| Proj No. | A1088-251 |
| Title | Machine learning and quantitative trading in stock market |
| Summary | Machine learning models such as recurrent neural networks (RNN) have shown promise in predicting temporal sequences, such as stock prices, using historical data. Stock market trends are difficult to predict even for experienced analysts due to the complexity of the market and unknown factors. There has been increasing interest in the use of machine learning to predict stock prices. A model that accurately predicts stock prices could directly impact the profits of investment firms and traders. The aim of the project is to investigate and compare the performance of different machine learning models in stock price prediction. The student can experiment on major factors from technical, fundamental, and sentiment analyses. This project will definitely be rewarding to those who have strong interests in stock trading/investing. |
| Supervisor | A/P Wong Jia Yiing, Patricia (Loc:S1 > S1 B1B > S1 B1B 58, Ext: +65 67904219) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Internet of Things Laboratory (Loc: S1-B4c-14, ext: 5470/5475) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |