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In this paper we propose a novel dual regression-based approach for pricingAmerican options. This approach reduces the complexity of the nested MonteCarlo method and has especially simple form for time discretised diffusionprocesses. We analyse the complexity of the proposed approach both in the caseof fixed and increasing number of exercise dates. The method is illustrated byseveral numerical examples.

Regression-based complexity reduction of the nested Monte Carlo methods