Seminar: Quantitative Risk Management (T-Module)
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
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.
Registration in Moodle Viadrina required.