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International Business Administration

Data Storytelling in Finance (R-Module)

Exam number: NEU ZU VERGEBEN

Semester: From 2nd semester

Duration of the module: one block

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Every summer semester, usually 2nd block

Prerequisites: Students must have taken at least one course that introduced data analysis and must have the ability to write code in the R programming language. Some topics may require specialized knowledge in statistics, machine learning, or portfolio management. Registration for this course according to the deadline specified in Moodle is required.

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Sven Husmann

Name of the professor: Prof. Dr. Sven Husmann

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time: 34 h, self-study: 146 h

Contact hours (per week in semester): 3

Methods and duration of examination:
Participants are required to submit a website with the results of the research project they have chosen with RShiny and present their work in an oral presentation.

Emphasis of the grade for the final grade: Please check the regulations of the study programs.

Aim of the module (expected learning outcomes and competencies to be acquired):
While many courses on data analytics teach how and when to apply different types of models, it is often neglected that in practice it is the data itself that needs to be examined, cleaned, visualized and explained. Because some people see only a large set of inscrutable numbers when confronted with Big Data analysis, data analysts must also be able to tell the story about the meaning and implications of the data being analyzed. Models are becoming increasingly complex and remain a black box for many decision makers and sometimes even for the modelers. It is therefore of utmost importance in practice to be able to communicate approaches and model implications in an understandable way to people with different backgrounds. In this course, students will learn how to use RShiny to program an interactive website that can be accessed from anywhere in the world without restrictive software requirements. To strengthen their oral communication skills, students will be required to conduct an empirical study using state-of-the-art models from the current finance literature and present their findings both using RShiny and in an oral presentation. The selection from various topics of current literature allows participants to become experts in a particular field. The mandatory participation in the oral presentations of fellow students aims to broaden the range of knowledge in the field of finance.

Contents of the module:
Students may choose from a variety of topics for their research project. The seminar's general topics may change each semester. Examples of general topics include factor investing, portfolio management, business valuation, risk management, or electricity pricing. Please check the Moodle pages for the most current topics.

Teaching and learning methods:
In the first two weeks compulsory online lectures to introduce the general topic. Afterwards project work in small groups.

Literature (compulsory reading, recommended literature):
Literature will be announced in the Moodle course.

Further information:
Registration in Moodle Viadrina required.