| Proj No. | A1086-251 |
| Title | Building of a machine learning powered high frequency algorithmic trading bot |
| Summary | This project aims to investigate various Machine Learning applications in the development of a High-Frequency Algorithmic Trading Bot, capable of executing complex trading strategies and reacting to market conditions in real time. The research will explore multiple ML techniques, such as reinforcement learning, deep learning, and statistical modeling, to enhance predictive accuracy and decision-making speed. The project focuses on evaluating different ML models based on key metrics, including adaptability to dynamically changing market conditions and effectiveness in optimizing trade execution for maximum profitability and efficiency. By implementing advanced feature engineering techniques, the model can extract meaningful patterns from vast amounts of market data, improving its predictive capabilities. Additionally, the bot’s decision-making process will be fine-tuned using backtesting and live simulations to ensure robustness in real-world scenarios. Subsequently, its performance can be tested across various asset classes and sectors, ensuring generalization across different markets. Comparative analyses will be conducted to measure its success against traditional algorithmic strategies and human traders. Ultimately, the goal is to develop a highly adaptive and efficient trading system that maximizes returns while minimizing risk. |
| 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?: |