Study of new rare event simulation schemes and their application to extreme scenario generation

Agarwal, A. , De Marco, S., Gobet, E. and Liu, G. (2018) Study of new rare event simulation schemes and their application to extreme scenario generation. Mathematics and Computers in Simulation, 143, pp. 89-98. (doi: 10.1016/j.matcom.2017.05.004)

Abstract

This is a companion paper based on our previous work on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods with comparisons of numerical performance. In numerical tests, we also illustrate the idea of extreme scenario generation based on the convergence of marginal distributions of the underlying Markov chains and show the impact of the discretization of continuous time models on rare event probability estimation.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Agarwal, Dr Ankush
• Authors: Agarwal, A., De Marco, S., Gobet, E., and Liu, G.
• Subjects: Q Science > QA Mathematics
• College/School: College of Social Sciences > Adam Smith Business School > Economics
• Journal Name: Mathematics and Computers in Simulation
• Publisher: Elsevier
• ISSN: 0378-4754
• ISSN (Online): 1872-7166
• Published Online: 30 May 2017
• Copyright Holders: Copyright © 2017 International Association for Mathematics and Computers in Simulation (IMACS)
• First Published: First published in Mathematics and Computers in Simulation 143: 89-98
• Publisher Policy: Reproduced in accordance with the publisher copyright policy