Jin, Xing, Li, Xun, Tan, Hwee Huat and Wu, Zhenyu (2013) A computationally efficient state-space partitioning approach to pricing high-dimensional American options via dimension reduction. European Journal of Operational Research, Volume 231 (Number 2). pp. 362-370. doi:10.1016/j.ejor.2013.05.035 ISSN 0377-2217.

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Abstract

This paper studies the problem of pricing high-dimensional American options. We propose a method based on the state-space partitioning algorithm developed by Jin et al. (2007) and a dimension-reduction approach introduced by Li and Wu (2006). By applying the approach in the present paper, the computational efficiency of pricing high-dimensional American options is significantly improved, compared to the extant approaches in the literature, without sacrificing the estimation precision. Various numerical examples are provided to illustrate the accuracy and efficiency of the proposed method. Pseudcode for an implementation of the proposed approach is also included.

Item Type:	Journal Article
Divisions:	Faculty of Social Sciences > Warwick Business School > Finance Group Faculty of Social Sciences > Warwick Business School
Journal or Publication Title:	European Journal of Operational Research
Publisher:	Elsevier Science BV
ISSN:	0377-2217
Official Date:	1 December 2013
Dates:	Date Event 1 December 2013 Published
Volume:	Volume 231
Number:	Number 2
Page Range:	pp. 362-370
DOI:	10.1016/j.ejor.2013.05.035
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

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