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Reclaiming quasi-Monte Carlo efficiency in portfolio value-at-risk simulation through Fourier transform

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Jin, Xing and Zhang, Allen X.. (2006) Reclaiming quasi-Monte Carlo efficiency in portfolio value-at-risk simulation through Fourier transform. Management Science, Vol.52 (No.6). pp. 925-938. ISSN 0025-1909

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Official URL: http://dx.doi.org/10.1287/mnsc.1060.0505

Abstract

Quasi-Monte Carlo methods overcome the problem of sample clustering in regular Monte Carlo simulation and have been shown to improve simulation efficiency in the derivatives pricing literature when the price is expressed as a multidimensional integration and the integrand is suitably smooth. For portfolio value-at-risk (VaR) problems, the distribution of portfolio value change is based on the expectation of an indicator function, hence the integrand is discontinuous. The purpose of this paper is to smooth the expectation estimation of an indicator function via Fourier transform so that the faster convergence rate of quasi-Monte Carlo methods can be reclaimed theoretically. Under fairly mild assumptions, the simulation of portfolio value-at-risk is fast and accurate. Numerical examples elucidate the advantage of the proposed approach over regular Monte Carlo and quasi-Monte Carlo methods.

Item Type: Journal Article
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: Faculty of Social Sciences > Warwick Business School > Finance Group
Faculty of Social Sciences > Warwick Business School
Journal or Publication Title: Management Science
Publisher: Institute for Operations Research and the Management Sciences (I N F O R M S)
ISSN: 0025-1909
Date: June 2006
Volume: Vol.52
Number: No.6
Number of Pages: 14
Page Range: pp. 925-938
Identification Number: 10.1287/mnsc.1060.0505
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: University of Singapore
Grant number: R-146-000-045-101, R-146-000-059-112
URI: http://wrap.warwick.ac.uk/id/eprint/33497

Data sourced from Thomson Reuters' Web of Knowledge

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