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74622-01 - Seminar: The Economy of Risk in Insurance and the Optimization of Reinsurance Programs (3 CP)
| Semester | spring semester 2025 |
| Course frequency | Once only |
| Lecturers |
Michel Dacorogna (michel.dacorogna@unibas.ch, Assessor)
Thom van Rijn (t.vanrijn@stud.unibas.ch) |
| Content | This course covers the key theoretical concepts and modeling techniques in Quantitative Risk Management (QRM) that underpin the modern optimization of reinsurance programs. The aim is for students to acquire practical tools to address real-world challenges, particularly in designing economically efficient reinsurance structures. While we focus on risk management within finance and insurance, these principles also apply broadly across other industry sectors. Main concepts include loss distributions, risk measures, interdependence, and concentration of (extreme) risks, techniques derived from probabilistic modelling and statistical analysis, copula and extreme value theory. We also discuss corporate finance concepts like economic valuation of liabilities, capital, capital allocation and structure of capital to reduce the cost-of-capital. Based on these concepts, we develop an economic valuation of reinsurance cover that will be the basis for optimization of reinsurance programs. |
| Learning objectives | Through examples and case studies from the practice, we explain how sophisticated mathematical methods can be integrated in the efficient management of an insurance portfolio of risk and its hedging through reinsurance covers. At the end of the course, students should be able to understand how a modern financial institution manages its risks and structures its reinsurance covers. |
| Bibliography | The following two papers are directly related to the method of optimizing reinsurance that will be presented in the course: - How Much Reinsurance Do You Really Need? A Case Study, by Peter Boller, Michel Dacorogna and Hubert Niggli, available on: https://ideas.repec.org/p/wpa/wuwpri/0306001.html, 2002. - Sharing Risk – An Economic Perspective, by Andreas Kull, in: ASTIN Bulletin Vol. 39 (2), pages 591-613, 2009. Further supporting literature will be provided throughout the lecture. |
| Comments | Most of the course will be lectures in front of students, but we will provide some exercises to deepen the understanding and discuss case studies coming from practice. Participating in the exercises is optional, but students who complete all exercises will receive an additional half-point on their exam. They will also receive the solution to the exercises. Thom van Rijn will assist with the exercises. |
| Weblink | https://adam.unibas.ch |
| Admission requirements | Introductory courses in probability and in statistics. Students are expected to be fluent in statistical programming languages either R or Python. |
| Language of instruction | English |
| Use of digital media | Online, mandatory |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| einmalig | See individual dates | ||
| unregelmässig | See individual dates | ||
Dates
| Date | Time | Room |
|---|---|---|
| Friday 21.03.2025 | 14.15-18.00 | Kollegienhaus, Hörsaal 119 |
| Friday 28.03.2025 | 14.15-18.00 | Kollegienhaus, Hörsaal 119 |
| Friday 04.04.2025 | 14.15-18.00 | Kollegienhaus, Hörsaal 119 |
| Friday 11.04.2025 | 14.15-16.00 | Kollegienhaus, Hörsaal 119 |
| Monday 19.05.2025 | 14.15-16.00 | Kollegienhaus, Seminarraum 103 |
| Modules |
Module: Insurance of Persons (Master's Studies: Actuarial Science) Module: Non-Life Insurance (Master's Studies: Actuarial Science) Module: Risk Analysis (Master's Studies: Actuarial Science) |
| Assessment format | continuous assessment |
| Assessment details | The assessment will be done through a research project with a written report. |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | no repetition |
| Responsible faculty | University of Basel |
| Offered by | Fachbereich Mathematik |