Seminar Quantitative Risk Management

Seminar "Quantitative Risk Management"

Veranstaltung für den Master (5, 6 oder 7 Credit Points - T, G oder E-Modul)

Attention!

Introductory lectures on the suggested topics are planned. Here, we will present you a short overview and basic aspects of every topic. Moreover, other important information concerning the exam and presentations will be mentioned on the introductory lectures. Everyone is encouraged to attend!

The date of the binding registration is moved by one week, i.e. on 27th of April.

Please note, the times of the introductory lectures on 19th and 26th of April are changed.

For further information or if you have any questions please contact ONLY parolya@europa-uni.de.

5 ECTS --> seminar paper and presentation

7 ECTS --> seminar paper, prensentation, and oral exam

April 12  Fr 13:00 - 15:00 HG 217 -->  first meeting and introductory lecture

April 19  Fr 12:30 - 14:30 GD 202 -->  second introductory lecture

April 26 Fr 12:30 - 14:30 GD 202 --> third introductory lecture

April 27 --> binding registration (verbindliche Anmeldung) ---> parolya@europa-uni.de

June 25  --> deadline for seminar papers

June 25 --> oral examination

July 01 --> presentations

The course materials including the tutorials in R and SAS are available in moodle (see, below details). The key for moodle will be announced on the introductory lecture or per email upon request of the already registered students.

Details

Contents:

The Concise Oxford English Dictionary defines risk as ’hazard, a chance of bad consequences, loss or exposure to mischance’. In many cases only the downside of risk is mentioned, rarely a possible upside, i.e. the potential for a gain. In recent decades the field of financial risk management has undergone explosive developments. This seminar is devoted specifically to quantitative modeling issues arising in this field.

It is possible to write your seminar paper in English or in German. Moreover, all participants have to present their seminar paper in English. The presentations should take about 25 minutes. In this case you receive 5 ECTS. Additionally, you have to pass an oral examination in order to receive 7 ECTS. Relevant topics will be announced later. The seminar paper should consist of at least 15 pages without cover sheet and appendix.

Choose one of the following topics or, alternatively, you may propose an own topic.

Some topics have an outline which contains different subtopics. Therefore, it is possible for students to choose the same topic but the different subtopic.

!Please note that in order to pass the oral exam you must choose at least 3 topics given below and obey a basic knowledge on the chosen subject!

The theoretical material for your individual preparation can be the introductory lectures and/or the books Tsay (2005) and Embrechts, Frey and McNeil (2006) (see, reference list below).

Topics

1. Different Approaches to Risk Measurement

- Loss Distributions

- VaR (reserved)

- Expected Shortfall (reserved)

- Other risk measures

2. Multivariate Risk Models and their Applications

- Multivariate Normal Distribution

- Spherical and Elliptical Distributions

- Mixtures of Multivariate Distributions

3. Copula and Dependence Modelling

- Dependence Measures

- Basic Properties of Copulas

- Main Types of Copulas

- Archimedean Copulas

4. Regression Analysis of Factor Models

- Single Factor Model (CAPM) (reserved)

- Fama-French Approach

- Multi-Factor Models

5. Basics of Principal Components Analysis

6. GARCH Models for Changing Volatility

- ARCH processes

- GARCH processes

- Simple extensions of GARCH (reserved)

7. Multivariate ARMA processes with Applications

8. Multivariate GARCH processes

- Models for Constant Conditional Correlation (reserved)

- Models for Dynamic Conditional Correlation

9. Credit risk models

- the Merton Model

- CreditMetrics (reserved)

- the KMV Model

• Abdi. H., & Williams, L.J. (2010). "Principal component analysis.". Wiley Interdisciplinary Reviews: Computational Statistics, 2: 433–459.-->5.
• Bauwens, L., Laurent, S. and Rombouts, J. V. K. (2006). Multivariate GARCH models: a survey, Journal of Applied Econometrics 21: 79–109. --> 8.
• Bhatia, M., Finger, C. and Gupton, G. (1997). CreditMetrics, Technical document, J.P.Morgan/Reuters. --> 9.
• Bluhm, Christian, Ludger Overbeck, and Christoph Wagner (2002). An Introduction to Credit Risk Modeling. Chapman & Hall/CRC. ISBN 978-1-58488-326-5.-->9.
• Brockwell, P. and Davis, R. A. (1991). Time series: theory and methods, Springer, New York. --> 6, 7, 8.
• Brockwell, P. and Davis, R. A. (1996). Introduction to time series and forecasting, Springer, New York. --> 6, 7, 8.
• Copeland, T. E., Shastri, K. and Weston, J. F. (2005). Financial theory and corporate policy, Pearson Addison-Wesley. --> 4.
• Embrechts, P., Frey, R. and McNeil, A. J. (2006). Quantitative risk management: concepts, techniques, tools. Princeton University Press, Princeton. --> 1-12.
• Holton, G. (2003). Value-at-risk, Academic Press, Amsterdam. --> 1.
• Hull J., Nelken I., and A. White (2004), Merton's Model, Credit Risk and Volatility Skews, Journal of Credit Risk, Vol. 1, No. 1, pp. 3-28. -->9.
• Kotz S., Balakrishnan N., and N. L. Johnson, (2000), Continuous Multivariate Distributions, Volume 1, Models and Applications. Wiley.-->2.
• Nelsen R. B., (1999), "An Introduction to Copulas", Springer.-->3.
• Reinsel, G. (1997). Elements of multivariate time series analysis, 2 edn, Springer, Berlin, Heidelberg, New York. --> 8.
• Ruppert, D., (2004), Statistics in Finance, Springer: New York.---> 1, 4, 6
• Tsay, R. (2005). Analysis of financial time series, 2 edn, Wiley, New Jersey. --> 4, 5, 6, 7, 8.