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

Emmanuel Gobet·Jean-Philippe Lemor·Xavier Warin
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Abstract

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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Emmanuel Gobet, Jean-Philippe Lemor, Xavier Warin. 2005-08-25. A regression-based Monte Carlo method to solve backward stochastic differential equations. https://doi.org/10.1214/105051605000000412

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