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View all- Roch A(2023)Optimal Liquidation Through a Limit Order Book: A Neural Network and Simulation ApproachMethodology and Computing in Applied Probability10.1007/s11009-023-09996-z25:1Online publication date: 27-Jan-2023
Regression-Based Complexity Reduction of the Nested Monte Carlo Methods
Pages 665 - 689
Abstract
In this paper we propose a novel dual regression-based approach for pricing American options. This approach reduces the complexity of the nested Monte Carlo method and has an especially simple form for time discretized diffusion processes. We analyze the complexity of the proposed approach in the case of both fixed and increasing numbers of exercise dates. The method is illustrated by several numerical examples.
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Published: 01 January 2018
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View all- Roch A(2023)Optimal Liquidation Through a Limit Order Book: A Neural Network and Simulation ApproachMethodology and Computing in Applied Probability10.1007/s11009-023-09996-z25:1Online publication date: 27-Jan-2023