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A regression-based Monte Carlo method to solve backward stochastic differential equations

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arxiv math/0508491 v1 pith:ETPODBON submitted 2005-08-25 math.PR

Emmanuel Gobet , Jean-Philippe Lemor , Xavier Warin This is my paper
classification math.PR
keywords differentialnumericalbackwardcarloequationsmontestochasticanalysis
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We are concerned with the numerical resolution of backward stochastic differential equations. We propose a new numerical scheme based on iterative regressions on function bases, which coefficients are evaluated using Monte Carlo simulations. A full convergence analysis is derived. Numerical experiments about finance are included, in particular, concerning option pricing with differential interest rates.

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  1. Quantum Derivative Pricing for SPDEs via BDSDE Representation

    quant-ph 2026-06 unverdicted novelty 5.0 of 10

    Quantum-accelerated MLMC methods for BDSDE-based SPDE derivative pricing and Greeks achieve sampling complexity improvement from O(ε^{-2}) to O(ε^{-1}).

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