Asset Class Credit Products

The most common products in this asset class and characteristic numbers; potential indices and benchmarks for this asset class; active vs. passive strategies and replication of benchmarks; maybe: approaches estimation of the long-term return distribution for this asset class; objective functions and performance measures for this asset class; trading strategies for this asset class controlling a credit portfolio using derivatives; selection and optimisation for a credit portfolio: performance and attribution analysis for a credit portfolio

Art der Vermittlung

Präsenzveranstaltung

Art der Veranstaltung

Pflichtfach

Empfohlene Fachliteratur

Reilly, F., Brown, K., 2003, Investment Analysis and Portfolio Management, 7th ed., ITPS Thomson Learning; Grinold, R., Kahn, R., 2008, Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk, 2nd ed., McG

Lern- und Lehrmethode

Interactive teaching (lecture and discussion)

Prüfungsmethode

The assessment of this course relies on a written assignment with qualitative and quantitative tasks during the course (30 points) and a final written exam (70 points).

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

2024

Semester in dem die Lehrveranstaltung angeboten wird

2 SS

Incoming

Lernergebnisse der Lehrveranstaltung

After the successful completion of the course, students are able to characterize products of the asset class credit. They are capable of differentiating between different financial products within the asset class and identify their associated risks. Additionally, they are able to construct forecasting models for this asset class and utilize the results for portfolio allocation and selection. Furthermore, they have the ability to conduct performance and attribution analyses for this asset class.

Kennzahl der Lehrveranstaltung

0613-09-01-BB-EN-17