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Marginal expected shortfall is unquestionably one of the most popular systemic risk measures. Studying its extreme behaviour is particularly relevant for risk protection against severe global financial market downturns. In this context,…

Statistics Theory · Mathematics 2023-04-18 Simone A. Padoan , Stefano Rizzelli , Matteo Schiavone

The escaping set of an entire function is the set of points that tend to infinity under iteration. We consider subsets of the escaping set defined in terms of escape rates and obtain upper and lower bounds for the Hausdorff measure of these…

Dynamical Systems · Mathematics 2013-06-03 Walter Bergweiler , Jörn Peter

We consider statistical models arising from the common set of solutions to a sparse polynomial system with general coefficients. The maximum likelihood degree counts the number of critical points of the likelihood function restricted to the…

Algebraic Geometry · Mathematics 2022-04-20 Julia Lindberg , Nathan Nicholson , Jose Israel Rodriguez , Zinan Wang

We study the probability distribution and the escape rate in systems with delayed dissipation that comes from the coupling to a thermal bath. To logarithmic accuracy in the fluctuation intensity, the problem is reduced to a variational…

Statistical Mechanics · Physics 2015-06-04 M. I. Dykman , I. B. Schwartz

Modifying the reward-biased maximum likelihood method originally proposed in the adaptive control literature, we propose novel learning algorithms to handle the explore-exploit trade-off in linear bandits problems as well as generalized…

Machine Learning · Computer Science 2020-10-09 Yu-Heng Hung , Ping-Chun Hsieh , Xi Liu , P. R. Kumar

In this paper, we provide some analysis on the asymptotic escape of strict saddles in manifold optimization using the projected gradient descent (PGD) algorithm. One of our main contributions is that we extend the current analysis to…

Optimization and Control · Mathematics 2020-06-30 Thomas Y. Hou , Zhenzhen Li , Ziyun Zhang

We propose to model the records of the maximum Drawdown in capital markets by means a Piecewise Deterministic Markov Process (PDMP). We derive statistical results such as the mean and variance that describes the sequence of maximum Drawdown…

Risk Management · Quantitative Finance 2025-04-01 Rolando Rubilar-Torrealba , Lisandro Fermin , Soledad Torres

Motivated by the applications of routing in PCB buses, the Rectangle Escape Problem was recently introduced and studied. In this problem, we are given a set of rectangles $\mathcal{S}$ in a rectangular region $R$, and we would like to…

Computational Geometry · Computer Science 2016-03-16 Aniket Basu Roy , Anil Maheshwari , Sathish Govindarajan , Neeldhara Misra , Subhas C Nandy , Shreyas Shetty

In the standard formulation of the occupancy problem one considers the distribution of r balls in n cells, with each ball assigned independently to a given cell with probability 1/n. Although closed form expressions can be given for the…

Probability · Mathematics 2007-05-23 Paul Dupuis , Carl Nuzman , Phil Whiting

Let $T$ be a piecewise expanding interval map and $T_H$ be an abstract perturbation of $T$ into an interval map with a hole. Given a number $\ell$, $0<\ell<1$, we compute an upper-bound on the size of a hole needed for the existence of an…

Dynamical Systems · Mathematics 2009-11-30 Wael Bahsoun , Christopher Bose

We develop a comprehensive mathematical framework for polynomial jump-diffusions in a semimartingale context, which nest affine jump-diffusions and have broad applications in finance. We show that the polynomial property is preserved under…

Mathematical Finance · Quantitative Finance 2019-07-23 Damir Filipović , Martin Larsson

This paper presents a pseudo-spectral method for Dynamic Optimization Problems (DOPs) that allows for tight polynomial bounds to be achieved via flexible sub-intervals. The proposed method not only rigorously enforces inequality…

Optimization and Control · Mathematics 2026-04-08 Eduardo M. G. Vila , Eric C. Kerrigan , Paul Bruce

Standard Markov decision process (MDP) and reinforcement learning algorithms optimize the policy with respect to the expected gain. We propose an algorithm which enables to optimize an alternative objective: the probability that the gain is…

Machine Learning · Computer Science 2023-03-06 Vincent Corlay , Jean-Christophe Sibel

This article discusses modelling of the tail of a multivariate distribution function by means of a large deviation principle (LDP), and its application to the estimation of the probability of a multivariate extreme event from a sample of n…

Statistics Theory · Mathematics 2017-02-23 Cees de Valk

Using martingale methods, we obtain some upper bounds for large and moderate deviations of products of independent and identically distributed elements of GL d (R). We investigate all the possible moment conditions, from super-exponential…

Probability · Mathematics 2016-10-25 Christophe Cuny , Jérôme Dedecker , Florence Merlevède

Recently, continuum Microkinetic Rate Theory (cMRT) has been advanced as a method of studying rates of systems, where deviations between observation and cMRT theory have been found, and it hypothesized that these deviations are linked…

Statistical Mechanics · Physics 2019-01-23 M. F. Francis

This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function…

Probability · Mathematics 2023-08-10 Anatolii A. Puhalskii

This paper examines the relationship between the escape rate and the minimal period of the hole. We consider a subshift of finite type on $q$ symbols with a union of $t$ cylinders based at words of identical length $p$ as the hole. The…

Dynamical Systems · Mathematics 2022-04-07 Haritha Cheriyath , Nikita Agarwal

An overview of rare events algorithms based on large deviation theory (LDT) is presented. It covers a range of numerical schemes to compute the large deviation minimizer in various setups, and discusses best practices, common pitfalls, and…

Statistical Mechanics · Physics 2019-07-24 Tobias Grafke , Eric Vanden-Eijnden

Several researchers have proposed minimisation of maximum mean discrepancy (MMD) as a method to quantise probability measures, i.e., to approximate a target distribution by a representative point set. We consider sequential algorithms that…

Machine Learning · Statistics 2021-02-15 Onur Teymur , Jackson Gorham , Marina Riabiz , Chris. J. Oates
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