| Proj No. | A1092-251 |
| Title | Pairs trading using statistical arbitrage with cointegration analysis |
| Summary | Pairs trading is a market-neutral strategy that takes advantage of the historical relationship between two correlated assets. This project explores statistical arbitrage by identifying asset pairs that move together and using cointegration analysis to detect profitable trading opportunities. Unlike simple correlation, cointegration ensures that the price spread between two assets remains stable over time, even if individual prices fluctuate. When the spread deviates significantly from its historical mean, traders can go long on the underperforming asset and short the outperforming one, expecting the relationship to revert. This approach relies on statistical techniques like the Augmented Dickey-Fuller (ADF) test and the Johansen test to confirm cointegration. Machine learning and time series modeling can further enhance trade selection and risk management. Pairs trading is widely used in equities, commodities, and forex markets due to its low market exposure and ability to profit in various conditions. However, risks include breakdowns in historical relationships and execution costs. By leveraging cointegration analysis, this project provides a systematic and data-driven framework for identifying profitable pairs, helping traders execute strategies with higher confidence and reduced directional market 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?: |