A New Algorithm for Monte Carlo for American Options

Mallier, Roland, and Alobaidi, Ghada. "A New Algorithm for Monte Carlo for American Options." Serdica Mathematical Journal 29.3 (2003): 271-290. <http://eudml.org/doc/219630>.

@article{Mallier2003,
abstract = {2000 Mathematics Subject Classification: 91B28, 65C05.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.},
author = {Mallier, Roland, Alobaidi, Ghada},
journal = {Serdica Mathematical Journal},
keywords = {American Options; Monte Carlo; American options},
language = {eng},
number = {3},
pages = {271-290},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {A New Algorithm for Monte Carlo for American Options},
url = {http://eudml.org/doc/219630},
volume = {29},
year = {2003},
}

TY - JOUR
AU - Mallier, Roland
AU - Alobaidi, Ghada
TI - A New Algorithm for Monte Carlo for American Options
JO - Serdica Mathematical Journal
PY - 2003
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 29
IS - 3
SP - 271
EP - 290
AB - 2000 Mathematics Subject Classification: 91B28, 65C05.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.
LA - eng
KW - American Options; Monte Carlo; American options
UR - http://eudml.org/doc/219630
ER -