Advanced PPNR Modeling

A practitioner-grade course on Pre-Provision Net Revenue (PPNR) modeling for the banking industry. Students master the full PPNR forecasting pipeline — from regulatory context (CCAR, DFAST, IFRS 9) to advanced econometric and machine learning techniques — and produce a defensible 9-quarter stressed forecast across Baseline, Adverse, and Deep Recession scenarios. Topics span balance sheet deconstruction, macro scenario translation, ARDL/VAR/VECM time series models, deposit beta and behavioral analytics, NII/NIR/NIE component modeling, XGBoost with SHAP interpretability, and SR 11-7 model governance. Designed for quantitative analysts, risk managers, and financial modelers at banks subject to regulatory stress testing.

  • Level: advanced
  • Duration: 3 months
  • 12 sections
  • Price: $99.99

Topics: PPNR, CCAR, DFAST, stress testing, Net Interest Income, NIM compression, deposit beta, ARDL, VAR, VECM, error correction model, deposit elasticity, XGBoost, SHAP, SR 11-7, asset liability management, structural model, reduced-form model, Lucas critique, model identification, non-interest income, macroeconomic scenarios, bank capital planning, model governance

What's inside

  1. Advanced PPNR Modeling
  2. Chapter 1: Foundations of PPNR and the Regulatory Landscape
  3. Chapter 2: Balance Sheet Architecture and Rate Sensitivity Classification
  4. Chapter 3: Macroeconomic Scenario Construction and Variable Mapping
  5. Chapter 4: Structural vs. Reduced-Form Models — Foundations and Trade-offs
  6. Chapter 5: Econometric Foundations — OLS, Robust Regression, and ARDL Models
  7. Chapter 6: Advanced Time Series — VAR, Impulse Responses, and Error Correction Models
  8. Chapter 7: Deposit Beta Modeling and Behavioral Analytics
  9. Chapter 8: Net Interest Income (NII) Modeling Under Stress
  10. Chapter 9: Non-Interest Income (NIR) and Non-Interest Expense (NIE) Modeling
  11. Chapter 10: Machine Learning Applications in PPNR — XGBoost, Elastic Net, and Interpretability
  12. Chapter 11: Model Governance, Backtesting, and Capstone PPNR Integration

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