Python Backtest Mastery For Risk Parity Portfolios

What you’ll learn

• Implement Modern Risk Parity analysis to select a portfolio of stocks and weights.
• Write a reusable backtesting class that iteratively implements your parameters
• Analytical outputs such as Sharpe Ratio, CAGR, Drawdown, Benchmark Charts , etc.
• Select optimal stock universes from S&P500 data
• Integrate SQL databases for streamlined data retrieval
• Generate key financial metrics for performance review
• Craft a Python backtesting class for strategy analysis
• Utilize Python for dynamic asset allocation
• Backtest how your strategy would have done through time