Introduction
Please note that this is a preliminary course description. The final version will be published in June 2026.
This course is of great importance for your master thesis for three reasons. First, it introduces you to econometric concepts that are used in empirical finance. As such, it helps you to understand the methodology employed in published articles. Second, this course equips you with the skills to test empirical predictions based on theories from finance or economics. Third, the library session familiarizes you with information search strategies.
The course kicks off with a brief revision of regression analysis and diagnostic tests, before delving into panel regressions. Subsequently, we shift our focus to univariate and multivariate time series models. In the section about cointegration, we explore unit roots, stationarity tests, and error correction models. Lastly, GARCH models are employed to capture volatility clustering.
For every topic, there will be R codes showcasing the practical implementation of each econometric technique or concept. Usually, each R code is accompanied by a video that walks you line-by-line through the code. In the context of the mid-term exam, you need to demonstrate your coding skills by applying econometric techniques to real-world data.