The topic of this course is the practical application of the statistics program “Stata” in Finance research. The course contains three major sections: How to use Stata, an introduction to the usage of the most common databases in Finance at this university, and an application example.
In the first section, we will introduce project and data management with Stata. In addition, we will teach estimation techniques and programming basics. In the second section, we will show where to get access to common datasets in Finance research. In the last section, students will have the chance to apply their knowledge to a practical example.
The course is offered shortly after the start of the seminar theses, that is, at the beginning of January in the fall semester (HWS) and at the beginning of July in the spring semester (FSS).
Lern- und Qualifikationsziele
The main aim of the course is to prepare students with practical methods for conducting empirical Finance research. Students learn how to load, manipulate, and evaluate data using Stata. Stata is the most popular statistics program used in the Finance research community. In addition, students learn where they can access popular databases used in Finance at the University of Mannheim. The main focus of the course lies on the practical application of the Stata software.
Due to a limited amount of seats in the computer lab, the number of participants will be limited. We will prefer students who are writing an empirical seminar thesis in the Finance Area in the semester when allocating spots.
|Vorlesung||1 SWS||5 SWS|
|Prüfungsform und -umfang||Take home exam (pass/|
|Informationen zur Anmeldung||Website of the Chair|
Prof. Dr. Erik Theissen
Dr. Stefan Scharnowski
|Dauer des Moduls||1 Semester|
|Verwendbarkeit||M.Sc. MMM, M.Sc. WiPäd, M.Sc. VWL, M.Sc. Wirt. Inf., M.Sc. Wirt. Math.|
|Programmspezifische Kompetenzziele||CG 1, CG 4|
|Literatur||The course is based on the provided lecture slides. The course requires the use of the statistical software Stata.|
|Gliederung||1. Introduction to Stata: Directories and folders, Stata extensions
2. Data Management: Reading and saving data, variables and data types
3. Database Manipulation: Creating variables, organizing and cleaning data
5. Estimation: Basis, regressions, post-estimation|
6. Programming basis: Good programming practice, macros, looping, branching