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Modeling and statistical analysis of extremes in time series
Provider: Faculty of Science

Activity no.: 5611-23-07-32
Enrollment deadline: 15/09/2023
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time16.10.2023, at: 09:00 - 20.10.2023, at: 16:00
Regular seats50
ECTS credits2.00
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserThomas Valentin Mikosch    E-mail address: mikosch@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Course workload
Course workload categoryHours
Course hours45.00
Sum45.00
Content
The understanding of the appearance of extremes in real-life time series (such as weather and climate observations, returns of stock prices, exchange rates, and stock indices, insurance claim data, failures in energy and social networks) requires suitable probabilistic models and their statistical analyses. Over the last 15-20 years such models and statistical tools have been developed under the assumption of serial dependence. They supplement classical extreme value analysis which deals with independent data.

Learning outcome
The goals of the course are
(1) to introduce and discuss the recent developments of extreme value theory in the time series context. The main focus will be on heavy-tail phenomena, where extremes are particularly severe, and cluster ing effects when extremes appear in clumps,
(2) to provide suitable statistical tools for analyzing the aforementioned phenomena,
(3) to provide relevant knowledge to graduate students about extreme behavior of random systems in contrast to their average behavior,
(4) to learn about applications of extreme value theory from top experts in the field.

Target group
The course aims at PhD and advanced Master students in statistics, probability theory, econometrics, or with a background in the aforementioned areas such as physics, geosciences.

Lecturers
The main lecturers of this PhD course Thomas Mikosch (University of Copenhagen) and Olivier Wintenberger (Sorbonne University and Pauli-Institut Wien) will base their lectures on the manuscript of their monograph Extremes for Time Series.

In addition to their own lectures (4 hours per day) international top experts on applications of extreme value theory/statistics have agreed to give lectures.
• Daniela Castro-Camilo (Glasgow University). She is an expert on Bayesian statistics applied to extreme values theory and environmental applications.
• Valerie Chavez-Desmoulins (HEC Lausanne). She is an expert on risk-measures and econometrics.
• Philippe Naveau (Paris Saclay). He is an expert on extremes in climate research.
• Kirstin Strokorb (Cardiff University). She is an expert on spatio-temporal modeling of extremes.
• Chen Zhou (Erasmus University). He is an expert on statistics for extremes and bootstrap, and applications in economics.

Remarks
Please sign up here: https://sites.google.com/view/extreme2023

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