Machine Learning-based Portfolio Optimization
Zikang Jia, Ankit NA, Demilade Akinbile, Yuanhang Lu
The proposed project aims to optimize portfolios in quantitative finance using machine learning techniques. It involves collecting and cleaning relevant financial data, selecting appropriate factors, and designing trading strategies. Machine learning algorithms will be utilized to estimate expected returns or volatility. Some backtesting to evaluate performance and refining the models based on the results are also expected. The ultimate goal is to develop an adaptive portfolio optimization framework.