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We study a Monte Carlo algorithm for simulation of probability distributions based on stochastic step functions, and compare to the traditional Metropolis/Hastings method. Unlike the latter, the step function algorithm can produce an…

Probability · Mathematics 2015-12-07 Torquil Macdonald Sørensen , Fred Espen Benth

Atypical, rare trajectories of dynamical systems are important: they are often the paths for chemical reactions, the haven of (relative) stability of planetary systems, the rogue waves that are detected in oil platforms, the structures that…

Statistical Mechanics · Physics 2012-04-12 Cristian Giardina , Jorge Kurchan , Vivien Lecomte , Julien Tailleur

We study large deviation probabilities for a sum of dependent random variables from a heavy-tailed factor model, assuming that the components are regularly varying. We identify conditions where both the factor and the idiosyncratic terms…

Probability · Mathematics 2007-12-05 Boualem Djehiche , Jens Svensson

The tail behavior of aggregates of heavy-tailed random vectors is known to be determined by the so-called principle of "one large jump'', be it for finite sums, random sums, or, L\'evy processes. We establish that, in fact, a more general…

Probability · Mathematics 2023-01-26 Bikramjit Das , Vicky Fasen-Hartmann

Extreme weather events epitomize high cost: to society through their physical impacts, and to computer servers that simulate them to assess risk and advance physical understanding. It costs hundreds of simulation years to sample a few…

Atmospheric and Oceanic Physics · Physics 2026-04-14 Justin Finkel , Paul A. O'Gorman

L\'{e}vy processes with completely monotone jumps appear frequently in various applications of probability. For example, all popular stock price models based on L\'{e}vy processes (such as the Variance Gamma, CGMY/KoBoL and Normal Inverse…

Probability · Mathematics 2016-01-08 Daniel Hackmann , Alexey Kuznetsov

We consider a general class of high order weak approximation schemes for stochastic differential equations driven by L\'evy processes with infinite activity. These schemes combine a compound Poisson approximation for the jump part of the…

Probability · Mathematics 2012-04-24 Arturo Kohatsu-Higa , Salvador Ortiz-Latorre , Peter Tankov

Rare events in the first-passage distributions of jump processes are capable of triggering anomalous reactions or series of events. Estimating their probability is particularly important when the jump probabilities have broad-tailed…

Statistical Mechanics · Physics 2024-05-06 Alessandro Vezzani , Raffaella Burioni

In this paper we propose and advocate the use of the so called L\'evy flights as a driving mechanism for a class of stochastic optimization computations. This proposal, for some reasons overlooked until now, is - in author's opinion - very…

Mathematical Physics · Physics 2007-05-23 Marek Gutowski

L\'{e}vy flights is a random walk where the step-lengths have a probability distribution that is heavy-tailed. It has been shown that L\'{e}vy flights can maximize the efficiency of resource searching in uncertain environments, and also…

Neural and Evolutionary Computing · Computer Science 2019-06-11 Jiamin Wei , YangQuan Chen , Yongguang Yu , Yuquan Chen

We develop generic and efficient importance sampling estimators for Monte Carlo evaluation of prices of single- and multi-asset European and path-dependent options in asset price models driven by L\'evy processes, extending earlier works…

Risk Management · Quantitative Finance 2016-08-17 Adrien Genin , Peter Tankov

Computation of extreme quantiles and tail-based risk measures using standard Monte Carlo simulation can be inefficient. A method to speed up computations is provided by importance sampling. We show that importance sampling algorithms,…

Probability · Mathematics 2009-09-21 Henrik Hult , Jens Svensson

In this paper we introduce a new class of state space models based on shot-noise simulation representations of non-Gaussian L\'evy-driven linear systems, represented as stochastic differential equations. In particular a conditionally…

Probability · Mathematics 2020-01-09 Simon Godsill , Marina Riabiz , Ioannis Kontoyiannis

Modeling uncertainty in heavy-tailed time series remains a critical challenge for deep probabilistic forecasting models, which often struggle to capture abrupt, extreme events. While L\'evy stable distributions offer a natural framework for…

Machine Learning · Computer Science 2026-05-15 Yang Yang , Du Yin , Hao Xue , Flora Salim

We derive subexponential tail asymptotics for the distribution of the maximum of a compound renewal process with linear component and of a L\'evy process, both with negative drift, over random time horizon $\tau$ that does not depend on the…

Probability · Mathematics 2024-10-07 Sergey Foss , Dmitry Korshunov , Zbigniew Palmowski

An important step in the design of autonomous systems is to evaluate the probability that a failure will occur. In safety-critical domains, the failure probability is extremely small so that the evaluation of a policy through Monte Carlo…

Machine Learning · Computer Science 2022-11-23 Anthony Corso , Kyu-Young Kim , Shubh Gupta , Grace Gao , Mykel J. Kochenderfer

State-of-the-art methods for rare event simulation of non-Markovian models face practical or theoretical limits if observing the event of interest requires prior knowledge or information on the timed behavior of the system. In this paper,…

Logic in Computer Science · Computer Science 2025-06-25 Gabriel Dengler , Carlos E. Budde , Laura Carnevali , Arnd Hartmanns

We investigate some recursive procedures based on an exact or ``approximate'' Euler scheme with decreasing step in vue to computation of invariant measures of solutions to S.D.E. driven by a L\'evy process. Our results are valid for a large…

Probability · Mathematics 2008-04-02 Fabien Panloup

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

We propose a novel estimation framework for path-dependent functionals of Levy processes from discretely observed data. Traditional approaches rely on Monte Carlo simulation of full paths, which requires complete model specification and…

Methodology · Statistics 2025-09-03 Yasutaka Shimizu , Hiroshi Shiraishi