Article

Derivatives and credit risk: enhanced quasi-monte carlo methods with dimension reduction

Authors:

Junichi Imai,

Ken Seng TanAuthors Info & Claims

WSC '02: Proceedings of the 34th conference on Winter simulation: exploring new frontiers

Pages 1502 - 1510

Published: 08 December 2002 Publication History

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Abstract

In recent years, the quasi-Monte Carlo approach for pricing high-dimensional derivative securities has been used widely relative to other competitive approaches such as the Monte Carlo methods. Such success can be, in part, attributed to the notion of effective dimension of the finance problems. In this paper, we provide additional insight on the connection between the effective dimension and the quasi-Monte Carlo method. We also propose a dimension reduction technique which further enhances the quasi-Monte Carlo method for derivative pricing. The efficiency of the proposed method is illustrated by applying it to high-dimensional multi-factor path-dependent derivative securities.

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Cited By

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Wang X(2009)Dimension Reduction Techniques in Quasi-Monte Carlo Methods for Option PricingINFORMS Journal on Computing10.1287/ijoc.1080.030421:3(488-504)Online publication date: 1-Jul-2009
https://dl.acm.org/doi/10.1287/ijoc.1080.0304
L'Ecuyer PParent-Chartier JDion MJefferson TFowler JIngalls R(2008)Simulation of a Lévy process by PCA sampling to reduce the effective dimensionProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516830(436-443)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516830
Wang X(2006)On the Effects of Dimension Reduction Techniques on Some High-Dimensional Problems in FinanceOperations Research10.1287/opre.1060.033454:6(1063-1078)Online publication date: 1-Nov-2006
https://dl.acm.org/doi/10.1287/opre.1060.0334
Show More Cited By

Derivatives and credit risk: enhanced quasi-monte carlo methods with dimension reduction
1. Mathematics of computing
  1. Probability and statistics
    1. Probabilistic reasoning algorithms

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Information

Published In

WSC '02: Proceedings of the 34th conference on Winter simulation: exploring new frontiers

December 2002

2143 pages

ISBN:0780376153

General Chair:
Jane L. Snowdon
IBM T. J. Watson Research Center, Yorktown Heights, NY
,
Program Chair:
John M. Charnes
The University of Kansas, Lawrence, KS

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Winter Simulation Conference

Publication History

Published: 08 December 2002

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WSC02: Winter Simulation Conference 2002

December 8 - 11, 2002

California, San Diego

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WSC '02 Paper Acceptance Rate 166 of 185 submissions, 90%;

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Cited By

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Wang X(2009)Dimension Reduction Techniques in Quasi-Monte Carlo Methods for Option PricingINFORMS Journal on Computing10.1287/ijoc.1080.030421:3(488-504)Online publication date: 1-Jul-2009
https://dl.acm.org/doi/10.1287/ijoc.1080.0304
L'Ecuyer PParent-Chartier JDion MJefferson TFowler JIngalls R(2008)Simulation of a Lévy process by PCA sampling to reduce the effective dimensionProceedings of the 40th Conference on Winter Simulation10.5555/1516744.1516830(436-443)Online publication date: 7-Dec-2008
https://dl.acm.org/doi/10.5555/1516744.1516830
Wang X(2006)On the Effects of Dimension Reduction Techniques on Some High-Dimensional Problems in FinanceOperations Research10.1287/opre.1060.033454:6(1063-1078)Online publication date: 1-Nov-2006
https://dl.acm.org/doi/10.1287/opre.1060.0334
L'Ecuyer P(2004)Quasi-Monte Carlo methods in financeProceedings of the 36th conference on Winter simulation10.5555/1161734.1162040(1645-1655)Online publication date: 5-Dec-2004
https://dl.acm.org/doi/10.5555/1161734.1162040
Lemieux C(2004)Randomized Quasi-Monte CarloProceedings of the 36th conference on Winter simulation10.5555/1161734.1162022(1565-1573)Online publication date: 5-Dec-2004
https://dl.acm.org/doi/10.5555/1161734.1162022
Staum JFerrin DMorrice D(2003)State of the art tutorial II: simulations for financial engineeringProceedings of the 35th conference on Winter simulation: driving innovation10.5555/1030818.1030856(258-266)Online publication date: 7-Dec-2003
https://dl.acm.org/doi/10.5555/1030818.1030856

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