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A primal-dual algorithm for BSDEs. (English) Zbl 1423.91008

Summary: We generalize the primal-dual methodology, which is popular in the pricing of early-exercise options, to a backward dynamic programming equation associated with time discretization schemes of (reflected) backward stochastic differential equations (BSDEs). Taking as an input some approximate solution of the backward dynamic program, which was precomputed, e.g., by least-squares Monte Carlo, this methodology enables us to construct a confidence interval for the unknown true solution of the time-discretized (reflected) BSDE at time 0. We numerically demonstrate the practical applicability of our method in two 5-dimensional nonlinear pricing problems where tight price bounds were previously unavailable.

MSC:

91G60 Numerical methods (including Monte Carlo methods)
65C05 Monte Carlo methods
60H10 Stochastic ordinary differential equations (aspects of stochastic analysis)
91G20 Derivative securities (option pricing, hedging, etc.)

References:

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