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Schreiber and Yukich [Ann. Probab. 36 (2008) 363-396] establish an asymptotic representation for random convex polytope geometry in the unit ball $\mathbb{B}^d, d\geq2$, in terms of the general theory of stabilizing functionals of Poisson…

Probability · Mathematics 2013-04-03 Pierre Calka , Tomasz Schreiber , J. E. Yukich

We show that the uniform norm of generalized grey Brownian motion over the unit interval has an analytic density, excluding the special case of fractional Brownian motion. Our main result is an asymptotic expansion for the small ball…

Probability · Mathematics 2023-01-13 Stefan Gerhold

We introduce the hybrid risk process, constructed via a time-change transformation applied to the solution of a hybrid stochastic differential equation. The framework covers several modern ruin settings, incorporating features like…

Probability · Mathematics 2025-07-01 Oscar Peralta , Habacuq Vallejo

We introduce generalizations of Aldous' Brownian Continuous Random Tree as scaling limits for multicritical models of discrete trees. These discrete models involve trees with fine-tuned vertex-dependent weights ensuring a k-th root…

Mathematical Physics · Physics 2007-05-23 J. Bouttier , P. Di Francesco , E. Guitter

We investigate, focusing on the ruin probability, an adaptation of the Cramer-Lundberg model for the surplus process of an insurance company, in which, conditionally on their intensities, the two mixed Poisson processes governing the…

Mathematical Finance · Quantitative Finance 2017-06-27 Matija Vidmar

In this paper, we deal with an axiomatic approach to default risk. We introduce the notion of a default risk measure, which generalizes the classical probability of default (PD), and allows to incorporate model risk in various forms. We…

Mathematical Finance · Quantitative Finance 2023-09-21 Max Nendel , Jan Streicher

In this paper, we obtain the finite-horizon and infinite-horizon ruin probability asymptotics for risk processes with claims of subexponential tails for non-stationary arrival processes that satisfy a large deviation principle. As a result,…

Risk Management · Quantitative Finance 2014-10-16 Lingjiong Zhu

We present a series of new and more favorable margin-based learning guarantees that depend on the empirical margin loss of a predictor. We give two types of learning bounds, both distribution-dependent and valid for general families, in…

Machine Learning · Computer Science 2020-10-30 Corinna Cortes , Mehryar Mohri , Ananda Theertha Suresh

Consider an insurance company exposed to a stochastic economic environment that contains two kinds of risk. The first kind is the insurance risk caused by traditional insurance claims, and the second kind is the financial risk resulting…

Statistics Theory · Mathematics 2015-07-29 Jinzhu Li , Qihe Tang

In this paper, we provide a new framework to obtain the generalization bounds of the learning process for domain adaptation, and then apply the derived bounds to analyze the asymptotical convergence of the learning process. Without loss of…

Machine Learning · Computer Science 2013-04-08 Chao Zhang , Lei Zhang , Jieping Ye

This paper investigates asymptotic estimates for the entrance probability of the discounted aggregate claim vector from a multivariate renewal risk model into some rare set. We provide asymptotic results for the entrance probability on both…

Probability · Mathematics 2026-04-14 Zhangting Chen , Dimitrios G. Konstantinides , Charalampos D. Passalidis

In this paper, we are concerned with the numerical solution of one type integro-differential equation by a probability method based on the fundamental martingale of mixed Gaussian processes. As an application, we will try to simulate the…

Probability · Mathematics 2020-05-08 Chunhao Cai , Weilin Xiao

We consider a classical risk process with arrival of claims following a non-stationary Hawkes process. We study the asymptotic regime when the premium rate and the baseline intensity of the claims arrival process are large, and claim size…

Risk Management · Quantitative Finance 2019-08-22 Zailei Cheng , Youngsoo Seol

Robust risk minimisation has several advantages: it has been studied with regards to improving the generalisation properties of models and robustness to adversarial perturbation. We bound the distributionally robust risk for a model class…

Machine Learning · Statistics 2018-09-06 Zac Cranko , Simon Kornblith , Zhan Shi , Richard Nock

In this paper a class of Ornstein--Uhlenbeck processes driven by compound Poisson processes is considered. The jumps arrive with exponential waiting times and are allowed to be two-sided. The jumps are assumed to form an iid sequence with…

Probability · Mathematics 2016-09-01 Anders Rønn-Nielsen

In this paper, we study the risk bounds for samples independently drawn from an infinitely divisible (ID) distribution. In particular, based on a martingale method, we develop two deviation inequalities for a sequence of random variables of…

Machine Learning · Statistics 2012-02-20 Chao Zhang , Dacheng Tao

We analyze the practices of reservoir computing in the framework of statistical learning theory. In particular, we derive finite sample upper bounds for the generalization error committed by specific families of reservoir computing systems…

Machine Learning · Computer Science 2019-10-31 Lukas Gonon , Lyudmila Grigoryeva , Juan-Pablo Ortega

In this paper we study the joint ruin problem for two insurance companies that divide between them both claims and premia in some specified proportions (modeling two branches of the same insurance company or an insurance and re-insurance…

Probability · Mathematics 2007-11-16 Florin Avram , Zbigniew Palmowski , Martijn Pistorius

This paper concerns the estimation of sums of functions of observable and unobservable variables. Lower bounds for the asymptotic variance and a convolution theorem are derived in general finite- and infinite-dimensional models. An explicit…

Statistics Theory · Mathematics 2007-06-13 Cun-Hui Zhang

In the extended gambler's ruin problem we can move one step forward or backward (classical gambler's ruin problem), we can stay where we are for a time unit (delayed action) or there can be absorption in the current state (game is…

Probability · Mathematics 2023-03-28 Theo van Uem