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Related papers: On Single Point Forecasts for Fat-Tailed Variables

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We introduce the \textsc{Tailed-Uniform} proposal distribution for generating training simulations in simulation-based inference. Instead of sampling parameters uniformly within bounded regions, we extend the distribution beyond prior…

Instrumentation and Methods for Astrophysics · Physics 2026-01-27 Chaipat Tirapongprasert , Matthew Ho

As the increasing application of AI in finance, this paper will leverage AI algorithms to examine tail risk and develop a model to alter tail risk to promote the stability of US financial markets, and enhance the resilience of the US…

Risk Management · Quantitative Finance 2025-08-08 Zong Ke , Yuchen Yin

We introduce a simple multiplicative model to describe the temporal behavior and the ultimate outcome of an epidemic. Our model accounts, in a minimalist way, for the competing influences of imposing public-health restrictions when the…

Physics and Society · Physics 2025-01-14 P. L. Krapivsky , S. Redner

We consider multivariate extreme value statistics for independent but nonidentically distributed random vectors. In particular, the data may have varying tail copulas and also heteroscedastic marginal distributions. Assuming smoothly…

Statistics Theory · Mathematics 2026-04-14 John H. J. Einmahl , Chen Zhou

The clarion call for causal reduction in the study of capital markets is intensifying. However, in self-referencing and open systems such as capital markets, the idea of unidirectional causation (if applicable) may be limiting at best, and…

General Finance · Quantitative Finance 2026-05-07 Daniel Polakow , Tim Gebbie , Emlyn Flint

Standard statistical analysis is unable to provide reliable confidence intervals on expectation values of probability distributions that do not satisfy the conditions of the central limit theorem. We present a regression-based estimator of…

Data Analysis, Statistics and Probability · Physics 2019-06-24 Pablo Lopez Rios , Gareth J. Conduit

In extreme value analysis, tail behavior of a heavy-tailed data distribution is modeled by a Pareto-type distribution in which the so-called extreme value index (EVI) controls the tail behavior. For heavy-tailed data obtained from multiple…

Methodology · Statistics 2026-01-08 Koki Momoki , Takuma Yoshida

Measures of tail dependence between random variables aim to numerically quantify the degree of association between their extreme realizations. Existing tail dependence coefficients (TDCs) are based on an asymptotic analysis of relevant…

Applications · Statistics 2021-06-11 Davide Lauria , Svetlozar T. Rachev , A. Alexandre Trindade

Reliable short term forecasting can provide potentially lifesaving insights into logistical planning, and in particular, into the optimal allocation of resources such as hospital staff and equipment. By reinterpreting COVID-19 daily cases…

Populations and Evolution · Quantitative Biology 2025-11-06 Yi Liang , James Unwin

US public health authorities claim imposing quarantines on healthcare workers returning from West Africa is incorrect according to science. Their positions rely upon a set of studies and experience about outbreaks and transmission…

Physics and Society · Physics 2014-11-07 Yaneer Bar-Yam

In this paper we discuss the problem of the estimation of extreme event occurrence probability for data drawn from some multifractal process. We also study the heavy (power-law) tail behavior of probability density function associated with…

Statistical Mechanics · Physics 2009-11-11 Jean-Francois Muzy , Emmanuel Bacry , Alexey Kozhemyak

Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237-249], where at least a finite second moment is required. This excludes some important distributions, for example, those in the…

Statistics Theory · Mathematics 2007-06-13 Liang Peng

COVID-19 pandemic has brought to the fore epidemiological models which, though describing a wealth of behaviors, have previously received little attention in signal processing literature. In this work, a generalized time-varying…

Methodology · Statistics 2025-08-13 Barbara Pascal , Samuel Vaiter

In many areas of interest, modern risk assessment requires estimation of the extremal behaviour of sums of random variables. We derive the first order upper-tail behaviour of the weighted sum of bivariate random variables under weak…

Statistics Theory · Mathematics 2022-08-17 Jordan Richards , Jonathan A. Tawn

We propose an analytical approach to the computation of tail probabilities of compound distributions whose individual components have heavy tails. Our approach is based on the contour integration method, and gives rise to a representation…

Computational Finance · Quantitative Finance 2017-10-04 Igor Halperin

Just like the degrees of human and animal interaction networks, the distribution of the times between interactions is known to often be right-skewed and fat-tailed. Both these distributions affect epidemic dynamics strongly, but, as we show…

Populations and Evolution · Quantitative Biology 2020-05-14 Naoki Masuda , Petter Holme

We show that the quotient of Levy processes of jump-diffusion type has a fat-tailed distribution. An application is to price theory in economics. We show that fat tails arise endogenously from modeling of price change based on an excess…

General Economics · Economics 2021-03-11 Gunduz Caginalp

We show bounds on tail probabilities for quadratic forms in sub-gaussian non-necessarily independent random variables. Our main tool will be estimates of the Luxemburg norms of such forms. This will allow us to formulate the above-mentioned…

Probability · Mathematics 2020-08-14 Krzysztof Zajkowski

In risk theory, financial asset returns often follow heavy-tailed distributions. Investors and risk managers used to compare risk measures as the value at risk or tail value at risk in order over the whole confidence levels to avoid the…

Statistics Theory · Mathematics 2024-12-12 Alfonso J. Bello , Julio Mulero , Miguel A. Sordo , Alfonso Suárez-Llorens

Heavy tailed distributions present a tough setting for inference. They are also common in industrial applications, particularly with Internet transaction datasets, and machine learners often analyze such data without considering the biases…

Applications · Statistics 2016-10-14 Matt Taddy , Hedibert Freitas Lopes , Matt Gardner