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The upper extremes of a Markov chain with regulary varying stationary marginal distribution are known to exhibit under general conditions a multiplicative random walk structure called the tail chain. More generally, if the Markov chain is…

Probability · Mathematics 2007-06-13 Johan Segers

Identifying groups of variables that may be large simultaneously amounts to finding out which joint tail dependence coefficients of a multivariate distribution are positive. The asymptotic distribution of a vector of nonparametric,…

Methodology · Statistics 2018-02-28 Maël Chiapino , Anne Sabourin , Johan Segers

We study the problem of heavy-tailed mean estimation in settings where the variance of the data-generating distribution does not exist. Concretely, given a sample $\mathbf{X} = \{X_i\}_{i = 1}^n$ from a distribution $\mathcal{D}$ over…

Statistics Theory · Mathematics 2020-12-10 Yeshwanth Cherapanamjeri , Nilesh Tripuraneni , Peter L. Bartlett , Michael I. Jordan

Let $\{\xi_1,\xi_2,\ldots\}$ be a sequence of independent random variables, and $\eta$ be a counting random variable independent of this sequence. In addition, let $S_0:=0$ and $S_n:=\xi_1+\xi_2+\cdots+\xi_n$ for $n\geqslant1$. We consider…

Probability · Mathematics 2017-04-10 Ieva Marija Andrulytė , Martynas Manstavičius , Jonas Šiaulys

We prove a large deviation principle for the sum of n independent heavy-tailed random variables, which are subject to a moving cut-off boundary at location n. Conditional on the sum being large at scale n, we show that a finite number of…

Probability · Mathematics 2024-12-17 Céline Kerriou , Peter Mörters

The size that an epidemic can reach, measured in terms of the number of fatalities, is an extremely relevant quantity. It has been recently claimed [Cirillo & Taleb, Nature Physics 2020] that the size distribution of major epidemics in…

Physics and Society · Physics 2021-03-18 Alvaro Corral

Given $n$ samples of a regular discrete distribution $\pi$, we prove in this article first a serial of SLLNs results (of Dvoretzky and Erd\"{o}s' type) which implies a typical power law when $\pi$ is heavy-tailed. Constructing a (random)…

Probability · Mathematics 2013-12-12 Xin-Xing Chen , Jian-Sheng Xie , Jiangang Ying

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

We attempt to bring some modest unity to three subareas of heavy tail analysis and extreme value theory: limit laws for componentwise maxima of iid random variables;hidden regular variation and asymptotic independence;conditioned limit laws…

Probability · Mathematics 2009-09-29 Sidney I. Resnick

It is well-known that the expected scaled maximum of non-negative random variables with unit mean defines a stable tail dependence function associated with some extreme-value copula. In the special case when these random variables are…

Methodology · Statistics 2018-05-30 Jan-Frederik Mai

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

In this work, we establish risk bounds for the Empirical Risk Minimization (ERM) with both dependent and heavy-tailed data-generating processes. We do so by extending the seminal works of Mendelson [Men15, Men18] on the analysis of ERM with…

Statistics Theory · Mathematics 2021-09-14 Abhishek Roy , Krishnakumar Balasubramanian , Murat A. Erdogdu

Models for extreme values are generally derived from limit results, which are meant to be good enough approximations when applied to finite samples. Depending on the speed of convergence of the process underlying the data, these…

Statistics Theory · Mathematics 2019-02-20 Thomas Lugrin , Anthony C. Davison , Jonathan A. Tawn

The masses of data now available have opened up the prospect of discovering weak signals using machine-learning algorithms, with a view to predictive or interpretation tasks. As this survey of recent results attempts to show, bringing…

Statistics Theory · Mathematics 2026-05-06 Stephan Clémençon , Anne Sabourin

We study the long-time behavior of the scaled walker (particle) position associated with decoupled continuous-time random walk which is characterized by superheavy-tailed distribution of waiting times and asymmetric heavy-tailed…

Statistical Mechanics · Physics 2013-02-19 S. I. Denisov , Yu. S. Bystrik , H. Kantz

Score-based diffusion models have become a powerful framework for generative modeling, with score estimation as a central statistical bottleneck. Existing guarantees for score estimation largely focus on light-tailed targets or rely on…

Statistics Theory · Mathematics 2026-01-13 Yifeng Yu , Lu Yu

Stochastic volatility processes with heavy-tailed innovations are a well-known model for financial time series. In these models, the extremes of the log returns are mainly driven by the extremes of the i.i.d. innovation sequence which leads…

Probability · Mathematics 2016-03-25 Anja Janssen , Holger Drees

In this paper, we investigate the extreme-value methodology, to propose an improved estimator of the conditional tail expectation ($CTE$) for a loss distribution with a finite mean but infinite variance. The present work introduces a new…

Statistics Theory · Mathematics 2020-02-11 Mohamed Laidi , Abdelaziz Rassoul , Hamid Ould Rouis

In this paper we consider a stochastic model of perpetuity-type. In contrast to the classical affine perpetuity model of Kesten [12] and Goldie [8] all discount factors in the model are mutually independent. We prove that the tails of the…

Probability · Mathematics 2017-03-22 Thomas Mikosch , Mohsen Rezapour , Olivier Wintenberger

Motivated by seminal paper of Kozlov et al.(1975) we consider in this paper a branching process with a geometric offspring distribution parametrized by random success probability $A$ and immigration equals $1$ in each generation. In…

Probability · Mathematics 2019-07-31 Ayan Bhattacharya , Zbigniew Palmowski