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Statistics in Finance III - Selected Topics *

Name of module: Statistics in Finance III - Selected Topics *

Exam number: 6402

Semester/Trimester: Semester

Duration of the module: Ein Semester

Form of the module (i.e. obligatory, elective course): Wahlpflicht

Frequency of module offer: Each summer semester

Prerequisites: Kenntnisse in Mathematik und Statistik.

Applicability of module for other modules and study programmes:
Verwendbar als G-Modul. Serviceveranstaltung für Masterstudierende der Kultur- bzw. Rechtswissenschaften.

Person responsible for module: Prof. Dr. Wolfgang Schmid

Name of the professor: Prof. Dr. Wolfgang Schmid

Language of teaching: Englisch

ECTS-Credits (based on the workload): 7 (T-Modul); 5 (G-Modul)

Workload and its composition (self-study, contact time):
T-Modul: Kontaktzeit (Vorlesung, Übung, Seminar etc.) 60 Std.; Selbststudium: 150 Std. / G-Modul: Kontaktzeit (Vorlesung, Übung, Seminar etc.) 37,5 Std.; Selbststudium: 112,5 Std.

Contact hours (per week in semester): 3+1

Methods and duration of examination:
Es kann ein Leistungsnachweis erworben werden. Voraussetzung hierfür ist
- beim T-Modul (7 ECTS-Credits) die erfolgreiche Anfertigung einer Projektarbeit,
- beim G-Modul (5 ECTS-Credits) die erfolgreiche Teilnahme an der Mündlichen Prüfung.

Emphasis of the grade for the final grade: 2/29 (T-Modul); 1/29 (G-Modul)

Aim of the module (expected learning outcomes and competencies to be acquired):
The students should get familiar with quantitative methods for measuring the risk of financial activities.

Contents of the module:
Summer semester 2009: Financial Risk Management
The Concise Oxford Englisch Dictionary defines risk as a „hazard, a chance of bad consequences, loss or exposure to mischance“. Mostly only the downside of a risk is mentioned, rarely a possible upside, i. e. the potential for a gain. In recent decades the field of risk management has undergone explosive developments. This lecture is devoted specifically to quantitative modelling issues arising in this field.
1. ARMA process: estimation and application to financial data. (The paper should also give an example of prediction in finance using ARMA processes, mention VARMA processes)
2. ARCH/GARCH process: motivation, modelling and estimation.
3. Volatility models and fundamentals of multivariate time series.
4. Copulas: properties and estimation of dependence measures.
5. Risk measures. (The paper should discuss suitable measurements of the risk)
6. Fitting the generalized extreme value distribution to financial data. (In the paper an overview about extreme value theory should be given)
7. Introduction to credit risk modelling.
8. The concepts of Value-at-Risk (In the paper the VaR should be introduced and it must be shown how the VaR can be determined)
9. Multivariate GARCH Processes.
10. Risk Measurement in Factor Models.
11. Forecasting High-Frequency Data.

Teaching and learning methods:

Literature (compulsory reading, recommended literature):
McNeil / Frey / Embrechts: Quantitative Risk Management, Princeton University Press, 2005.
Campbell / Lo / MacKinlay: The Econometrics of Financial Markets, Princeton University Press, 1997.

Further information:
Registration in Moodle required.
Chair's web page