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International Business Administration

Quantitative Risk Management

Exam number: 6401

Semester: from 1st semester

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Each summer semester

Prerequisites: None

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Wolfgang Schmid

Name of the professor: Prof. Dr. Wolfgang Schmid

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 45 h; self-study: 135 h

Contact hours (per week in semester): 2

Methods and duration of examination:
Successful preparation of a term paper as well as presentation of the results of work

Emphasis of the grade for the final grade: Please check regulations of the study programme

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:
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 the seminar paper in English or in German. Moreover, all participants have to present their seminar paper in English. Each student has to apply theoretical aspects to financial data, i.e the participants must use statistical software packages. We offer introductory problem sets that help to work with the software packages R and SAS. You are allowed to use R and SAS in order to apply statistical methods to real data.

Teaching and learning methods:

Literature (compulsory reading, recommended literature):
Embrechts, P., Frey, R. and McNeil, A. J. (2006). Quantitative risk management: concepts, techniques, tools. Princeton University Press, Princeton.
Ruppert, D., (2004), Statistics in Finance, Springer: New York.
Tsay, R. (2005). Analysis of financial time series, 2 edn, Wiley, New Jersey.

Further information:
Registration in Moodle Viadrina required.