Project Seminar: Finance with R
Semester: SP 23
The goal of this course is to bridge the gap between understanding financial theories, models and concepts and implementing them using the R software of statistical computing. In the first part of the course, students will learn how to download financial data from Refinitiv Datastream and other sources, how to import data into R and how to create a tidy database. This part will also introduce important structural elements of R programs, such as functions and group-wise transformations. In the second part of the course, students will work on their own empirical project using R. The data will be individual to each student, but similar topics will be assigned to groups of students to allow and encourage cooperation. At the end of the course, students should be able to independently implement a project in R, e.g., as part of a master's thesis or later in practice.
- Matloff, N., The Art of R Programming, no starch press 2011.
Wickham, H. & Grolemund, G., R for Data Science, O’Reilly 2017.
Brooks, C., Introductory Econometrics for Finance, 4th ed., Cambridge University Press 2019.