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Programming in Finance and Economics I

Description

Prerequisites

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.

Objectives

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.

Exam Style

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

Requested Material

Students should bring a laptop with R and R Studio installed to all classes

This class is generously supported by Datacamp.

Readings/Textbooks

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

People

 

Gruber P.

Course director

Additional information

Semester
Fall
Academic year
2020-2021
ECTS
3
Language
English
Education
Master of Science in Economics, Elective course, Minor in Public Policy, 2nd year
Master of Science in Economics, Core course, Minor in Data Science, 1st year
Master of Science in Economics and Communication in Financial Communication, Elective course, Elective course, 2nd year
Master of Science in Economics in Finance, Core course, Minor in Quantitative Finance, 1st year
Master of Science in Economics in Finance, Core course, Minor in Banking and Finance, 1st year
Master of Science in Economics in Finance, Core course, Minor in Digital Finance, 1st year