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This entry is from Winter semester 2020/21 and might be obsolete. You can find a current equivalent here.

Quantitative Risk Management
(dt. Quantitatives Risikomanagement)

Level, degree of commitment Specialization module, depends on importing study program
Forms of teaching and learning,
workload
Lecture (3 SWS), recitation class (1 SWS) or lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements
6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises.
Examination type: Written or oral examination
Language,
Grading
German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Business Mathematics.
Subject, Origin Mathematics, M.Sc. Business Mathematics, M.Sc. Business Mathematics, M.Sc. Business Mathematics
Duration,
frequency
One semester,
Regularly alternating with other specialization modules
Person in charge of the module's outline Prof. Dr. Hajo Holzmann

Contents

The basic concepts and models of risk management are discussed, in particular

  • Risk factors, conditional/unconditional loss distributions, risk measures
  • risk aggregation, coherent risk measures, bounds on the aggregated risk
  • Market risk, estimation of risk measures, backtesting
  • Credit risk, Merton model, credit rating and migration, factor models and other statistical models.

Data examples and their analysis with R are treated as illustrations.


Qualification Goals

The students shall

  • learn basic concepts of quantitative risk management, in particular for the financial industry,
  • learn methods for estimating market risk and credit risk,
  • be able to implement them with suitable software,
  • improve their oral communication skills in the recitation class by practicing free speech in front of an audience and during discussion.

Prerequisites

None. The competences taught in the following modules are recommended: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis, Elementary Stochastics, Financial Mathematics I, Probability Theory, Internship Stochastics.


Recommended Reading

  • McNeil, A., Frey, R. und Embrechts, P. (2005), Quantitative Risk Management. Princeton Series in Finance.
  • Bluhm, C., Overbeck, L., Wagner, C. (2002), Introduction to Credit Risk Modelling. CRC Press/Chapman Hall.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2020/21. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.