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## Loss Models

• Teacher(s):
• Course given in: English
• ECTS Credits:
• Schedule: Spring Semester 2018-2019, 4.0h. course (weekly average)
WARNING :   this is an old version of the syllabus, old versions contain   OBSOLETE   data.
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### Objectives

The principal objective of this course is to provide a solid actuarial understanding of building, selecting and developing statistical models relevant for insurance business and related actuarial applications. This course aims at establishing a useful bridge between statistical and probabilistic models of insurance contracts and the raw, typically incomplete, insurance portfolio data available to actuaries. Accompanying exercises in R will help towards a better understanding of both insurance data and statistical models used by actuaries.

### Contents

• Introduction to Models, Data & Insurance Contracts
• Parametric Models
• Non-parametric Models
• Loss Data, Model Validation & Selection
• Extreme Value Statistics
• Generalised Linear Models

### References

• Loss Models. From Data to Decisions. Klugman, S.T., Panjer, H.H., and Willmot, G.E. 3rd Edition, Wiley, 2008.
• Statistical Theory. Seleznjev, O. Manuscript available in moodle.
• Generalized Linear Models for Insurance Data. Jong, P., Heller, G.Z. Cambridge University Press, Cambridge, 2008.
• Nonlife Actuarial Models, Theory, Methods and Evaluation. Tse, Y. Cambridge University Press, Cambridge, 2009.
• Regression Modeling with Actuarial and Financial Applications. Frees, E.W. Cambridge University Press, Cambridge, 2009.
• Statistical Analysis of Extreme Values: From Insurance, Finance, Hydrology and Other Fields. Reiss, R-D., Thomas, M. 3rd Edition, Birkhäuser, Basel, 2007.
• Modeling Extremal Events for Finance and Insurance. Embrechts, P., Klüpelberg, C., and Mikosch, T. Springer, 1997.
• Laws of Small Numbers: Extremes and Rare Events. Falk M., Hüsler, J., and Reiss R.-D. DMV Seminar 23, 3rd Edition, Birkhàuser, Basel, 2010.
• Non-Life Insurance Mathematics: An Introduction with Stochastic Processes. Mikosch, T. 2nd Edition, Springer, 2006.

### Pre-requisites

Basic in statistics & probability

### Evaluation

#### First attempt

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#### Retake

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