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We study a new estimator for the tail index of a distribution in the Frechet domain of attraction that arises naturally by computing subsample maxima. This estimator is equivalent to taking a U-statistic over a Hill estimator with two order…

Methodology · Statistics 2015-03-20 Stefan Wager

The extreme value theory is very popular in applied sciences including Finance, economics, hydrology and many other disciplines. In univariate extreme value theory, we model the data by a suitable distribution from the general max-domain of…

Methodology · Statistics 2019-05-09 Abhik Ghosh

In this paper, we investigate and develop a new approach to the numerical analysis and characterization of random fluctuations with heavy-tailed probability distribution function (PDF), such as turbulent heat flow and solar flare…

Statistical Mechanics · Physics 2017-03-22 Mohsen Ghasemi Nezhadhaghighi , Abbas Nakhlband

Heavy-tailed distributions, prevalent in a lot of real-world applications such as finance, telecommunications, queuing theory, and natural language processing, are challenging to model accurately owing to their slow tail decay. Bernstein…

Performance · Computer Science 2025-10-31 Abdelhakim Ziani , András Horváth , Paolo Ballarini

The market efficiency hypothesis has been proposed to explain the behavior of time series of stock markets. The Black-Scholes model (B-S) for example, is based on the assumption that markets are efficient. As a consequence, it is…

Statistical Finance · Quantitative Finance 2019-03-20 Carlos Arturo Soto Campos , Leopoldo Sánchez Cantú , Zeus Hernández Veleros

The performance of the multifractal detrended analysis on short time series is evaluated for synthetic samples of several mono- and multifractal models. The reconstruction of the generalized Hurst exponents is used to determine the range of…

Data Analysis, Statistics and Probability · Physics 2013-11-12 Juan Luis Lopez , Jesus Guillermo Contreras

Despite the successes of probabilistic models based on passing noise through neural networks, recent work has identified that such methods often fail to capture tail behavior accurately, unless the tails of the base distribution are…

Machine Learning · Statistics 2023-06-16 Feynman Liang , Liam Hodgkinson , Michael W. Mahoney

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is investigated on the Chinese stock market using mean-variance analysis, fluctuation analysis and their generalizations to…

Physics and Society · Physics 2008-12-02 Zhi-Qiang Jiang , Liang Guo , Wei-Xing Zhou

Several novel statistical methods have been developed to estimate large integrated volatility matrices based on high-frequency financial data. To investigate their asymptotic behaviors, they require a sub-Gaussian or finite high-order…

Statistics Theory · Mathematics 2023-08-15 Minseok Shin , Donggyu Kim , Jianqing Fan

Extreme events and the heavy tail distributions driven by them are ubiquitous in various scientific, engineering and financial research. They are typically associated with stochastic instability caused by hidden unresolved processes.…

Probability · Mathematics 2019-05-22 Andrew J. Majda , Xin T. Tong

Considering that both the entropy-based market information and the Hurst exponent are useful tools for determining whether the efficient market hypothesis holds for a given asset, we study the link between the two approaches. We thus…

Statistical Finance · Quantitative Finance 2023-06-26 Xavier Brouty , Matthieu Garcin

A new estimator is proposed for estimating the tail exponent of a heavy-tailed distribution. This estimator, referred to as the layered Hill estimator, is a generalization of the traditional Hill estimator, building upon a layered structure…

Statistics Theory · Mathematics 2026-04-20 Taegyu Kang , Takashi Owada

The paper deals with fractal characteristics (Hurst exponent) and wavelet-scaleograms of the information distribution model, suggested by the authors. The authors have studied the effect of Hurst exponent change depending upon the model…

Social and Information Networks · Computer Science 2016-10-17 D. V. Lande , V. A. Dodonov

In order to interpret and explain the physiological signal behaviors, it can be interesting to find some constants among the fluctuations of these data during all the effort or during different stages of the race (which can be detected…

Applications · Statistics 2011-12-06 Imen Kammoun , Véronique Billat , Jean-Marc Bardet

We introduce a novel rough Bergomi (rBergomi) model featuring a variance-driven exponentially weighted moving average (EWMA) time-dependent Hurst parameter $H_t$, fundamentally distinct from recent machine learning and wavelet-based…

Mathematical Finance · Quantitative Finance 2025-09-09 Jayanth Athipatla

In this paper we are concerned with the analysis of heavy-tailed data when a portion of the extreme values is unavailable. This research was motivated by an analysis of the degree distributions in a large social network. The degree…

Statistics Theory · Mathematics 2018-12-20 Jingjing Zou , Richard A. Davis , Gennady Samorodnitsky

In this work, we consider systems that are subjected to intermittent instabilities due to external stochastic excitation. These intermittent instabilities, though rare, have a large impact on the probabilistic response of the system and…

Chaotic Dynamics · Physics 2017-06-02 Mustafa A. Mohamad , Themistoklis P. Sapsis

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

In this paper it presents, develops and discusses the existence of a process with long scope memory structure, representing of the independence between the degree of randomness of the traffic generated by the sources and flow pattern…

Physics and Society · Physics 2021-04-01 G. Millán

Forecasting multivariate time series is a computationally intensive task challenged by extreme or redundant samples. Recent resampling methods aim to increase training efficiency by reweighting samples based on their running losses.…

Machine Learning · Computer Science 2024-06-21 Jiang You , Arben Cela , René Natowicz , Jacob Ouanounou , Patrick Siarry
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