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We obtain a number of new general properties, related to the closedness of the class of long-tailed distributions under convolutions, that are of interest themselves and may be applied in many models that deal with "plus" and/or "max"…

Probability · Mathematics 2015-11-24 Hui Xu , Sergey Foss , Yuebao Wang

We provide the exact large-time behavior of the tail distribution of the extinction time of a self-similar fragmentation process with a negative index of self-similarity, improving thus a previous result on the logarithmic asymptotic…

Probability · Mathematics 2021-11-16 Bénédicte Haas

Our paper is devoted to several problems from the field of modified divisors: namely exponential and infinitary divisors. We study the behaviour of modified divisors, sum-of-divisors and totient functions. Main results concern with the…

Number Theory · Mathematics 2014-06-24 Andrew V. Lelechenko

In this article the relation between the tail behaviours of a free regular infinitely divisible (positively supported) probability measure and its L\'evy measure is studied. An important example of such a measure is the compound free…

Probability · Mathematics 2018-10-05 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

We establish a new integral equation for the probability density of the exponential functional of a L\'evy process and provide a three-term (Wiener-Hopf type) factorisation of its law. We explain how these results complement the techniques…

Probability · Mathematics 2023-06-23 Jonas Arista , Víctor M. Rivero

This article focuses on properties of monotone convolutions. A criterion for infinite divisibility and time evolution of convolution semigroups are mainly studied. In particular, we clarify that many analogues of the classical results of…

Operator Algebras · Mathematics 2010-08-30 Takahiro Hasebe

The exact expression for the probability density $p_{_N}(x)$ for sums of a finite number $N$ of random independent terms is obtained. It is shown that the very tail of $p_{_N}(x)$ has a Gaussian form if and only if all the random terms are…

Probability · Mathematics 2013-05-29 Michael I. Tribelsky

In this paper we first provide several conditional limit theorems for L\'evy processes with negative drift and regularly varying tail. Then we apply them to study the asymptotic behavior of expectations of some exponential functionals of…

Probability · Mathematics 2020-05-29 Wei Xu

We propose an approach to compute the conditional moments of fat-tailed phenomena that, only looking at data, could be mistakenly considered as having infinite mean. This type of problems manifests itself when a random variable Y has a…

Applications · Statistics 2018-08-02 Nassim Nicholas Taleb , Pasquale Cirillo

We consider a new approach in the definition of two-dimensional heavy-tailed distributions. Namely, we introduce the classes of two-dimensional long-tailed, of twodimensional dominatedly varying and of two-dimensional consistently varying…

Probability · Mathematics 2025-06-25 Dimitrios G. Konstantinides , Charalampos D. Passalidis

This paper studies new classes of infinitely divisible distributions on R^d. Firstly, the connecting classes with a continuous parameter between the Jurek class and the class of selfdecomposable distributions are revisited. Secondly, the…

Probability · Mathematics 2009-09-11 Makoto Maejima , Muneya Matsui , Mayo Suzuki

Empirical distributions have their in-sample maxima as natural censoring. We look at the "hidden tail", that is, the part of the distribution in excess of the maximum for a sample size of $n$. Using extreme value theory, we examine the…

Statistical Finance · Quantitative Finance 2020-04-14 Nassim Nicholas Taleb

We consider a supercritical branching L\'evy process on the real line. Under mild moment assumptions on the number of offspring and their displacements, we prove a second-order limit theorem on the empirical mean position.

Probability · Mathematics 2020-11-25 David Cheek , Seva Shneer

We derive some estimates for the integral modulus of continuity of probability densities of infinitely divisible distributions. The paper is splitted into two parts. The first part deals with general infinitely divisible distributions. The…

Probability · Mathematics 2018-05-07 David Berger

We study the tail asymptotic of sub-exponential probability densities on the real line. Namely, we show that the n-fold convolution of a sub-exponential probability density on the real line is asymptotically equivalent to this density times…

Probability · Mathematics 2018-02-26 Dmitri Finkelshtein , Pasha Tkachov

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

The paper develops new methods of non-parametric estimation a compound Poisson distribution. Such a problem arise, in particular, in the inference of a Levy process recorded at equidistant time intervals. Our key estimator is based on…

Statistics Theory · Mathematics 2015-10-19 Alexey Lindo , Sergei Zuyev , Serik Sagitov

We consider the infinite divisibility of distributions of some well-known inverse subordinators. Using a tail probability bound, we establish that distributions of many of the inverse subordinators used in the literature are not infinitely…

Probability · Mathematics 2019-02-11 Arun Kumar , Erkan Nane

In the probability theory limit distributions (or probability measures) are often characterized by some convolution equations (factorization properties) rather than by Fourier transforms (the characteristic functionals). In fact, usually…

Probability · Mathematics 2013-07-24 Zbigniew J. Jurek

We investigate the relaxation of long-tailed distributions under stochastic dynamics that do not support such tails. Linear relaxation is found to be a borderline case in which long tails are exponentially suppressed in time but not…

Statistical Mechanics · Physics 2015-06-22 Christian Van den Broeck , Upendra Harbola , Raul Toral , Katja Lindenberg