Iterative Improvement of Lower and Upper Bounds for Backward SDEs

DOI10.1137/16M1081348zbMath1365.65011MaRDI QIDQ5738163

Christian Bender, Christian Gärtner, Nikolaus Schweizer

Publication date: 31 May 2017

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

zbMATH Keywords

dynamic programmingMonte Carlobackward stochastic differential equationsfinancial applicationiterated improvement

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Dynamic programming in optimal control and differential games (49L20) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (3)

Overcoming the curse of dimensionality in the numerical approximation of backward stochastic differential equations ⋮ ``Regression anytime with brute-force SVD truncation ⋮ Pathwise Dynamic Programming

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