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We consider a sequence of fractional Ornstein-Uhlenbeck processes, that are defined as solutions of a family of stochastic Volterra equations with kernel given by the Riesz derivative kernel, and leading coefficients given by a sequence of…

Probability · Mathematics 2022-11-24 Luigi Amedeo Bianchi , Stefano Bonaccorsi , Luciano Tubaro

This work investigates the tail behavior of solutions to the affine stochastic fixed-point equation of the form $X\stackrel{d}{=}AX+B$, where $X$ and $(A,B)$ are independent. Focusing on the light-tail regime, following [Burdzy et al.…

Probability · Mathematics 2025-03-25 Julia Le Bihan , Bartosz Kołodziejek

Let $\Phi_n$ be an i.i.d. sequence of Lipschitz mappings of $\R^d$. We study the Markov chain $\{X_n^x\}_{n=0}^\infty$ on $\R^d$ defined by the recursion $X_n^x = \Phi_n(X^x_{n-1})$, $n\in\N$, $X_0^x=x\in\R^d$. We assume that…

Probability · Mathematics 2011-10-20 Dariusz Buraczewski , Ewa Damek , Mariusz Mirek

Recent theoretical studies have shown that heavy-tails can emerge in stochastic optimization due to `multiplicative noise', even under surprisingly simple settings, such as linear regression with Gaussian data. While these studies have…

Machine Learning · Statistics 2025-05-06 Mert Gurbuzbalaban , Yuanhan Hu , Umut Simsekli , Kun Yuan , Lingjiong Zhu

Consider a Lamperti-Kiu Markov additive process $(J_t,\xi_t:t\geq0)$ on $\{+,-\}\times\mathbb{R}\cup\infty$ where $J$ is the modulating Markov chain component. First, we study the finiteness of the exponential functional and then consider…

Probability · Mathematics 2020-11-23 Larbi Alili , David Woodford

Regime switching processes have proved to be indispensable in the modeling of various phenomena, allowing model parameters that traditionally were considered to be constant to fluctuate in a Markovian manner in line with empirical findings.…

Probability · Mathematics 2019-04-03 Filip Lindskog , Abhishek Pal Majumder

Masked language models (MLMs) define local conditional distributions over tokens but do not, in general, correspond to any consistent joint distribution over sequences. This raises a fundamental question: what global distributional behavior…

Machine Learning · Computer Science 2026-05-19 Suvadip Sana , Sami Wolf , Neer Mehta , Alina Shah , Aitzaz Shaikh , Janna Goodman , Lionel Levine

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

The areas under workload process and under queuing process in a single server queue over the busy period have many applications not only in queuing theory but also in risk theory or percolation theory. We focus here on the tail behaviour of…

Probability · Mathematics 2011-02-08 Rafal Kulik , Zbigniew Palmowski

Our work aims to study the tail behaviour of weighted sums of the form $\sum_{i=1}^{\infty} X_{i} \prod_{j=1}^{i}Y_{j}$, where $(X_{i}, Y_{i})$ are independent and identically distributed, with common joint distribution bivariate Sarmanov.…

Probability · Mathematics 2017-09-05 Krishanu Maulik , Moumanti Podder

This paper studies subordinate Ornstein-Uhlenbeck (OU) processes, i.e., OU diffusions time changed by L\'{e}vy subordinators. We construct their sample path decomposition, show that they possess mean-reverting jumps, study their equivalent…

Pricing of Securities · Quantitative Finance 2012-04-18 Lingfei Li , Vadim Linetsky

There is a well-established theory linking certain semi-Markov chains and continuous-time random walks to time-fractional equations and anomalous diffusion. In this work, we go beyond the semi-Markov framework by considering some…

Probability · Mathematics 2026-02-27 Lorenzo Facciaroni , Costantino Ricciuti , Enrico Scalas

The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of…

Quantum Physics · Physics 2012-10-02 Mohan Sarovar , Matthew D. Grace

Stochastic ordering of distributions of random variables may be defined by the relative convexity of the tail functions. This has been extended to higher order stochastic orderings, by iteratively reassigning tail-weights. The actual…

Statistics Theory · Mathematics 2017-03-14 Idir Arab , Paulo Eduardo Oliveira

Cyclic and randomized stepsizes are widely used in the deep learning practice and can often outperform standard stepsize choices such as constant stepsize in SGD. Despite their empirical success, not much is currently known about when and…

Machine Learning · Statistics 2023-08-30 Mert Gürbüzbalaban , Yuanhan Hu , Umut Şimşekli , Lingjiong Zhu

Contrary to the theory of Markov processes, no general theory exists for the so called nonlinear Markov processes. We study an example of "nonlinear Markov process" related to classical probability theory, merely to random walks. This model…

Mathematical Physics · Physics 2011-10-31 S. A. Muzychka , K. L. Vaninsky

We develop a general approach for studying the cumulative probability distribution function of localized objects (particles) whose dynamics is governed by the first-order Langevin equation driven by superheavy-tailed noise. Solving the…

Statistical Mechanics · Physics 2011-04-05 S. I. Denisov , H. Kantz

We investigate subcritical Galton-Watson branching processes with immigration in a random environment. Using Goldie's implicit renewal theory we show that under general Cram\'er condition the stationary distribution has a power law tail. We…

Probability · Mathematics 2020-02-04 Bojan Basrak , Peter Kevei

L\'evy-driven Ornstein-Uhlenbeck (OU) processes represent an intriguing class of stochastic processes that have garnered interest in the energy sector for their ability to capture typical features of market dynamics. However, in the current…

Computational Finance · Quantitative Finance 2026-05-07 Roberto Baviera , Pietro Manzoni

We look at joint regular variation properties of MA($\infty$) processes of the form $\mathbf{X} = (X_k, k \in \mathbb{Z})$ where $X_k = \sum_{j=0}^{\infty} \psi_j Z_{k-j}$ and the sequence of random variables $(Z_i, i \in \mathbb{Z})$ are…

Probability · Mathematics 2013-10-01 Sideny I. Resnick , Joyjit Roy
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