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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1711

Title: A New Algorithm for Monte Carlo for American Options
Authors: Mallier, Roland
Alobaidi, Ghada
Keywords: American Options
Monte Carlo
Issue Date: 2003
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Serdica Mathematical Journal, Vol. 29, No 3, (2003), 271p-290p
Abstract: We consider the valuation of American options using Monte Carlo simulation, and propose a new technique which involves approximating the optimal exercise boundary. Our method involves splitting the boundary into a linear term and a Fourier series and using stochastic optimization in the form of a relaxation method to calculate the coefficients in the series. The cost function used is the expected value of the option using the the current estimate of the location of the boundary. We present some sample results and compare our results to other methods.
Description: 2000 Mathematics Subject Classification: 91B28, 65C05.
URI: http://hdl.handle.net/10525/1711
ISSN: 1310-6600
Appears in Collections:Volume 29 Number 3

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