Empirical Finance

Information about Impact of Corona Epidemic

We will not teach this course in the summer term 2020. However, you can still register for the examination. Please visit the course website on StudOn for further information.


This is a course for advanced undergraduate (Bachelor) students. It deals with important empirical questions in finance. Issues covered are the empirical properties of high-frequency financial market data, the predictability of returns, estimation of the  Capital Asset Pricing Model (CAPM), the modeling of time-varying volatility (ARCH and GARCH models), the concept of Value-at-Risk and basic methods for option pricing. All topics are taught in an applied way that involves the implementation of the discussed methods in R.

At the end of the course, students are able to discuss properties (“stylized facts”) of high-frequency financial market data and can apply modern approaches to return and volatility modeling to financial time series. They know how to implement and evaluate econometric models for financial data using R. They will also be able to replicate and validate findings from state-of-the-art empirical finance research.


The course consists of a lecture (3 SWS) and exercise sessions (1 SWS). The latter focus mainly on implementation of methods in R. Both lecture and exercise session are organized by Dr. Alexander Glas.

The course is taught regularly in the summer semester. The course language is English.

The first lecture of the summer semester 2019 takes place on April 23, 2019 at 13.15h in room 4.109.

The course is worth 5 ECTS which can be earned by passing a written exam (90 minutes).


  • Campbell, J. Y., A. W. Lo, and A. C. MacKinlay (1997). The Econometrics of Financial Markets. Princeton University Press.
  • Christoffersen, P. F. (2012). Elements of Financial Risk Management. Academic Press.
  • Tsay, R. S. (2010). Analysis of Financial Time Series. Wiley Series in Probability and Statistics.
  • Additional references will be provided in class.


More information about dates, grading, the software that is used, and the course in general can be found in the syllabus.