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, RolandAlobaidi, Ghada Keywords: American OptionsMonte 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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