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Related papers: Tail Asymptotic Expansions for L-Statistics

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For measuring tail risk with scarce extreme events, extreme value analysis is often invoked as the statistical tool to extrapolate to the tail of a distribution. The presence of large datasets benefits tail risk analysis by providing more…

Methodology · Statistics 2023-12-18 Liujun Chen , Deyuan Li , Chen Zhou

This article introduces a non-parametric information-theoretic approach to inference about the tail of a continuous or a discrete distribution. Leveraging a new concept named tail profile -- a set of information-theoretic quantities…

Applications · Statistics 2025-03-19 Jialin Zhang , Zhiyi Zhang

The problem of estimating a linear functional based on observational data is canonical in both the causal inference and bandit literatures. We analyze a broad class of two-stage procedures that first estimate the treatment effect function,…

Statistics Theory · Mathematics 2022-09-28 Wenlong Mou , Martin J. Wainwright , Peter L. Bartlett

A bivariate random vector can exhibit either asymptotic independence or dependence between the largest values of its components. When used as a statistical model for risk assessment in fields such as finance, insurance or meteorology, it is…

Probability · Mathematics 2019-04-29 Sebastian Engelke , Thomas Opitz , Jennifer Wadsworth

Lower and upper bounds are explored for the uniform (Kolmogorov) and $L^2$-distances between the distributions of weighted sums of dependent summands and the normal law. The results are illustrated for several classes of random variables…

Probability · Mathematics 2023-08-08 S. G. Bobkov , G. P. Chistyakov , F. Götze

A recent article on generalised linear mixed model asymptotics, Jiang et al. (2022), derived the rates of convergence for the asymptotic variances of maximum likelihood estimators. If $m$ denotes the number of groups and $n$ is the average…

Statistics Theory · Mathematics 2023-04-03 Luca Maestrini , Aishwarya Bhaskaran , Matt P. Wand

We study the dynamics of the normal implied volatility in a local volatility model, using a small-time expansion in powers of maturity T. At leading order in this expansion, the asymptotics of the normal implied volatility is similar, up to…

Computational Finance · Quantitative Finance 2015-03-19 Viorel Costeanu , Dan Pirjol

An asymptotic model for extreme behavior of certain Markov chains is the "tail chain". Generally taking the form of a multiplicative random walk, it is useful in deriving extremal characteristics such as point process limits. We place this…

Probability · Mathematics 2011-12-30 Sidney I. Resnick , David Zeber

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

Large and moderate deviation probabilities play an important role in many applied areas, such as insurance and risk analysis. This paper studies the exact moderate and large deviation asymptotics in non-logarithmic form for linear processes…

Statistics Theory · Mathematics 2013-05-07 Magda Peligrad , Hailin Sang , Yunda Zhong , Wei Biao Wu

There is an increasing interest to understand the dependence structure of a random vector not only in the center of its distribution but also in the tails. Extreme-value theory tackles the problem of modelling the joint tail of a…

Methodology · Statistics 2014-11-04 Anna Kiriliouk , Johan Segers , Michal Warchol

Asymptotic expansions with explicit upper bounds for remainders are given for stationary distributions of nonlinearly perturbed semi-Markov processes with finite phase spaces. The corresponding algorithms are based on a special technique of…

Probability · Mathematics 2016-03-16 Dmitrii Silvestrov , Sergei Silvestrov

Loynes' distribution, which characterizes the one dimensional marginal of the stationary solution to Lindley's recursion, possesses an ultimately exponential tail for a large class of increment processes. If one can observe increments but…

Probability · Mathematics 2013-09-19 Ken R. Duffy , Sean P. Meyn

We study distributions $F$ on $[0,\infty)$ such that for some $T\le\infty$, $F^{*2}(x,x+T]\sim 2 F(x,x+T]$. The case $T=\infty$ corresponds to $F$ being subexponential, and our analysis shows that the properties for $T<\infty$ are, in fact,…

Probability · Mathematics 2013-03-20 S. Asmussen , S. Foss , D. Korshunov

Based on a faithful representation of the heavy tail multivariate distribution of asset returns introduced previously (Sornette et al., 1998, 1999) that we extend to the case of asymmetric return distributions, we generalize the return-risk…

Statistical Mechanics · Physics 2008-12-02 J. V. Andersen , D. Sornette

We consider a discrete-time two-dimensional quasi-birth-and-death process (2d-QBD process for short) $\{(\boldsymbol{X}_n,J_n)\}$ on $\mathbb{Z}_+^2\times S_0$, where $\boldsymbol{X}_n=(X_{1,n},X_{2,n})$ is the level state, $J_n$ the phase…

Probability · Mathematics 2022-02-23 Toshihisa Ozawa

Let $X_{1,n}\le\cdots\le X_{n,n}$ be the order statistics of $n$ independent random variables with a common distribution function $F$ having right heavy tail with tail index $\gamma$. Given known constants $d_{i,n}$, $1\le i\le n$, consider…

Probability · Mathematics 2021-04-13 Lillian Achola Oluoch , László Viharos

The so-called partition function is a sample moment statistic based on blocks of data and it is often used in the context of multifractal processes. It will be shown that its behaviour is strongly influenced by the tail of the distribution…

Methodology · Statistics 2013-10-02 Danijel Grahovac , Mofei Jia , Nikolai N. Leonenko , Emanuele Taufer

We study tail risk dynamics in high-frequency financial markets and their connection with trading activity and market uncertainty. We introduce a dynamic extreme value regression model accommodating both stationary and local unit-root…

Econometrics · Economics 2023-01-05 Julien Hambuckers , Li Sun , Luca Trapin

Let $X$ be the number of $k$-term arithmetic progressions contained in the $p$-biased random subset of the first $N$ positive integers. We give asymptotically sharp estimates on the logarithmic upper-tail probability $\log \Pr(X \ge E[X] +…

Probability · Mathematics 2024-09-16 Matan Harel , Frank Mousset , Wojciech Samotij
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