A New Algorithm for Monte Carlo for American Options
Serdica Mathematical Journal, Tome 29 (2003) no. 3, pp. 271-290
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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.
Keywords:
American Options, Monte Carlo
Mallier, Roland; Alobaidi, Ghada. A New Algorithm for Monte Carlo for American Options. Serdica Mathematical Journal, Tome 29 (2003) no. 3, pp. 271-290. http://geodesic.mathdoc.fr/item/SMJ2_2003_29_3_a3/
@article{SMJ2_2003_29_3_a3,
author = {Mallier, Roland and Alobaidi, Ghada},
title = {A {New} {Algorithm} for {Monte} {Carlo} for {American} {Options}},
journal = {Serdica Mathematical Journal},
pages = {271--290},
year = {2003},
volume = {29},
number = {3},
language = {en},
url = {http://geodesic.mathdoc.fr/item/SMJ2_2003_29_3_a3/}
}