Integrating Aspects of Asset Management

Lehrinhalte

The course includes advanced programming in Python, focusing on backtesting trading strategies and setting up live trading strategies on a server. It also covers Linux, server setup, and the use of interactive brokers. Additionally, the course offers an online certification in Machine Learning using SAS Viya, along with a course on utilizing the SAS Viya REST API with both Python and R.

Art der Vermittlung

Präsenzveranstaltung

Art der Veranstaltung

Pflichtfach

Empfohlene Fachliteratur

Aronson, David: Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, Wiley 2006 Hilpisch, Yves J.: Python for Finance: Mastering Data-Driven Finance, 2nd Ed., O’Reilly 2019 Hilpisch, Yves J.: Python for Algorithmic Trading: From Idea to Cloud Deployment, 1st Ed., O’Reilly 2020

Lern- und Lehrmethode

Interactive course, consisting of lectures, group work, and self-study. Certification for SAS Viya and machine learning is also offered.

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

Upon successful completion of this course, students will be able to: • Demonstrate advanced proficiency in the Python programming language, with a focus on financial applications. • Develop, backtest, and implement trading strategies using Python, as well as optimize portfolios based on quantitative methods. • Apply knowledge of Linux and server configuration in financial settings, particularly in the integration with interactive brokerage systems. • Utilize SAS Viya software to perform data analysis, machine learning, and interact with REST APIs, effectively applying these tools to real-world financial scenarios.

Kennzahl der Lehrveranstaltung

0613-09-09-BB-EN-29