Keen interest in programming and quantitative problem solving
Good knowledge of a programming language is a powerful tool for researchers and practitioners. It is also a valuable skill in the labor market. This course introduces the students to advanced and powerful programming techniques. Building upon the foundation of Programming in Finance I, this course uses mostly R, but adds other tools where useful and necessary.
The course has the following goals:
After this course, students should be able to collaborate on a complex R programming project in finance and data science.
Description / Program
The course is structured along computational concepts, not applications. The topics include
Learning Method / Style of Lessons
The course is organized in seven blocks of four hours. Each block introduces a new concept and employs learning-by-doing to move from theory to practice. Students start with short tutorial or reading 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 perform small individual tasks (mostly writing summaries) and collaborate on three to four larger programming projects.
33% Small individual tasks
67% Programming projects in small groups
Students should bring a laptop with R and R Studio installed to all classes.
To be discussed in the first lecture.