Solving High Dimensional PDEs with Machine Learning Methods and Its Application in Option Pricing

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Aghapour, Ahmad | 2024

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 57253 (44)
University: Sharif University of Technology
Department: Management and Economics
Advisor(s): Arian, Hamid Reza; Zamani, Shiva
Abstract:
differential equations. These methods have extensive applications in the financial domain, including in risk hedging and derivative pricing. One of the main advantages of using deep learning methods in this area is their high capability to solve high-dimensional problems. Despite the introduction of these new methods, some of them have not performed well in certain problems. In this research, efforts have been made to improve the efficiency of these methods by enhancing the neural network architecture and modifying the learning process
Keywords:
Partial Differential Equations ; Machine Learning ; Deep Learning ; Option Pricing ; Network Architecture