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This paper presents an identity between the multivariate and univariate saddlepoint approximations applied to sample path probabilities for a certain class of stochastic processes. This class, which we term the recursively compounded…

Probability · Mathematics 2024-06-21 Jesse Goodman

We determine the large exceedance probabilities and large exceedance paths for the matrix recursive sequence $V_n = M_n V_{n-1} + Q_n, \: n=1,2,\ldots,$ where $\{M_n\}$ is an i.i.d. sequence of $d \times d$ random matrices and $\{ Q_n\}$ is…

Probability · Mathematics 2016-08-19 Jeffrey F. Collamore , Sebastian Mentemeier

This paper is devoted to the problem of sample path large deviations for multidimensional queueing models with feedback. We derive a new version of the contraction principle where the continuous map is not well-defined on the whole space:…

Probability · Mathematics 2007-05-23 Marc Lelarge

We prove a large deviation principle on path space for a class of discrete time Markov processes whose state space is the intersection of a regular domain $\L\subset \R^d$ with some lattice of spacing $\e$. Transitions from $x$ to $y$ are…

Probability · Mathematics 2007-05-23 Anton Bovier , Veronique Gayrard

We consider asymptotics for the maximum of a modulated random walk whose increments $\xi_n^{X_n}$ are heavy-tailed. Of particular interest is the case where the modulating process $X$ is regenerative. Here we study also the maximum of the…

Probability · Mathematics 2017-11-29 Sergey Foss , Stan Zachary

The problem of (pathwise) large deviations for conditionally continuous Gaussian processes is investigated. The theory of large deviations for Gaussian processes is extended to the wider class of random processes -- the conditionally…

Probability · Mathematics 2019-02-07 Barbara Pacchiarotti , Alessandro Pigliacelli

We study the stochastic recursion $X_n=\Psi_n(X_{n-1})$, where $(\Psi_n)_{n\geq 1}$ is a sequence of i.i.d. random Lipschitz mappings close to the random affine transformation $x\mapsto Ax+B$. We describe the tail behaviour of the…

Probability · Mathematics 2020-12-16 Ewa Damek , Bartosz Kołodziejek

Let $\xi_1, \xi_2,\ldots$ be a sequence of independent and identically distributed random variables with zero mean, finite second moment and regularly varying right distribution tail. Motivated by a stop-loss insurance model, we consider a…

Probability · Mathematics 2025-06-05 Aaron Chong , Konstantin Borovkov

Modern risk modelling approaches deal with vectors of multiple components. The components could be, for example, returns of financial instruments or losses within an insurance portfolio concerning different lines of business. One of the…

Probability · Mathematics 2021-05-12 Miriam Hägele , Jaakko Lehtomaa

Consider the continuous greedy paths model: given a $d$-dimensional Poisson point process with positive marks interpreted as masses, let $\mathrm P(\ell)$ denote the maximum mass gathered by a path of length $\ell$ starting from the origin.…

Probability · Mathematics 2025-03-04 Julien Verges

We prove a large deviations principle for the class of multidimensional affine stochastic volatility models considered in (Gourieroux, C. and Sufana, R., J. Bus. Econ. Stat., 28(3), 2010), where the volatility matrix is modelled by a…

Pricing of Securities · Quantitative Finance 2018-06-20 Aurélien Alfonsi , David Krief , Peter Tankov

Let $X_k$ denote the number of $k$-term arithmetic progressions in a random subset of $\mathbb{Z}/N\mathbb{Z}$ or $\{1, \dots, N\}$ where every element is included independently with probability $p$. We determine the asymptotics of $\log…

Probability · Mathematics 2019-11-12 Bhaswar B. Bhattacharya , Shirshendu Ganguly , Xuancheng Shao , Yufei Zhao

Heavy-tailed distributions are found throughout many naturally occurring phenomena. We have reviewed the models of stochastic dynamics that lead to heavy-tailed distributions (and power law distributions, in particular) including the…

Mathematical Physics · Physics 2011-05-09 Ph. Blanchard , T. Krueger , D. Volchenkov

We consider a modulated process S which, conditional on a background process X, has independent increments. Assuming that S drifts to -infinity and that its increments (jumps) are heavy-tailed (in a sense made precise in the paper), we…

Probability · Mathematics 2017-11-29 Sergey Foss , Takis Konstantopoulos , Stan Zachary

In this paper we propagate a large deviations approach for proving limit theory for (generally) multivariate time series with heavy tails. We make this notion precise by introducing regularly varying time series. We provide general large…

Statistics Theory · Mathematics 2015-09-02 T. Mikosch , O. Wintenberger

We prove pathwise large-deviation principles of switching Markov processes by exploiting the connection to associated Hamilton-Jacobi equations, following Jin Feng's and Thomas Kurtz's method. In the limit that we consider, we show how the…

Probability · Mathematics 2021-06-08 Mark A. Peletier , Mikola C. Schlottke

In this paper we prove scalar and sample path large deviation principles for a large class of Poisson cluster processes. As a consequence, we provide a large deviation principle for ergodic Hawkes point processes.

Probability · Mathematics 2007-05-23 Charles Bordenave , Giovanni Luca Torrisi

We consider a stochastic fluid network where the external input processes are compound Poisson with heavy-tailed Weibullian jumps. Our results comprise of large deviations estimates for the buffer content process in the vector-valued…

Probability · Mathematics 2023-02-21 Mihail Bazhba , Chang-Han Rhee , Bert Zwart

We prove large deviation results for the position of the rightmost particle, denoted by $M_n$, in a one-dimensional branching random walk in a case when Cram\'er's condition is not satisfied. More precisely we consider step size…

Probability · Mathematics 2020-06-17 Piotr Dyszewski , Nina Gantert , Thomas Höfelsauer

We prove a version of Nagaev's theorem for the branching random walk with heavy-tailed associated random walk. For a branching random walk on $\mathbb{R}$ we consider the random measure $Z_n = \sum_{|u|=n} e^{-V_u} \delta_{V_u}$ where…

Probability · Mathematics 2026-03-18 Jakob Stonner