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Article Dans Une Revue The Journal of Computational Finance Année : 2020

Pricing path-dependent Bermudan options using Wiener chaos expansion: an embarrassingly parallel approach

Jérôme Lelong

Résumé

In this work, we propose a new policy iteration algorithm for pricing Bermudan options when the payoff process cannot be written as a function of a lifted Markov process. Our approach is based on a modification of the well-known Longstaff Schwartz algorithm, in which we basically replace the standard least square regression by a Wiener chaos expansion. Not only does it allow us to deal with a non Markovian setting, but it also breaks the bottleneck induced by the least square regression as the coefficients of the chaos expansion are given by scalar products on the L^2 space and can therefore be approximated by independent Monte Carlo computations. This key feature enables us to provide an embarrassingly parallel algorithm.
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Dates et versions

hal-01983115 , version 1 (16-01-2019)
hal-01983115 , version 2 (07-07-2020)

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Jérôme Lelong. Pricing path-dependent Bermudan options using Wiener chaos expansion: an embarrassingly parallel approach. The Journal of Computational Finance, 2020, 24 (2), pp.1-31. ⟨10.21314/JCF.2020.394⟩. ⟨hal-01983115v2⟩
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