Please note that it is not clear whether this course will be offered from summer 2024 onwards. Winter term 2023/24 might be the last chance to decide to take the exam for this course.
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) and the modeling of time-varying volatility (ARCH and GARCH models). 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 two weekly meetings (4 SWS). Tutorials sessions focus mainly on implementation of methods in R. Lectures and exercise sessions 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 2023 takes place on April 18, 2023 at 13.15h in LG 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.
- Cochrane, J. H. (2005). Asset Pricing: Revised Edition. Princeton University Press.
- Tsay, R. S. (2010). Analysis of Financial Time Series. Wiley Series in Probability and Statistics.
- Additional references will be provided in class.