98773 - ADVANCED METHODS FOR RISK MANAGEMENT

Learning outcomes

At the end of the course the student is familiar with the main principles and tools of market risk analysis and the hedging techniques. He knows the general theory of risk measures and the principles of market risk regulation. He is able to design a process of market risk measurement and reporting, and to make market risk management decisions.

Course contents

1. Market risk and the definitions of "price", "risk factor" and "sensitivity"

2. Risk factors and risk mapping for linear, non linear and structured products.

3. Spread risk single name (CSR risk): bond and CDS spreads

4. Credit risk models: structural and intensity based models

5. Correlation risk and copula functions

5. Spread risk multi name: credit risk portfolios and securitizations

6. Counter party risk and credit valuation adjustments

7. Counterparty risk mitigation and funding valuations adjustments

8. Risk measures: VaR and ES in the axiomatic approach

9. Market liquidity risk and accounting: valuation risk

10. Funding liquidity risk, IRBB and non maturing deposits management.

Readings/Bibliography

1. C. Acerbi, Coherent Representations of Subjective Risk Aversion, ch. 10 in G. Szego (ed), Risk Measures for the 21th Century, Wiley Finance Series, 2004
2. M. Bianchetti and U. Cherubini, Prudent Valuation Guidelines and Sound Practices, https://ssrn.com/abstract=2790629 , 2016
3. U. Cherubini and G. Della Lunga, Structured Finance: The Objected Oriented Approach, Wiley Finance, Chichester, 2007
4. J. Mina and J. Y. Xiao, Return to RiskMetrics: The Evolution of the Standard,RiskMetrics, New York, 2001
5. JP Morgan, RiskMetrics™ – Technical Document, Fourth Edition, New York, 1996

Additional reading will be provided during the course

Teaching methods

Classroom lectures

Assessment methods

The exam will be based on:

1. a term paper
2. an oral examination in which the student will discuss the term paper or portfolio and then will answer questions about the subjects covered in the whole program.

The term paper will account for up to 5 points in the final grade.

The term paper should consist of

1. an introduction to the problem or topic chosen
2. a review of the literature on the subject
3. a mathematical treatment of the problem
4. an illustrative example with data, either real or simulated

The maximum possible score is 30 cum laude.

The grades are described as follows

< 18 failed

18-23 sufficient

24-27 good

28-30 very good

30 cum laude Excellent

 

Teaching tools

Portfolio case study. Computer exercises.

Office hours

See the website of Umberto Cherubini