Artificial intelligence/machine learning for wealth management on mobile device
Traditionally, portfolio management involves balancing a portfolio with different assets using statistical methods of analysis. These analyses are typically performed by portfolio managers or expert investors. For the amateur investor, the level of research required to form a solid understanding...
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Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
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Online Access: | https://hdl.handle.net/10356/156611 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Traditionally, portfolio management involves balancing a portfolio with different assets using
statistical methods of analysis. These analyses are typically performed by portfolio managers or
expert investors. For the amateur investor, the level of research required to form a solid
understanding of assets can be unmanageable. In the absence of time, tools, or level of
information to match the experts, this project explores artificial intelligence solutions that may
aid in reducing the analytical gap between amateur investors and financial experts.
Our goal is to create an application that is intuitive to an amateur investor while maintaining the
technicalities required for deep valuations of portfolio assets. Apart from the ability to learn and
predict optimal allocations of portfolios, the application provides supplementary features
automating the analysis of a portfolio using standard modern portfolio theory (MPT) frameworks.
The mobile application is developed using the Dart programming language along with the Flutter
Framework. A variant of the deep reinforcement learning algorithm known as proximal policy
optimization (PPO) is used as the agent to learn an investor’s portfolio and suggest optimal stock
allocations for maximized returns.
It is imperative to note that this mobile application is a proof of concept and is not financial
advice.
Keywords: Analysis; Reinforcement Learning; Mobile Application; Amateur Investor |
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