Teaching

I teach several courses in the field of insurance and econometrics. For these courses a solid background in probability theory is a very imporant prerequisite for students. I therefore put a lot of emphasis on proper use of probability theory, including decent notation.

In all my courses empirical work plays an important role. To fully understand quantitative techniques it is crucial for students to apply these methods to data. Therefore, my students have to do weekly exercises and assignments, on which I provide them feedback. A great advantage of this approach is that it forces students to study the course material on a regular basis. 

Often statistical software is needed to do the empirical work related to my courses. We always use R for this purpose. R has several advantages. It is shareware, so students can use it for free. There are many useful libraries available that students can use. Moreover, the libraries are generally well documented.

The courses I teach are:

• Introduction to Actuarial Science
  Eight-week course, covering the basics of life and risk insurance. We use the book "Actuarial Mathematics" (second edition) by Bowers et al. (1997).
• Applied Statistics for Econometrics
  A one-semester course about survival analysis, with applications in economics and insurance.
• Risk Insurance
  An eight-week course about risk insurance, based on the book "Modern Actuarial Risk Theory Using R" by Kaas et al. (2008).

Students can find more detailed information on  Nestor.