Quantitative Hedge Fund Strategy Using Factor Investing

About Course
- Tools & Languages: Python, R, MATLAB, QuantConnect, Pandas, NumPy, Scikit-learn, SQL
- Objective: Develop a quantitative hedge fund strategy based on factor investing (e.g., momentum, value, growth). Identify and model factors that drive excess returns across multiple asset classes. Use backtesting frameworks like QuantConnect to test the performance of the strategy over historical data and adjust dynamically to market conditions.
- Skills Needed: Quantitative finance, factor investing, asset allocation, backtesting (QuantConnect), machine learning (Python, R), portfolio risk management.
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