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  1. B200 工学部/工学研究科
  2. B200a 雑誌掲載論文
  3. 学術雑誌

Efficient Parallel Implementation of a Weather Derivatives Pricing Algorithm based on the Fast Gauss Transform

http://hdl.handle.net/2237/9478
http://hdl.handle.net/2237/9478
c5b19ddf-a089-418c-916d-d98648238e72
名前 / ファイル ライセンス アクション
yamamoto_1.pdf yamamoto_1.pdf (1.1 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2008-02-26
タイトル
タイトル Efficient Parallel Implementation of a Weather Derivatives Pricing Algorithm based on the Fast Gauss Transform
言語 en
著者 Yamamoto, Yusaku

× Yamamoto, Yusaku

WEKO 22015

en Yamamoto, Yusaku

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 Copyright © 2006 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
抄録
内容記述 CDD weather derivatives are widely used to hedge weather risks and their fast and accurate pricing is an important problem in financial engineering. In this paper, we propose an efficient parallelization strategy of a pricing algorithm for the CDD derivatives. The algorithm uses the fast Gauss transform to compute the expected payoff of the derivative and has proved faster and more accurate than the conventional Monte Carlo method. However, speeding up the algorithm on a distributed-memory parallel computer is not straightforward because naїve parallelization will require a large amount of inter-processor communication. our new parallelization strategy exploits the structure of the fast Gauss transform and thereby reduces the amount of inter-processor communication considerably. Numerical experiments show that our strategy achieves up to 50 % performance improvement over the naїve one on an 16-node Mac G5 cluster and can compute the price of a representative CDD derivative in 7 seconds. This speed is adequate for almost any applications.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/IPDPS.2006.1639615
ISBN
関連タイプ isPartOf
識別子タイプ ISBN
関連識別子 1-4244-0054-6
書誌情報 en : 20th International Parallel and Distributed Processing Symposium

p. 8-8, 発行日 2006
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/9478
識別子タイプ HDL
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