Program Overview

Programming in Finance and Economics I

Description

This course requires basic knowledge of a programming language, as specified in the admission criteria to the Master in Finance. For USI students, Informatica I is sufficient. Students with little or no programming experience in R have to follow an online tutorial before the course starts.

The course teaches how to solve quantitative problems 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 and confident to use R independently for project work, courses such as numerical methods or for their master thesis.

Program

The course is structured along computational concepts, not applications. The topics include:

• Recap of basic R: variables, types, operators and main commands
• How computers calculate: floating point numbers
• The R language: commands and functions
• Modular programming: User-defined functions and loops
• Working with data in R, data sources and data APIs
• A short introduction to numerical algorithms
• Random number generation and simple simulations
• Optimization
• Finding and installing R packages
• How to write a successful program or an entire research report in R
• Finding errors and improving R programs

Learning Method

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 online tutorials 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 train their skills with programming exercises that are submitted to an online system that provides instant feedback.

Exam Style

The exam style consists of:

• 10% participation in online tutorials, graded based on timely completion
• 40% individual programming exercises during the course phase, graded based on the correctness of the results and programming style
• 50% programming project in small groups, due at the end of the semester, graded based on four criteria:
  • Completeness and correctness
  • Programming style
  • User documentation
  • Complexity of the problem and the solution

Requested Material

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

Readings/Textbooks

All slides and sample programs will be published on iCorsi. Additional material about the R programming language includes "An introduction to R" by Venables et al.

Education

This course is part of the following programs:

• Master of Science in Economics, Core course, Minor in Data Science, 1st year
• Master of Science in Economics in Finance, Core course, 1st year

Additional Information

• Semester: Fall
• Academic year: Not specified
• ECTS: 3.0
• Language: English