Applied Big Data Analytics in Finance (Python)

Summary: Through three applications, the course will provide an introduction to Big Data Analytics in finance. Each project (6 hours) will be divided into three sessions:

1. A presentation of the problematic and a discussion about the tools and the methodology that could be used by students.
2. A session during which students works in group on the project and ask questions (debugging).
3. A presentation of the project to the class by the students.

- The first project will consist of using Google Trends to create a novel indicator of sentiment/attention to financial news before using this indicator for asset pricing.

- The second project will consist of analyzing interactions between users on Twitter to detect influential users talking about financial markets using network theory.

- The third project will consist of using machine learning algorithms to classify messages posted on StockTwits as positive or negative.

The language used for the course is Python. 

Professor: Thomas Renault (Assistant Professor - University Paris 1 Panthéon-Sorbonne)

Student assessment: Project (submission + presentation)