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

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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.
Published at http://dx.doi.org/10.1214/105051605000000412 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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Probability, 60H10, 60H10, 65C30 (Primary)

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http://salesiana.dossiersoluciones.com/handle/123456789/76154

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/math/0508491
 http://arxiv.org/abs/math/0508491
 Annals of Applied Probability 2005, Vol. 15, No. 3, 2172-2202
 doi:10.1214/105051605000000412

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arXiv