## Measurement of Life Risk

Modelling of future life time on historical data: approaches that assume a) constant mortality rates, b) mortality rates that change deterministically, c) mortality rates that change stochastically over time; Simulation of the future life time on the basis of the above models; Financial products that contain biometric risks: life insurance, pension funds; Pricing rules for life insurance contracts; Modelling loss distributions and estimating VaR for the above products and for portfolios of products; Combining interest rate and biometric risk and simulating the joint loss distribution of insurance products and portfolios; Back testing and stress testing

### Art der Vermittlung

Präsenzveranstaltung

Pflichtfach

### Empfohlene Fachliteratur

Dickson, D., Hardy, M., Waters, 2012, H., Actuarial Mathematics for Life Contingent Risks, Cambridge University Press; Promislow, S., 2011, Fundamentals of Actuarial Mathematics, Wiley; Seog, S., 2010, The Economics of Risk and Insurance, Wiley-Blackwell; Gerber, H., 2010, Life Insurance Mathematics, Springer

integrated class

### Prüfungsmethode

Students are assessed on the quality of their assignments, their presentations, their participation and the results of the written quizzes.

Courses 1 - 6

### Schnellinfos

#### Studiengang

Quantitative Asset and Risk Management (Master)

Master

3.00

Englisch

Berufsbegleitend

2023

2 SS

Ja

#### Lernergebnisse der Lehrveranstaltung

After the successful completion of the course, students are able to master the various computational approaches to estimating mortality rates. This allows them to derive the distribution of the future life time of persons which is a major risk driver for life insurance risk. They understand how products that contain biometric risk (e.g. life insurance contracts) function, and they can price these products. Using their (pre-existing) knowledge of interest rate risk, students are able to estimate the loss distribution for a portfolio of insurance contracts. This understanding allows them to estimate risk measures such as the Value at Risk. Additionally, they are able to test the quality of already implemented risk measurement models (back-testing) and they can conduct stress tests that analyse the impact of scarce extreme events. This detailed knowledge of life risk measurement is essential for managing life risk.

#### Kennzahl der Lehrveranstaltung

0613-09-01-BB-EN-12