Jin, Xing, Tan, Hwee Huat and Sun, Junhua. (2007) A state-space partitioning method for pricing high-dimensional American-style options. Mathematical Finance, Vol.17 (No.3). pp. 399-426. ISSN 0960-1627

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Abstract

The pricing of American-style options by simulation-based methods is an important but difficult task primarily due to the feature of early exercise, particularly for high-dimensional derivatives. In this paper, a bundling method based on quasi-Monte Carlo sequences is proposed to price high-dimensional American-style options. The proposed method substantially extends Tilley's bundling algorithm to higher-dimensional situations. By using low-discrepancy points, this approach partitions the state space and forms bundles. A dynamic programming algorithm is then applied to the bundles to estimate the continuation value of an American-style option. A convergence proof of the algorithm is provided. A variety of examples with up to 15 dimensions are investigated numerically and the algorithm is able to produce computationally efficient results with good accuracy.

Item Type:	Journal Article
Subjects:	H Social Sciences > HG Finance H Social Sciences > HC Economic History and Conditions Q Science > QA Mathematics H Social Sciences
Divisions:	Faculty of Social Sciences > Warwick Business School > Finance Group
Journal or Publication Title:	Mathematical Finance
Publisher:	Wiley-Blackwell Publishing, Inc.
ISSN:	0960-1627
Date:	July 2007
Volume:	Vol.17
Number:	No.3
Number of Pages:	28
Page Range:	pp. 399-426
Identification Number:	10.1111/j.1467-9965.2007.00309.x
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
URI:	http://wrap.warwick.ac.uk/id/eprint/31736

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