American Options Based on Malliavin Calculus and Nonparametric Variance Reduction Methods
Lokman Abbas-Turki and
Bernard Lapeyre
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Lokman Abbas-Turki: LAMA
Bernard Lapeyre: CERMICS
Papers from arXiv.org
Abstract:
This paper is devoted to pricing American options using Monte Carlo and the Malliavin calculus. Unlike the majority of articles related to this topic, in this work we will not use localization fonctions to reduce the variance. Our method is based on expressing the conditional expectation E[f(St)/Ss] using the Malliavin calculus without localization. Then the variance of the estimator of E[f(St)/Ss] is reduced using closed formulas, techniques based on a conditioning and a judicious choice of the number of simulated paths. Finally, we perform the stopping times version of the dynamic programming algorithm to decrease the bias. On the one hand, we will develop the Malliavin calculus tools for exponential multi-dimensional diffusions that have deterministic and no constant coefficients. On the other hand, we will detail various nonparametric technics to reduce the variance. Moreover, we will test the numerical efficiency of our method on a heterogeneous CPU/GPU multi-core machine.
Date: 2011-04, Revised 2011-04
New Economics Papers: this item is included in nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1104.5131
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