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Rapport Année : 2011

Approximation of discrete BSDE using least-squares regression

Résumé

We consider the dynamic programming equation arising from the time-discretization of backward stochastic differential equations. When the sequence of conditional expectations is computed using empirical least-squares regressions, we show that the Multi step-forward Dynamic Programming (MDP) equation yields better error estimates than the usual One-step forward DP (ODP) equation. We provide full error estimates, depending on the time-grid, the number of simulations and the approximation spaces for regression. The generator is assumed to be locally Lipschitz, which includes some cases of quadratic drivers.
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Dates et versions

hal-00642685 , version 1 (18-11-2011)
hal-00642685 , version 2 (28-06-2013)
hal-00642685 , version 3 (09-07-2013)
hal-00642685 , version 4 (25-03-2014)

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  • HAL Id : hal-00642685 , version 1

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Emmanuel Gobet, Plamen Turkedjiev. Approximation of discrete BSDE using least-squares regression. 2011. ⟨hal-00642685v1⟩
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