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In this paper we present two parallel Monte Carlo based algorithms forpricing multi--dimensional Bermudan/American options. First approach relies oncomputation of the optimal exercise boundary while the second relies onclassification of continuation and exercise values. We also evaluate theperformance of both the algorithms in a desktop grid environment. We show theeffectiveness of the proposed approaches in a heterogeneous computingenvironment, and identify scalability constraints due to the algorithmicstructure.

Parallel Pricing Algorithms for Multi--Dimensional Bermudan/American Options using Monte Carlo methods