Required in stage
Second term
Both terms
Not organised
This year
Next year
Alternating years
External
Prerequisites
Identical coursesStatistical Tools for Quantitative Risk Management (B-KUL-G0Q24A)
Cannot be taken as part of an examination contract
N. | Smits Bert (substitute) Aims
The objectives of this course are to study some selected topics from finance and insurance that cover a variety of (advanced) statistical techniques.
Upon completion of this course the student
- understands the definitions, the theoretical properties and the proofs that were given for the studied methodologies
- is able to give a proof or a counterexample for a newly stated (similar) hypothesis
- is able to apply the definitions and properties of the studied methodologies in practical situations (exercises, examples) and to draw conclusions about the obtained results
- is able to understand and to interpet R code and output and to draw the correct conclusions
- is able to understand a scientific article (or chapter from a scientific book) and to explain the most important results (in group); is able to implement and illustrate part of the studied methodology and/or application in the article with R (in group).
Previous knowledge
The prerequisites are basic calculus, basic concepts of probability and statistics, matrices and linear algebra.
Is included in these courses of study
- Doctoral Programme in Business Economics (Leuven)
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Business) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Theoretical Statistics and Data Science) 120 ects.
- Master in de wiskunde (Leuven) 120 ects.
- Master of Mathematics (Leuven) 120 ects.
- Master of Actuarial and Financial Engineering (Leuven) 120 ects.
- Master in de actuariële en financiële wetenschappen (Leuven) 120 ects.
Activities
6 ects. Statistical Tools for Quantitative Risk Management (B-KUL-G0Q24a)
EnglishFormat: Lecture
39 
First termN. | Smits Bert (substitute) Content
The following topics will be studied
- Multivariate Statistical Methods and Exploratory Data Analysis
- Returns and Portfolio Selection
- Copulas
- Extreme Value Analysis
- Time Series Models
Course material
Used course material consists of slides (available on Toledo)
Background information (recommended reading) can be found in several chapters of the following books
- D. Ruppert (2011). Statistics and Data Analysis for Financial Engineering. Springer Texts in Statistics.
- R.S. Tsay (2002) Analysis of Financial Time Series.Wiley series in Probability and Statistics.
- J. Beirlant, Y. Goegebeur, J. Segers and J. Teugels (2003) Extreme Value modelling. Wiley series in Probability and Statistics.
and in some scientific articles (also available on Toledo).
Format: more information
Formal lectures with interaction and discussions. (teaching conversation).
Teaching will be done by giving spoken explanations of the subject that is to be learned (accompanied by visual aids) and/or through examples or applications. The students will have to solve exercises (individually and in group) during the lectures, often with aid of statistical software. The students (divided in groups) will also teach to each other (one hour presentation) and will evaluate each other’s work.
Evaluation
Evaluation: Statistical Tools for Quantitative Risk Management (B-KUL-G2Q24a)
Explanation
Features of the evaluation
*The evalution consists of a single final exam
* The final exam is a written exam. During the exam a summary of the course notes (this summary can be downloaded from Toledo) can be consulted. It is not allowed to make notes on the material that can be used during the exam.
Determination of final grades
*The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a whole number on a scale of 20.