Description:

This course provides an advanced treatment of econometric methods used in financial economics. It
combines asset pricing theory with modern econometric techniques to analyze financial market data. Students will learn how to translate asset pricing theory into testable econometric models and implement
them using financial data.

Outline:

• The stochastic discount factor framework
• Generalized Method of Moments (GMM)
• Factor pricing models
• Time-varying risk premia
• Predictability of returns
• Volatility modeling

Literature:

• Linton (2019) Financial Econometrics: Models and Methods. Cambridge University Press, 1st ed.
• Cochrane (2005) Asset Pricing: Revised Edition. Princeton University Press, revised ed.
• Newey and McFadden (1994) Large Sample Estimation and Hypothesis Testing. In Engle, R. F. and
• McFadden, D., editors, Handbook of Econometrics, volume 4, chapter 36, pages 2111–2245

Methods of Assessment:

The exam takes place during the regular exam period. It covers both the theoretical and practical content of the course, including programming and interpreting the results obtained in R. You may bring a single-sided, handwritten DIN A4 sheet of paper with information of your choice into the exam. Furthermore, you can earn bonus points in the classroom exercises, for example in the form of presentations.

Formalities:

The course builds directly on basic knowledge of (univariate) time series analysis as acquired, e.g., in
a master’s level course on time series analysis. To begin with, we will briefly review some fundamental
concepts from probability theory.

We would also like to draw your attention to the R
Propädeutikum, which is offered by Prof. Behr this year and will take place in the first week of the semester
instead of the usual exercise session. For more information, please visit https://stat.wiwi.uni-due.de under Studium & Lehre or the Moodle page for the course.