Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/136056
Title: NUMERICAL METHODS FOR HIGH DIMENSIONALBACKWARD STOCHASTICDIFFERENTIAL EQUATIONS
Authors: MAJDI RABIA
Keywords: bsde, high dimension, random forest, pricing, finance, 2-BSDE
Issue Date: 28-Apr-2017
Source: MAJDI RABIA (2017-04-28). NUMERICAL METHODS FOR HIGH DIMENSIONALBACKWARD STOCHASTICDIFFERENTIAL EQUATIONS. ScholarBank@NUS Repository.
Abstract: Option Pricing is a well-known subject in the literature since Black and Scholes model first appeared in 1973. However, with the emergence of robust processors, pricing basket options (options on multiple assets) in finance or solving optimisation problems of diversified portfolios became less time-consuming. This is what we aim for in this MSc thesis: explore the currently used computational methods and try new ones for an already settled theory, the High Dimensional Backward Stochastic Differential Equation (HD BSDEs). This special kind of Stochastic Differential Equation, is useful for problems involving final condition hypotheses. Hence, from an ending point, we work backward to an optimal initial solution.
URI: http://scholarbank.nus.edu.sg/handle/10635/136056
Appears in Collections:Master's Theses (Open)

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