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In this note we explain two transitions known for moment generating functions of local times by means of properties of the renewal measure of a related renewal equation. The arguments simplify and strengthen results on the asymptotic…

Probability · Mathematics 2011-06-29 Leif Doering , Mladen Savov

In this paper, we derive tail approximations of integrals of exponential functions of Gaussian random fields with varying mean functions and approximations of the associated point processes. This study is motivated naturally by multiple…

Statistics Theory · Mathematics 2011-12-05 Jingchen Liu , Gongjun Xu

We obtain in this paper a non-asymptotic non-improvable up to multiplicative constant moment and exponential tail estimates for distribution for U-statistics by means of martingale representation. We show also the exactness of obtained…

Statistics Theory · Mathematics 2016-02-02 E. Ostrovsky , L. Sirota

In this paper non-asymptotic exponential and moment estimates are derived for tail of distribution for discrete time martingale and martingale transform by means of martingale differences in the terms of moments and tails of distributions…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

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 determine the rate of decrease of the right tail distribution of the exponential functional of a Levy process with a convolution equivalent Levy measure. Our main result establishes that it decreases as the right tail of the image under…

Probability · Mathematics 2016-08-14 Víctor Rivero

Existing theory for multivariate extreme values focuses upon characterizations of the distributional tails when all components of a random vector, standardized to identical margins, grow at the same rate. In this paper, we consider the…

Statistics Theory · Mathematics 2013-12-20 J. L. Wadsworth , J. A. Tawn

We establish sharp tail asymptotics for component-wise extreme values of bivariate Gaussian random vectors with arbitrary correlation between the components. We consider two scaling regimes for the tail event in which we demonstrate the…

Probability · Mathematics 2019-03-28 Remco van der Hofstad , Harsha Honnappa

Given the discrete-time sequence of nonnegative random variables, general dependencies between the exponential convergence of the expectations, exponential convergence of the trajectories and the logarithmic growth of the corresponding…

Probability · Mathematics 2024-08-06 Dawid Tarłowski

In a recent article the authors obtained a formula which relates explicitly the tail of risk neutral returns with the wing behavior of the Black Scholes implied volatility smile. In situations where precise tail asymptotics are unknown but…

Probability · Mathematics 2007-05-23 Shalom Benaim , Peter Friz

We consider the tail behavior of random variables $R$ which are solutions of the distributional equation $R\stackrel{d}{=}Q+MR$, where $(Q,M)$ is independent of $R$ and $|M|\le 1$. Goldie and Gr\"{u}bel showed that the tails of $R$ are no…

Probability · Mathematics 2010-02-08 Paweł Hitczenko , Jacek Wesołowski

The class of subweibull distributions has recently been shown to generalize the important properties of subexponential and subgaussian random variables. We describe alternative characterizations of subweibull distributions and detail the…

Probability · Mathematics 2025-11-12 F. William Townes

We consider the large deviations associated with the empirical mean of independent and identically distributed random variables under a subexponential moment condition. We show that non-trivial deviations are observable at a subexponential…

Probability · Mathematics 2025-07-22 Grégoire Ferré

This is Part II of our work about random tensor inequalities and tail bounds for bivariate random tensor means. After reviewing basic facts about random tensors, we first consider tail bounds with more general connection functions. Then, a…

Probability · Mathematics 2023-05-08 Shih-Yu Chang

We derive in this short report the exponential as well as power decreasing tail estimations for the sums of centered exchangeable random variables, alike ones for the sums of the centered independent ones.

Probability · Mathematics 2022-06-02 M. R. Formica , E. Ostrovsky , L. Sirota

Recent work on random growth models with light-tailed Markov-modulated additive shocks has shown that irreducible modulation yields tail behavior resembling an exponential distribution. We show that with reducible modulation the tail…

Probability · Mathematics 2026-05-07 Brendan K. Beare , Alexis Akira Toda

Self-normalized processes arise naturally in statistical applications. Being unit free, they are not affected by scale changes. Moreover, self-normalization often eliminates or weakens moment assumptions. In this paper we present several…

Probability · Mathematics 2007-05-23 Victor H. de la Pena , Michael J. Klass , Tze Leung Lai

Heavy-tailed fluctuations and power law statistics pervade physics, finance, and economics, yet their origin is often ascribed to systems poised near criticality. Here we show that such behavior can emerge far from instability through a…

Statistical Mechanics · Physics 2025-10-15 Virgile Troude , Didier Sornette

We derive in this article the exact non-asymptotical exponential and power estimates for self-normalized sums of centered independent random variables (r.v.) under natural norming. We will use also the theory of the so-called Grand Lebesgue…

Probability · Mathematics 2018-09-25 E. Ostrovsky , L. Sirota

Exponential, and not Gaussian, decay of probability density functions was studied by Laplace in the context of his analysis of errors. Such Laplace propagators for the diffusive motion of single particles in disordered media were recently…

Statistical Mechanics · Physics 2022-09-09 Stanislav Burov , Wanli Wang , Eli Barkai