A review of conditional rare event simulation for tail probabilities of heavy tailed random variables



Rojas Nandayapa, L ORCID: 0000-0001-5652-3183
(2013) A review of conditional rare event simulation for tail probabilities of heavy tailed random variables. Boletín de la Sociedad Matemática Mexicana, 19 (2). 159 - 182.

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Abstract

Approximating the tail probability of a sum of heavy-tailed random variables is a difficult problem. In this review we exhibit the challenges of approximating such probabilities and concentrate on a rare event simulation methodology capable of delivering the most reliable results: Conditional Monte Carlo. To provide a better flavor of this topic we further specialize on two algorithms which were specifically designed for tackling this problem: the Asmussen-Binswanger estimator and the Asmussen-Kroese estimator. We extend the applicability of these estimators to the non-independent case and prove their efficiency.

Item Type: Article
Depositing User: Symplectic Admin
Date Deposited: 31 May 2017 09:29
Last Modified: 09 Jan 2021 06:49
URI: https://livrepository.liverpool.ac.uk/id/eprint/3007728