# Coursebooks 2018-2019

## Risk, rare events and extremes

#### Lecturer(s) :

Davison Anthony C.

English

#### Remarque

Cous donné en alternance tous les deux ans (donné en 2018-19)

#### Summary

Modelling of rare events, such as stock market crashes, storms and catastrophic structural failures, is important. This course will describe the special models and methods that are relevant to such modelling, including the mathematical bases, statistical tools and applications.

#### Content

• Mathematical bases: behaviour of maxima and threshold exceedances in large samples, both for independent and dependent data. Poisson process modelling.
• Statistical methods: modelling using the GEV and GP distributions, for independent and dependent data. Likelihood and Bayesian inference. Non-stationarity. Extremal coefficients. Multivariate extreme-value distributions. Max-stable processes.
• Applications: Environmental, financial, and engineering applications. Use of R for extremal modelling.

#### Learning Prerequisites

##### Important concepts to start the course

Probability and statistics at the level of second-year bachelor (mathematics), plus further knowledge of statistics and stochastic processes.

#### Learning Outcomes

By the end of the course, the student must be able to:
• Recognize situations where statistical analysis of extrema is appropriate
• Manipulate mathematical objects related to the study of extrema
• Analyze empirical data on extremes using appropriate statistical methods
• Construct appropriate statistical models for extremal data
• Interpret such models in terms of underlying phenomena
• Infer properties of real systems in terms of probability models for extremes

#### Teaching methods

Lectures, theoretical and computational exercises in class and at home.

#### Assessment methods

Mini-project, final exam.

Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

#### Supervision

 Assistants Yes

#### Resources

##### Bibliography

Coles, S. G. (2001) An Introduction to the Statistical Modelling of Extreme Values. Springer.

Beirlant, J, Goegebeur. Y., Teugels. J. and Segers. J. (2004) Statistics of Extremes: Theory and Applications. Wiley.

### In the programs

• Data Science, 2018-2019, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Data Science, 2018-2019, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Financial engineering, 2018-2019, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Financial engineering, 2018-2019, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Applied Mathematics, 2018-2019, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Applied Mathematics, 2018-2019, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Mathematics - master program, 2018-2019, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Mathematics - master program, 2018-2019, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Mathematics for teaching, 2018-2019, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Mathematics for teaching, 2018-2019, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Data science minor, 2018-2019, Autumn semester
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Risk, rare events and extremes
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks

MoTuWeThFr
8-9GCB330
9-10
10-11GCB330
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
Lecture
Exercise, TP
Project, other

### legend

• Autumn semester
• Winter sessions
• Spring semester
• Summer sessions
• Lecture in French
• Lecture in English
• Lecture in German