Asset Class Equity

Lehrinhalte

· Most common products in this asset class;
· Indices and benchmarks for this asset class;
· Active vs. passive strategies and replication of benchmarks;
· Applying Python for as many topics as possible mentioned here
· Performance measures for this asset class;
· Factor models; market beta, size factor, value factor, momentum factor, CAPM,
· Multi-Factor models, Fama-French, Factor benchmarks and style analysis,
· Smart beta, types of factors
· Naive vs. Scientific diversification,
· Computation of the statistical return distribution and of statistical characteristic numbers for an equity portfolio;
· Selection and optimisation for an equity portfolio:
· Performance and attribution analysis of an equity portfolio
· Company valuation: different methodologies with intrinsic vs. relative valuation

Art der Vermittlung

Präsenzveranstaltung

Art der Veranstaltung

Pflichtfach

Lern- und Lehrmethode

Interactive teaching (lecture and discussion)

Prüfungsmethode

Assessment consist of a 30-point quantitative project and a 70-point written final exam conducted in a pen-and-paper format.

Voraussetzungen laut Lehrplan

Courses of the 1st semester

Schnellinfos

Studiengang

Quantitative Asset and Risk Management (Master)

Akademischer Grad

Master

ECTS Credits

2.00

Unterrichtssprache

Englisch

Studienplan

Berufsbegleitend

Studienjahr, in dem die Lerneinheit angeboten wird

2025

Semester in dem die Lehrveranstaltung angeboten wird

2 SS

Incoming

Ja

Lernergebnisse der Lehrveranstaltung

After the successful completion of the course, students are able to characterise the asset class equity, lay out the risks associated with this asset class and know the most efficient way of investing in this asset class. They are capable of programming in Python return and distribution metrics as well as other risk metrics. In addition, students are able to calculate portfolios based on the CAPM and Fama-French while they also have the ability to conduct performance and attribution analyses for equities in Python. Finally students are in the position to value companies with different methodologies, especially intrinsic and relative valuations.

Kennzahl der Lehrveranstaltung

0613-09-01-BB-EN-15