Informations about the modules
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Module (6 Credits)
Statistical Modeling of Extremes
- Name in diploma supplement
- Statistical Modeling of Extremes
- Responsible
- Admission criteria
- See exam regulations.
- Workload
- 180 hours of student workload, in detail:
- Attendance: 60 hours
- Preparation, follow up: 60 hours
- Exam preparation: 60 hours
- Duration
- The module takes 1 semester(s).
- Qualification Targets
Students
- acquire comprehensive knowledge of modern statistical and econometric tools to tackle issues related to extreme events
- are capable of applying these to address empirical issues in fields ranging from economics and finance to areas like hydrology and finance
- identify suitable data to do so and
- know how to translate an empirical problem into a statistical model
- critically assess their findings
- are proficient in assessing the formal properties of key techniques and are able to demonstrate these formally
- independently and competently use and develop statistical routines and code to practically apply these
- independently address relevant exercises
- Relevance
The practical relevance of the module is high in view of the key and increasing importance of empirical work in economics and elsewhere.
- Module Exam
Examination for this module takes place through a written exam (typically 60-90 minutes), or an oral exam (typically 20-40 minutes), or an empirical project (70% of the final grade) combined with a presentation (typically 20 minutes, 30% of the final grade). The type of examination will be communicated at the start of the semester.
- Usage in different degree programs
- Elements
Lecture (3 Credits)
Statistical Modeling of Extremes
- Name in diploma supplement
- Statistical Modeling of Extremes
- Organisational Unit
- Lecturers
- SPW
- 2
- Language
- English
- Cycle
- irregular
- Participants at most
- no limit
- Preliminary knowledge
Knowledge of basic econometric concepts such as communicated in our bachelor and master courses “Einführung in die Ökonometrie" and “Methoden der Ökonometrie“ as well as good working knowledge of mathematical statistics.
- Contents
- Models for maxima
- Peaks over threshold
- Extremes of dependent sequences
- Extremes of non-stationary sequences
- Multivariate extremes
- Literature
- Hayashi, F. (2000). Econometrics. Princeton: Princeton Univ. Press.
- Gumbel (1958) Statistics of Extremes, Columbia University Press
- Coles (2001) An Introduction to Statistical Modeling of Extreme Values, Springer
- Beirlant, Goegebeur, Segers and Teugels (2004) Statistics of Extremes: Theory and Applications, Wiley
- Finkenstädt and Rootzén (2004) Extreme Values in Finance, Telecommunications and the Environment, CRC
- de Haan and Ferreira (2006) Extreme Value Theory: An Introduction, Springer
- Reiss and Thomas (2007) Statistical Analysis of Extreme Values with Applications to Insurance, Finance, Hydrology and Other Fields, Birkhäuser
- Teaching concept
Classes are organized around traditional lectures. Students are however expected to contribute intensively through active discussion. Lectures are complemeted via, e.g., illustrations in R, joint interactive programming to better understand the statistical concepts as well as comprehensive problem sets to deepen students’ proficiency.
- Participants
Exercise (3 Credits)
Statistical Modeling of Extremes
- Name in diploma supplement
- Statistical Modeling of Extremes
- Organisational Unit
- Lecturers
- SPW
- 2
- Language
- English
- Cycle
- irregular
- Participants at most
- no limit
- Preliminary knowledge
see lecture
- Abstract
see lecture
- Contents
see lecture
- Literature
see lecture
- Participants