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Financial time series have been investigated to follow fat-tailed distributions. Further, an empirical probability distribution sometimes shows cut-off shapes on its tails. To describe this stylized fact, we incorporate the cut-off effect…

Statistical Finance · Quantitative Finance 2019-06-26 Yusuke Uchiyama , Takanori Kadoya

Power-law distributions occur in wide variety of physical, biological, and social phenomena. In this paper, we propose a statistical hypothesis test based on the log-likelihood ratio to assess whether two samples of discrete data are drawn…

Methodology · Statistics 2015-03-03 Alessandro Bessi

Empirical evidence shows stock returns are often heavy-tailed rather than normally distributed. The $\kappa$-generalised distribution, originated in the context of statistical physics by Kaniadakis, is characterised by the…

Statistical Finance · Quantitative Finance 2024-05-17 Samuel Forbes

This Colloquium reviews statistical models for money, wealth, and income distributions developed in the econophysics literature since the late 1990s. By analogy with the Boltzmann-Gibbs distribution of energy in physics, it is shown that…

Statistical Finance · Quantitative Finance 2009-12-24 Victor M. Yakovenko , J. Barkley Rosser

One of the standardized features of financial data is that log-returns are uncorrelated, but absolute log-returns or their squares namely the fluctuating volatility are correlated and is characterized by heavy tailed in the sense that some…

Statistical Finance · Quantitative Finance 2021-05-11 Geoffrey Ducournau

It is well known that the probability distribution of high-frequency financial returns is characterized by a leptokurtic, heavy-tailed shape. This behavior undermines the typical assumption of Gaussian log-returns behind the standard…

Statistical Finance · Quantitative Finance 2023-06-14 Federica De Domenico , Giacomo Livan , Guido Montagna , Oreste Nicrosini

At high levels, the asymptotic distribution of a stationary, regularly varying Markov chain is conveniently given by its tail process. The latter takes the form of a geometric random walk, the increment distribution depending on the sign of…

Methodology · Statistics 2014-12-11 Holger Drees , Johan Segers , Michał Warchoł

Quantal systems are predicted to show a change-over from exponential decay to power law decay at very long times. Although most theoretical studies predict integer power-law exponents, recent measurements by Rothe et al. of decay…

Quantum Physics · Physics 2009-11-13 J. Martorell , J. G. Muga , D. W. L. Sprung

The study of loss function distributions is critical to characterize a model's behaviour on a given machine learning problem. For example, while the quality of a model is commonly determined by the average loss assessed on a testing set,…

Machine Learning · Computer Science 2023-06-06 Etrit Haxholli , Marco Lorenzi

Probability distributions of money, income, and energy consumption per capita are studied for ensembles of economic agents. The principle of entropy maximization for partitioning of a limited resource gives exponential distributions for the…

Statistical Finance · Quantitative Finance 2010-09-02 Anand Banerjee , Victor M. Yakovenko

We introduce a new actuarial tail-shape index, the $\theta$-index, based on a probability equal level relationship between Value at Risk and Expected Shortfall. The index is defined at each tail probability level as the parameter value for…

Risk Management · Quantitative Finance 2026-01-29 Georgios I. Papayiannis , Georgios Psarrakos

We propose a model to create synthetic networks that may also serve as a narrative of a certain kind of infrastructure network evolution. It consists of an initialization phase with the network extending tree-like for minimum cost and a…

Physics and Society · Physics 2016-02-09 Paul Schultz , Jobst Heitzig , Jürgen Kurths

Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggests that reweighting or curating data towards a uniform distribution may help models…

Artificial Intelligence · Computer Science 2026-04-28 Zixuan Wang , Xingyu Dang , Jason D. Lee , Kaifeng Lyu

The purpose of this paper is to show that the use of heavy-tailed distributions in Financial problems is theoretically baseless and can lead to significant misunderstandings. The reason for this the authors see in an incorrect…

Probability · Mathematics 2015-07-29 Lev B Klebanov , Irina V Volchenkova

We study dynamical behavior of the Chinese stock markets by investigating the statistical properties of daily ensemble returns and varieties defined respectively as the mean and the standard deviation of the ensemble daily price returns of…

Physics and Society · Physics 2008-12-02 Gao-Feng Gu , Wei-Xing Zhou

A generic communication model of a boolean network with transmission errors is proposed to explore the power-law scaling of states' evolution in small-world networks. In the model, the power spectrum of the population difference between…

Condensed Matter · Physics 2007-05-23 Jiann-Shing Lih , Jyh-Long Chern

The use of expectiles in risk management has recently gathered remarkable momentum due to their excellent axiomatic and probabilistic properties. In particular, the class of elicitable law-invariant coherent risk measures only consists of…

Statistics Theory · Mathematics 2023-03-21 Abdelaati Daouia , Simone A. Padoan , Gilles Stupfler

Quasi-power law ensembles are discussed from the perspective of nonextensive Tsallis distributions characterized by a nonextensive parameter $q$. A number of possible sources of such distributions are presented in more detail. It is further…

Statistical Mechanics · Physics 2023-07-19 Grzegorz Wilk , Zbigniew Włodarczyk

[Takayasu et al., Phys. Rev.Lett. 79, 966 (1997)] revisited the question of stochastic processes with multiplicative noise, which have been studied in several different contexts over the past decades. We focus on the regime, found for a…

Statistical Mechanics · Physics 2009-10-30 D. Sornette

In this work, we provide an overview of the recent investigations on the non-extensive Tsallis statistics and its applications to high energy physics and astrophysics, including physics at the Large Hadron Collider (LHC), hadron physics,…

High Energy Physics - Phenomenology · Physics 2020-09-15 Airton Deppman , Eugenio Megias , Debora P. Menezes