationary processes defined by multiple stable integrals and renewal processes with infinite means. The model may exhibit behaviors of short-range or long-range dependence, respectively, depending…

Probability · Mathematics 2022-12-29 Shuyang Bai , Yizao Wang

We study modified ruin probabilities in a Cram\'er-Lundberg model driven by a compound mixed Poisson process. In the heavy-tailed regime, if the integrated claim-size distribution is subexponential and the upper endpoint of the mixing…

Probability · Mathematics 2026-05-11 Noriyoshi Sakuma , Momoka Tashiro

The task for a general and useful classification of the tail behaviors of probability distributions still has no satisfactory solution. Due to lack of information outside the range of the data the tails of the distribution should be…

Probability · Mathematics 2019-07-23 Pavlina Jordanova

We consider the probability that a weighted sum of $n$ i.i.d. random variables $X_j$, $j = 1, . . ., n$, with stretched exponential tails is larger than its expectation and determine the rate of its decay, under suitable conditions on the…

Probability · Mathematics 2014-12-30 Nina Gantert , Kavita Ramanan , Franz Rembart

We characterize the second order subexponentiality of an infinitely divisible distribution on the real line under an exponential moment assumption. We investigate the asymptotic behaviour of the difference between the tails of an infinitely…

Probability · Mathematics 2020-01-30 Toshiro Watanabe

We prove tail estimates for variables $\sum_i f(X_i)$, where $(X_i)_i$ is the trajectory of a random walk on an undirected graph (or, equivalently, a reversible Markov chain). The estimates are in terms of the maximum of the function $f$,…

Probability · Mathematics 2007-12-25 Roy Wagner

We establish upper and lower bounds with matching leading terms for tails of weighted sums of two-sided exponential random variables. This extends Janson's recent results for one-sided exponentials.

Probability · Mathematics 2025-01-28 Jiawei Li , Tomasz Tkocz

We propose a stochastic process driven by memory effect with novel distributions including both exponential and leptokurtic heavy-tailed distributions. A class of distribution is analytically derived from the continuum limit of the discrete…

Statistical Finance · Quantitative Finance 2013-05-14 Jongwook Kim , Gabjin Oh

Model reduction of Markov processes is a basic problem in modeling state-transition systems. Motivated by the state aggregation approach rooted in control theory, we study the statistical state compression of a discrete-state Markov chain…

Machine Learning · Statistics 2019-11-26 Anru Zhang , Mengdi Wang

This paper describes limiting behaviour of tail empirical process associated with long memory stochastic volatility models. We show that such process has dichotomous behaviour, according to an interplay between a Hurst parameter and a tail…

Statistics Theory · Mathematics 2010-11-23 Rafal Kulik , Philippe Soulier

We consider the 2D Landau Hamiltonian $H$ perturbed by a random alloy-type potential, and investigate the Lifshitz tails, i.e. the asymptotic behavior of the corresponding integrated density of states (IDS) near the edges in the spectrum of…

Mathematical Physics · Physics 2016-08-16 Frédéric Klopp , Georgi Raikov

We examine random variables in the power law/regularly varying class with stochastic tail exponent, the exponent $\alpha$ having its own distribution. We show the effect of stochasticity of $\alpha$ on the expectation and higher moments of…

Statistical Finance · Quantitative Finance 2017-04-06 Nassim Nicholas Taleb

Random multiplicative growth with redistribution generates stationary Pareto wealth tails in the Bouchaud-M\'ezard model, but assumes a fixed multiplicative noise intensity. This is restrictive for physical and financial growth processes,…

Disordered Systems and Neural Networks · Physics 2026-05-20 Maxence Arutkin , Alexandre Vallée

Motivated by a risk process with positive and negative premium rates, we consider a real-valued Markov additive process with finitely many background states. This additive process linearly increases or decreases while the background state…

Probability · Mathematics 2008-08-21 Masakiyo Miyazawa

This paper quantifies the ergodicity and the rate of decay of the tail of the stationary distribution for a broad class of storage models, encompassing constant, linear, and power-type release rates with both finite and infinite activity…

Probability · Mathematics 2025-11-19 Miha Brešar , Aleksandar Mijatović , Nikola Sandrić

We study the speed of extinction of continuous state branching processes in a L\'evy environment, where the associated L\'evy process oscillates. Assuming that the L\'evy process satisfies the Spitzer's condition and the existence of some…

Probability · Mathematics 2021-07-26 Vincent Bansaye , Juan Carlos Pardo , Charline Smadi

We study the properties of the exponential functional $\int\_0^{+ \infty} e^{- X^{\uparrow} (t)}dt$ where $X^{\uparrow}$ is a spectrally one-sided L{\'e}vy process conditioned to stay positive. In particular, we study finiteness,…

Probability · Mathematics 2019-11-27 Grégoire Véchambre , Grégoire Vechambre

To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and Warcho{\l} [Extremes (2015) 18, 369--402] proposed nonparametric estimators of the spectral tail process. The methodology can be extended…

Methodology · Statistics 2018-01-30 R. A. Davis , H. Drees , J. Segers , M. Warchoł

We consider two independent random variables with the given tail asymptotic (e.g. power or exponential). We find tail asymptotic for their sum and product. This is done by some cumbersome but purely technical computations and requires the…

Probability · Mathematics 2013-05-09 Andrey Sarantsev

We study heavy-tailed Hermitian random matrices that are unitarily invariant. The invariance implies that the eigenvalue and eigenvector statistics are decoupled. The motivating question has been whether a freely stable random matrix has…

Mathematical Physics · Physics 2021-09-27 Mario Kieburg , Adam Monteleone