Perturbative Expansion Technique for Non-linear FBSDEs with Interacting Particle Method
AbstractIn this paper, we propose an efficient Monte Carlo implementation of non-linear FBSDEs as a system of interacting particles inspired by the ideas of branching diffusion method. It will be particularly useful to investigate large and complex systems, and hence it is a good complement of our previous work presenting an analytical perturbation procedure for generic non-linear FBSDEs. There appear multiple species of particles, where the first one follows the diffusion of the original underlying state, and the others the Malliavin derivatives with a grading structure. The number of branching points are capped by the order of perturbation, which is expected to make the scheme less numerically intensive. The proposed method can be applied to semi-linear problems, such as American and Bermudan options, Credit Value Adjustment (CVA), and even fully non-linear issues, such as the optimal portfolio problems in incomplete and/or constrained markets, feedbacks from large investors, and also the analysis of various risk measures.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1204.2638.
Date of creation: Apr 2012
Date of revision: Apr 2012
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- Akihiko Takahashi & Toshihiro Yamada, 2013. "On an Asymptotic Expansion of Forward-Backward SDEs with a Perturbed Driver," CIRJE F-Series CIRJE-F-902, CIRJE, Faculty of Economics, University of Tokyo.
- Akihiko Takahashi & Toshihiro Yamada, 2013. "On an Asymptotic Expansion of Forward-Backward SDEs with a Perturbed Driver," CARF F-Series CARF-F-326, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Oct 2013.
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