Built for anyone doing serious quant work in Python who needs to move fast on strategy development and risk analysis. Covers the full pipeline: algo trading with walk-forward validation to catch overfitting, risk models like VaR and Greeks, portfolio optimization from mean-variance to risk parity, and Monte Carlo for derivatives pricing. The focus on vectorized NumPy/Pandas operations is smart since performance matters when you're backtesting or running simulations. This handles both the math-heavy stuff (factor modeling, time series analysis) and practical concerns like transaction costs and rebalancing. Good fit if you're building trading systems or need to analyze market microstructure without reinventing statistical wheels.
npx skills add https://github.com/404kidwiz/claude-supercode-skills --skill quant-analyst