arXiv:math/0508491 Abstract

arXiv:math/0508491 [math.PR]Abstract References Reviews Resources

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

Emmanuel Gobet, Jean-Philippe Lemor, Xavier Warin

Published 2005-08-25Version 1

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.

Comments: 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)

Journal: Annals of Applied Probability 2005, Vol. 15, No. 3, 2172-2202

DOI: 10.1214/105051605000000412

Categories: math.PR

Subjects: 60H10, 60H10, 65C30

Keywords: backward stochastic differential equations, regression-based monte carlo method, monte carlo simulations, full convergence analysis, differential interest rates

Tags: journal article

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