Numberical Method for Backward Stochastic Differential Equations
By Jin Ma, Philip Protter, J. S. Martín, S. Torres. 2002
140 citations recorded by the source corpus.
Subfields: Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a9346c946dc2cc0af56fba17e0104ac0cb5778a1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Nizar Touzi
- Christian Bender
- Bruno Bouchard
- Emmanuel Gobet
- Jessica Steiner
- D. Crisan
- Xavier Warin
- H. M. Soner
In Statistics and Probability
- Christian Bender
- Jessica Steiner
- Bruno Bouchard
- Nizar Touzi
- Emmanuel Gobet
- Xavier Warin
- Romuald Elie
- H. M. Soner
Citations in the corpus
- A general theory of finite state Backward Stochastic Difference Equations (2008, methodology): “In [3], a similar existence theorem for a solution (Y,Z) is proven using the assumption that F is Lipschitz, and a fixed point argument is used.”
- Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations (2004, methodology): “Discrete-time scheme based on the approximation of the Brownian motion by some discrete process have been considered in [10], [12], [8], [1] and [ 22 ].”
- Discrete time approximation of decoupled Forward-Backward SDE with jumps (2008, background): “and [ 17 ]), our scheme does not provide a fully implementable numerical procedure since it involves the computation of a large number of conditional expectations.”
- Rate of convergence of an empirical regression method for solving generalized backward stochastic differential equations (2006, methodology): “This is achieved either by replacing the Brownian motion by a random walk (see Briand et al. 2001; Ma et al. 2002) or by using quantization techniques (see Bally and Pagès 2003).”
- Least-Squares Monte Carlo for Backward SDEs (2012, methodology): “Different techniques have been suggested in the literature including: • Approximation of the driving Brownian motion by trees for low-dimensional problems, see Briand et al. (2001) and Ma et al. (2002).”
- Second‐order backward stochastic differential equations and fully nonlinear parabolic PDEs (2005, methodology): “Member of the Turkish Academy of Sciences and this work was partly supported by the Turkish Academy of Sciences.”