CFRM 547 Credit Risk Management

This course is an introduction to the mathematical, statistical and financial foundations of models for analyzing, predicting, and mitigating credit risks. Students will learn the theoretical basis for widely-used modeling methods for credit risk assessment and implement those methods through programming assignments using R. The course will focus on both obligor-level and portfolio-level credit risks, as well as valuation and risk analysis of assets and derivatives with credit risk. Topics include:

  • Credit risk drivers and portfolio diversification (idiosyncratic and systemic risks)
  • Applied logistic regression (credit scoring models)
  • Credit rating products for individuals and corporations (FICO, S&P, Moodys, Experian)
  • Merton model for default risk
  • Credit risk economic capital
  • Basel II credit capital framework for banks
  • Modeling loss frequency (PD) and severity (LGD)
  • Credit risks in structured asset backed securities
  • Credit default swaps, models for valuation and risk measurement
Instructor: 
Jay Henniger
Textbooks: 
Servigny and Renault (2004). Measuring and Managing Credit Risk, McGraw-Hill Professional
Software: 
R and R Finance Packages
Prerequisites: 
CFRM 541 and CFRM 546 or equivalents, or by permission
Credits: 
4