Module Title: Credit Risk

Module title: Credit Risk

Module convenor: Dr Simone Varotto

Aims:

This course introduces students to a set of newly developed techniques to measure and manage credit risk in bank portfolios. In recent years financial institutions have been looking at ways to quantify risk in their corporate loan and mortgage books. The lack of market prices for these types of illiquid assets implies that standard risk assessment procedures can not be employed. The course focuses on (1) an analysis of the causes of 2007-2010 financial crisis and their relationship with retail, corporate and sovereign credit risk (1) default and recovery risk, (2) credit ratings and credit scoring models (3) how to measure portfolio credit risk using contingent claim and credit rating based approaches (4) credit risk management tools and (5) credit risk capital regulation (Basel 2 and Basel 3).

Intended learning outcomes:

Assessable outcomes

By the end of the module it is expected that students will:

·  Be familiar with the events that led to the 2007-2010 financial crisis and their implications for credit risk management

·  Understand the relationship between capital and risk;

·  Be familiar with the latest credit risk capital regulation;

·  Be able to apply Value-at-Risk techniques to portfolios of credit risk sensitive instruments;

·  Be able to derive and use credit ratings and credit scores;

·  Know how to estimate a credit loss distribution and use it for risk management purposes;

·  Understand the main features and implementation of the following models:

o  JP Morgan’s CreditMetrics

o  Moody’s-KMV model

·  Be able to use risk management tools such as Component VaR and Best Hedge calculated with and without distributional assumptions.

Outline content:

1. Credit risks and the 2007-2010 Financial Crisis

2. Economic and Regulatory capital (Basel 2 and Basel 3)

3. Credit scoring models: Altman Z-score and refinements

4. Credit rating issues: designing and implementing effective internal credit rating systems.

5. Credit Loss Distribution: Expected and Unexpected Loss

6. A Rating-based Credit Risk Model: CreditMetrics

7. An Equity-based Credit Risk Model: KMV

8. Credit Risk Management Tools

Brief description of teaching and learning methods:

The core theory and concepts will be presented during lectures. Problem sets will be solved in workshops.

Assessment:

Coursework

1) One Multiple choice test (50% each).

2) Group Project (50%): Students will be asked to work in teams and use a selection of models to measure the risk of a bank’s loan portfolio. Input data to the model will have to be collected electronically through Reuters, Bloomberg or DataStream terminals. Each team will do the analysis in Excel, summarise the results in a report and deliver a Power-Point presentation.

Relative percentage of coursework/test : 100%

Requirements for a pass

50% overall grade

Reassessment arrangements

By individual project.