1. Apply statistical and machine learning models to combine thousands of alpha signals.
2. Conduct research on portfolio construction to maximize the value of alpha.
3. Investigate into stock risk model: search for new risk factors, research on market liquidity and volatility.
4. Evaluate the new alpha generated by other researchers, and integrate the new alpha into the portfolio.
5. Systematically analyze the performance of each combination in live trading environment and make necessary adjustments to them.
6. Use Python to develop necessary tools in all above research.
1. Master or doctor degree in science or engineering with excellent quantitative skills and logical thinking, and has a strong interest in quantitative strategy research.
2. Excellent programming skills (must be able to use python, C++ is a plus), proficient in various data structures and algorithms.
3. Comprehensive understanding of various statistical models, including traditional statisticis and basic machine learning algorithms.