A collection (yet to finish) of Python implementations for core quantitative risk management techniques, aligned with industry practices.
| Risk Type | Key Methods |
|---|---|
| Market Risk | VaR (Historical/Parametric/MC), Expected Shortfall, GARCH, Backtesting |
| Credit Risk | PD Models (Merton/Logistic), Credit VaR, CDS Pricing, Z-Score |
| Liquidity Risk | Bid-Ask Spread Analysis, Liquidity-Adjusted VaR (LVaR) |
| Term Structure | Yield Curve Interpolation (Nelson-Siegel, Cubic Splines), Bootstrapping Zero-Coupon Yields |
| Portfolio Risk | Efficient Frontier, Risk Parity, PCA Factor Models |
| ML in Risk | XGBoost for Default Prediction, SHAP Explainability, RL for Hedging |
- Clone the repo:
git clone https://github.com/Jmmostafa/quant-risk-mgmt.git cd quant-risk-mgmt