Portfolio Optimization and Risk Management Using Modern Portfolio Theory

About Course
- Tools & Languages: Python, R, MATLAB, Pandas, NumPy, PyPortfolioOpt, Scikit-learn, SQL
- Objective: Design and optimize an investment portfolio using Modern Portfolio Theory (MPT) and the Efficient Frontier. Utilize machine learning techniques to predict asset returns and optimize the portfolio for maximum returns given specific risk parameters. Backtest the portfolio with historical data and track performance using real-time updates.
- Skills Needed: Portfolio optimization, modern portfolio theory, risk management, machine learning (Python, R), asset allocation, backtesting, financial metrics.
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