Program Overview

Program Overview

The Programming in Finance and Economics I course is a comprehensive program designed to teach students how to solve quantitative problems in economics and finance using the R programming language.

Description

The course is structured along computational concepts, covering topics such as:

• Recap of basic R: variables, types, operators, and main commands
• How computers calculate: floating point numbers
• 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

Prerequisites

This course requires basic knowledge of a programming language, as specified in the admission criteria to the Master in Finance. For USI bachelor graduates, Informatica I is sufficient. Students from other universities require a similar introduction to programming. Students with little or no programming experience in R have to follow a tutorial before the start of the semester.

Objectives

The course aims to teach students how to solve quantitative problems in economics and finance using R. The objectives include:

• Learning the most important elements of the R language
• Understanding the differences between analytical and numerical problem-solving
• Learning how to translate mathematical or statistical problems into the R language
• Learning how to organize data efficiently with the help of R
• Learning how to write efficient and durable R programs

Teaching Mode

The course is taught in presence.

Learning Methods

The course is organized in seven blocks of four hours, with each block introducing a new concept and employing 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, followed by studying a sample R program and trying to understand the underlying ideas. Students then train their skills with programming exercises that are submitted to an online system that provides instant feedback.

Examination Information

The examination consists of:

• 10% participation in online tutorials, graded based on timely completion
• 30% individual programming exercises during the course phase, graded based on the correctness of the results and programming style
• 60% 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

Bibliography

Recommended readings include:

• An Introduction to R
• Bennett, Mark J., Hugen, Dirk L.. Financial analytics with R: building a laptop laboratory for data science. Cambridge, UK: Cambridge University Press, 2016.
• RStudio Webinars - RStudio (Choose "Programming part I")

Education

The course is part of the following programs:

• Master of Science in Economics, Lecture, 120 ECTS, Elective, 2nd year
• Master of Science in Economics, Lecture, Internship or Electives, Elective, 2nd year
• Master of Science in Economics, Lecture, Mandatory if without internship, Elective, 2nd year
• Master of Science in Economics, Lecture, minor Data Science, 1st year
• Master of Science in Economics in Finance, Lecture, 1st year

Prerequisite

Informatics I, Tenconi P., SA

Additional Information

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