| Proj No. | A3210-251 |
| Title | Machine Learning–Based Portfolio Optimization and Stock Price Trend Analysis |
| Summary | This project aims to apply machine learning techniques to optimize personal investment portfolios with a primary focus on stock market investments. The project will explore how different allocations across stocks, bonds, and fixed deposits (FDs) affect overall returns based on varying investment horizons and risk profiles. Stock price trends will be analyzed and predicted using machine learning models such as regression, recurrent neural networks (RNN/LSTM), and reinforcement learning to guide allocation strategies. The outcome of this project will be a data-driven framework that assists individual investors in making informed allocation decisions, balancing risk and return effectively. |
| Supervisor | A/P Wang Lipo (Loc:S1 > S1 B1C > S1 B1C 98, Ext: +65 67906372) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Computer Engineering I (Loc: S2-B4c-15) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |