Quantitative Risk Management

lactu2210  2019-2020  Louvain-la-Neuve

Quantitative Risk Management
Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h
Q2
Teacher(s)
Hafner Christian;
Language
English
Prerequisites
Basic classes in statistics (e.g. INGE1214) and quantitative finance
Main themes
Analysis of various risks in financial and alternative markets
Aims

At the end of this learning unit, the student is able to :

1 Ability to evaluate and assess quantitative risks
 

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
This class introduces the student to the methodology used in
quantitative risk management. The topics cover basic concepts in risk management, risk measures, multivariate models, financial time series
and measures of dependence. It will be focused on the statistical
aspects and practical implementation of the discussed techniques.
Teaching methods
Several practical assignments, to be solved on the computer, will be
used to guideline the students throughout the class. The assignments
will be evaluated.
Evaluation methods
Assignments (20%) and oral exam (80%)
Bibliography
Les transparents se basent principalement sur
  • Franke, J., Haerdle, W. and Hafner, C. (2012) Statistics of Financial Markets, an Introduction, 3rd edition, New York: Springer.
  • McNeil, A.J., Frey, R. and Embrechts, P. (2005), Quantitative Risk Management: Concepts, Techniques, and Tools, Princeton UP Series in Finance.
Teaching materials
  • transparents sur moodle
Faculty or entity
LSBA


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Mathematics

Master [120] in Actuarial Science

Master [120] in Mathematical Engineering

Master [120] in Statistic: General