A regression-based Monte Carlo method to solve backward stochastic   differential equations
  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. 
Emmanuel Gobet, Jean-Philippe Lemor and Xavier Warin