Programming in Finance and Economics I
Introduction to programming with R, for example Informatica I or an online introduction (see requested material)Students having no programming experience will have the opportunity to follow an online tutorial before the course starts.
Many interesting problems in economics and finance can only be solved with the help of the computer, as no analytical solution exists or large amounts of data are involved. This course teaches how to solve quantitative problems in finance with the help of R, a powerful and widely used open source programming environment.
The course has the following goals:
- Learn the most important elements of the R language
- Understand the differences between analytical and numerical problem solving
- Learn how to translate mathematical or statistical problems into the R language
- Learn how to organize data efficiently with the help of R
- Learn how to write efficient and durable R programs
After this course, students should be able to use R in courses such as numerical methods as well as for their master thesis.
Learning Method / Style of Lessons
The course is organized in seven blocks of four hours. It takes part in the first half of the semester, to leave sufficient time for the programming projects. Each block introduces a new concept and employs learning-by-doing to move from theory to practice. Students start with short online tutorial before each class (flipped classroom). The course block itself starts with a presentation of a new concept. Next, we study a sample R program that illustrates this concept and try to understand the underlying ideas. Students will then solve a few simple programming exercises to be submitted online by the next class.
20% participation in online tutorials
40% individual programming exercises during the course phase
40% programming project in small groups, due at the end of the semester
Students should bring a laptop with R and R Studio installed to all classes
This class is generously supported by Datacamp.
All slides and sample programs will be published on iCorsi.
Additional material about the R programming language
Venables et al: An introduction to R, https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
Additional material about the Rstudio IDE
https://www.rstudio.com/resources/webinars/ (choose “Programming part I”)
Additional resources will be discussed in the first lecture
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