Numerical approximation of general Lipschitz BSDEs with branching processes

DOI10.1051/proc/201965309zbMath1416.60070arXiv1710.10933OpenAlexW2963493040MaRDI QIDQ4967879

Xiaolu Tan, Bruno Bouchard, Xavier Warin

Publication date: 11 July 2019

Published in: ESAIM: Proceedings and Surveys (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.10933

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Branching processes (Galton-Watson, birth-and-death, etc.) (60J80)

Related Items

Monotone methods in counterparty risk models with nonlinear Black-Scholes-type equations ⋮ Stability of backward stochastic differential equations: the general Lipschitz case ⋮ Nesting Monte Carlo for high-dimensional non-linear PDEs ⋮ High order one-step methods for backward stochastic differential equations via Itô-Taylor expansion

Uses Software

• StOpt

Cites Work

• Fundamentals and advanced techniques in derivatives hedging. Translated from the French
• A numerical scheme for BSDEs
• Numerical approximation of BSDEs using local polynomial drivers and branching processes
• Nesting Monte Carlo for high-dimensional non-linear PDEs
• Branching diffusion representation of semilinear PDEs and Monte Carlo approximation
• Representation theorems for backward stochastic differential equations
• Applications of Malliavin calculus to Monte Carlo methods in finance
• When terminal facelift enforces delta constraints
• On the branching process for Brownian particles with an absorbing boundary
• Some non-monotone schemes for time dependent Hamilton-Jacobi-Bellman equations in stochastic control
• A numerical algorithm for a class of BSDEs via the branching process
• Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations
• A regression-based Monte Carlo method to solve backward stochastic differential equations
• Error analysis of the optimal quantization algorithm for obstacle problems.
• Monte-Carlo Valuation of American Options: Facts and New Algorithms to Improve Existing Methods
• Application of brownian motion to the equation of kolmogorov-petrovskii-piskunov
• Backward Stochastic Differential Equations in Finance
• Branching Diffusion Processes

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