Integrating Aspects of Asset Management

Lehrinhalte

  • Programming language "Python" at an advanced level
  • Backtesting of trading strategies as well as setting up a live trading strategy on a server
  • Teaching Linux, server setup as well as Interactive Brokers skills
  • Online course and certification: Machine Learning using SAS Viya
  • Online course: Using SAS Viya REST API with Python and R

Art der Vermittlung

Präsenzveranstaltung

Art der Veranstaltung

Pflichtfach

Empfohlene Fachliteratur

David Aronson: Evidenced-based technical analysis
Yves Hilpisch: Phyton for Finance
Yves Hilpisch: Phyton for Algorithmic Trading

Lern- und Lehrmethode

Interactive teaching (lecture and group works), self-study and certification for SAS Viya and Machine learning

Prüfungsmethode

This practical class has two components each counts for 50 points, in total 100 points.
Self-study: SAS Viya online courses (50 points)
Classroom teaching and group work for trading strategies and interactive brokers skills (50 points)
The rules are outlined in the syllabus of each lecturer.

Voraussetzungen laut Lehrplan

Courses of the 2nd semester

Schnellinfos

Studiengang

Quantitative Asset and Risk Management (Master)

Akademischer Grad

Master

ECTS Credits

6.00

Unterrichtssprache

Englisch

Studienplan

Berufsbegleitend

Studienjahr, in dem die Lerneinheit angeboten wird

2025

Semester in dem die Lehrveranstaltung angeboten wird

3 WS

Incoming

Ja

Lernergebnisse der Lehrveranstaltung

Learning outcomes After the successful completion of the course, students are able to use the software “Python” on an advanced level and to apply the programming knowledge on setting up a trading strategy, backtesting a trading strategy and optimize a portfolio. Students are familiar with Linux and server setup and can apply the learnings to interactive brokerage.
Students are able to work with the SAS software Viya and can apply the programming skills to Machine Learning and REST API.

Kennzahl der Lehrveranstaltung

0613-09-09-BB-EN-29