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In this paper we study precise large deviations for the partial sums of a stationary sequence with a subexponential marginal distribution. Our main focus is on distributions which either have a regularly varying or a lognormal-type tail. We…

Probability · Mathematics 2020-09-15 Thomas Mikosch , Igor Rodionov

We study the large deviation function for the empirical measure of diffusing particles at one fixed position. We find that the large deviation function exhibits anomalous system size dependence in systems that satisfy the following…

Statistical Mechanics · Physics 2015-01-20 Naoto Shiraishi

We study the work fluctuations of a particle subjected to a deterministic drag force plus a random forcing whose statistics is of the L\'evy type. In the stationary regime, the probability density of the work is found to have ``fat''…

Statistical Mechanics · Physics 2007-09-02 H. Touchette , E. G. D. Cohen

A novel statistical method is proposed and investigated for estimating a heavy tailed density under mild smoothness assumptions. Statistical analyses of heavy-tailed distributions are susceptible to the problem of sparse information in the…

Methodology · Statistics 2022-11-18 Surya T Tokdar , Sheng Jiang , Erika L Cunningham

We develop an econometric framework integrating heavy-tailed Student's $t$ distributions with behavioral probability weighting while preserving infinite divisibility. Using 432{,}752 observations across 86 assets (2004--2024), we…

Mathematical Finance · Quantitative Finance 2025-11-21 Akash Deep , Svetlozar T. Rachev , Frank J. Fabozzi

We derive exponential bounds for tail of distribution for natural, i.e. under ordinary logarithm, normalized sums of arrays of random variables, not necessarily independent.

We present the elliptical processes -- a family of non-parametric probabilistic models that subsumes the Gaussian process and the Student-t process. This generalization includes a range of new fat-tailed behaviors yet retains computational…

Methodology · Statistics 2020-12-03 Maria Bånkestad , Jens Sjölund , Jalil Taghia , Thomas Schön

In a general class of one dimensional random differential equation the convergence of the distribution function of the solution to stationary state distribution is studied. In particular it is proved the boundedness respectively the…

Probability · Mathematics 2010-07-07 Gyorgy Steinbrecher , Xavier Garbet , Boris Weyssow

Real-world data are long-tailed, the lack of tail samples leads to a significant limitation in the generalization ability of the model. Although numerous approaches of class re-balancing perform well for moderate class imbalance problems,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Yanbiao Ma , Licheng Jiao , Fang Liu , Shuyuan Yang , Xu Liu , Puhua Chen

Large deviations for sums of i.i.d.\ random variables with stretched-exponential tails (also called Weibull or semi-exponential tails) have been well understood since the 60's, going back to Nagaev's seminal work. Many extensions in the…

Probability · Mathematics 2026-02-04 Nina Gantert , Joscha Prochno , Philipp Tuchel

Probabilistic forecasts comprehensively describe the uncertainty in the unknown future outcome, making them essential for decision making and risk management. While several methods have been introduced to evaluate probabilistic forecasts,…

Methodology · Statistics 2025-05-23 Sam Allen , Jonathan Koh , Johan Segers , Johanna Ziegel

Skew-elliptical distributions constitute a large class of multivariate distributions that account for both skewness and a variety of tail properties. This class has simpler representations in terms of densities rather than cumulative…

Probability · Mathematics 2019-01-21 Harry Joe , Haijun Li

We give explicit bounds for the tail probabilities for sums of independent geometric or exponential variables, possibly with different parameters.

Probability · Mathematics 2017-09-26 Svante Janson

The normal distribution and its perturbation has left an immense mark on the statistical literature. Hence, several generalized forms were developed to model different skewness, kurtosis, and body shapes. However, it is not easy to…

Methodology · Statistics 2019-12-10 Matthias Wagener , Mohammad Arashi

This paper discusses the use of fat-tailed distributions in catastrophe prediction as opposed to the more common use of the Normal Distribution.

Other Computer Science · Computer Science 2011-11-09 Louis Mello

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

We analyze quantitatively the effect of spurious multifractality induced by the presence of fat-tailed symmetric and asymmetric probability distributions of fluctuations in time series. In the presented approach different kinds of symmetric…

Computational Finance · Quantitative Finance 2018-05-31 Rafal Rak , Dariusz Grech

We investigate the Large Deviations properties of bootstrapped empirical measure with exchangeable weights. Our main result shows in great generality how the resulting rate function combines the LD properties of both the sample weights and…

Probability · Mathematics 2011-10-24 José Trashorras , Olivier Wintenberger

We introduce a new statistical tool (the TP-statistic and TE-statistic) designed specifically to compare the behavior of the sample tail of distributions with power-law and exponential tails as a function of the lower threshold u. One…

Computational Physics · Physics 2009-11-10 V. F. Pisarenko , D. Sornette

By using a probabilistic technique based on the exponential change of measure we find a precise tail asymptotic behavior of some perpetuities with distributions close to the Dickman distribution.

Probability · Mathematics 2026-04-17 Alexander Iksanov , Oleh Iksanov