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Phone: (843) 722-7550
West Ashley Library
9 a.m. - 6 p.m.
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An analysis of a least squares regression method for American option pricing.
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- Author(s): Clément, Emmanuelle; Lamberton, Damien; Protter, Philip
- Source:
Finance & Stochastics; 2002, Vol. 6 Issue 4, p449, 23p- Subject Terms:
- Source:
- Additional Information
- Subject Terms:
- Abstract: Recently, various authors proposed Monte-Carlo methods for the computation of American option prices, based on least squares regression. The purpose of this paper is to analyze an algorithm due to Longstaff and Schwartz. This algorithm involves two types of approximation. Approximation one: replace the conditional expectations in the dynamic programming principle by projections on a finite set of functions. Approximation two: use Monte-Carlo simulations and least squares regression to compute the value function of approximation one. Under fairly general conditions, we prove the almost sure convergence of the complete algorithm. We also determine the rate of convergence of approximation two and prove that its normalized error is asymptotically Gaussian. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Finance & Stochastics is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. 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.)
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