Vorlesung + Übung: Financial Data Analytics - Details
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Lehrveranstaltung wird in Präsenz abgehalten.

General information

Course name Vorlesung + Übung: Financial Data Analytics
Course number WIW-5283
Semester WS 2023/24
Current number of participants 49
Home institute Prof. Dr. Jan Muntermann - Financial Data Analytics
Courses type Vorlesung + Übung in category Teaching
Next date Tue., 12.12.2023 14:00 - 15:30, Room: (K: 1003)
Performance record Written Exam
Online/Digitale Veranstaltung Veranstaltung wird in Präsenz abgehalten.
Hauptunterrichtssprache englisch
Literaturhinweise M. Alvarez (2007) Market Data Explained: A Practical Guide to Global Capital Markets Information, Oxford, Elsevier
Sharda, R.; Delen, D.; Turban, E. (2020) Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th Ed., Prentice Hall, NJ.
Sabherwal, R.; Becerra-Fernandez, I. (2013) Business Intelligence: Practices, technologies and management, John Wiley & Sons, NY.
Tan, P.; Steinbach, M.; Karpatne, A.; Kumar, V. (2018) Introduction to Data Mining, 2nd Ed., Addison Wesley, Boston.
Han, J.; Pei, J.; Tong, H. (2022) Data Mining: Concepts and Techniques, 4th Ed., Morgan Kaufmann, Waltham, MA.
ECTS points 6

Course location / Course dates

(K: 1003) Tuesday: 14:00 - 15:30, weekly (12x)
(CIP 2113) Wednesday: 12:15 - 13:45, weekly (9x)
n.a. Wednesday: 12:15 - 13:45, weekly

Module assignments


After successfully passing this course, students have expertise in the most important methodological aspects of advanced data analytics in financial contexts. First, they understand the most relevant data structures, models, and standards in finance. Further, they understand the basic principles of descriptive, predictive, and prescriptive analytic approaches to support financial decision-making processes. Students know and apply a skill set suited for addressing related unstructured decision situations that require advanced data processing and analysis. Based on the introduced methodological foundations, the students are enabled to apply and evaluate different methodological approaches for advanced data analytics, especially data and text mining techniques to support decision-making in financial contexts.

Admission settings

The course is part of admission "Anmeldung mit Passwort: Financial Data Analytics".
The following rules apply for the admission:
  • Password required.