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An improved simulation method for pricing high-dimensional American derivatives

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Title: An improved simulation method for pricing high-dimensional American derivatives
Authors: Boyle, Phelim P.1, Kolkiewicz, Adam W.2, Tan, Ken Seng2 kstan@uwaterloo.ca
Source: Mathematics & Computers in Simulation. Mar2003, Vol. 62 Issue 3-6, p315. 8p.
Subjects: Monte Carlo method, Dynamic programming
Abstract: In this paper, we propose an estimator for pricing high-dimensional American-style options and show that asymptotically its upper bias converges to zero. An advantage of the proposed estimator is that when combined with low discrepancy sequences, it exhibits a superior rate of convergence. Numerical examples are conducted to demonstrate its efficiency. [Copyright &y& Elsevier]
Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 9192067
AccessLevel: 6
PubType: Periodical
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PreciseRelevancyScore: 0
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  Data: An improved simulation method for pricing high-dimensional American derivatives
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  Data: <searchLink fieldCode="AR" term="%22Boyle%2C+Phelim+P%2E%22">Boyle, Phelim P.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kolkiewicz%2C+Adam+W%2E%22">Kolkiewicz, Adam W.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Tan%2C+Ken+Seng%22">Tan, Ken Seng</searchLink><relatesTo>2</relatesTo><i> kstan@uwaterloo.ca</i>
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  Data: <searchLink fieldCode="JN" term="%22Mathematics+%26+Computers+in+Simulation%22">Mathematics & Computers in Simulation</searchLink>. Mar2003, Vol. 62 Issue 3-6, p315. 8p.
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  Data: In this paper, we propose an estimator for pricing high-dimensional American-style options and show that asymptotically its upper bias converges to zero. An advantage of the proposed estimator is that when combined with low discrepancy sequences, it exhibits a superior rate of convergence. Numerical examples are conducted to demonstrate its efficiency. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/S0378-4754(02)00248-3
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 315
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      – SubjectFull: Dynamic programming
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              Text: Mar2003
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