Financial Data Analytics

Course goals

Learning objectives
At the end of the course, the student is able to:

• use Python and Jupyter notebooks to program
• understand and use of different data types, data structures, loops, functions, and pandas in Python
• import financial data via application programming interfaces (API)
• apply programming skills to analyse and evaluate a range of finance issues relating to the analysis of financial data incl. descriptive analysis and regression analysis

Content

This course aims to combine programming and analytical skills to interpret and analyse financial data for a wide variety of finance issues. Building up programming skills gradually, it will be shown how to effectively use Python to handle and analyse data in a finance context. The course demonstrates by using real-life cases how to analyse financial data including balance sheet figures and, time series. Thereby the course provides valuable skills for other courses in the Banking and Finance master program, in particular, it is a critical requisite for the course Algorithms in Finance.

In particular, students will learn to create, modify, and extrapolate the use of:

• Variables of different datatypes (Boolean, integer, floats, strings)
• Lists
• Dictionaries
• Conditional Statements
• Loops (for, while)
• Functions
• Pandas
• Statistical models

In case online access is required for this course and you are not in the position to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN. Separate or spare codes are usually not available.