Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/25847
Title: | Numerical Analysis of Two-Asset Options in a Finite Liquidity Framework |
Authors: | Kevin Shuai Zhang |
Advisor: | Pirvu, Traian |
Department: | Mathematics and Statistics |
Keywords: | Mathematical Finance;Derivative Pricing;Stochastic Analysis;Computational Finance;Machine Learning;Deep Learning |
Publication Date: | 2020 |
Abstract: | In this manuscript, we develop a nite liquidity framework for two-asset markets. In contrast to the standard multi-asset Black-Scholes framework, trading in our market model has a direct impact on the asset's price. The price impact is incorporated into the dynamics of the first asset through a specific trading strategy, as in large trader liquidity models. We adopt Euler- Maruyama and Milstein scheme in the simulation of asset prices. Exchange and Spread option values are numerically estimated by Monte Carlo with the Margrabe option as a controlled variate. The time complexity of these numerical schemes is included. Finally, we provide some deep learning frameworks to implement these pricing models effectively. |
URI: | http://hdl.handle.net/11375/25847 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Thesis.pdf | 3.47 MB | Adobe PDF | View/Open |
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