Financial Data Decision Analysis

2019-2020

Course Objective

In this course, students study the quantitative skills necessary to do
empirical research.
You will be able to answer questions such as:
- How to handle financial data?
- What model should we use for these data and is this a valid model?
- What happens when the assumptions underlying the model do not hold?
Beyond understanding different types of models, you will also be able to
work with them practically by means of the statistical software package
Stata.
Finally, you learn how to interpret the outcomes of your analyses
correctly and do proper inference.

After this course, you are able to:
- use financial data in a proper way and set up a plausible empirical
model (Academic Skills);
- to work with the classical linear regression model (and its
shortcomings) and panel regressions making use of the software program
Stata (Academic Skills, Bridging Theory and Practice);
- interpret correctly the outcomes of the aforementioned models and
report them according to the academic standards (Academic Skills).

Course Content

Students will learn how to summarize different forms of data by means of
statistics, develop a thorough understanding of the classical linear
regression model, the concept of inference, the assumptions needed, and
what to do if any of these assumptions are violated. We will introduce
concepts of the transformation of variables and dummy variables. You
will be acquainted with the event study approach, binary choice and
limited dependent variable models, models with time series data and
panel data. Moreover, the course covers methods that help you identify
causal links between variables. You do not only learn about this in
theory, but also actually apply what you learned in practical financial
assignments using statistical software (Stata) by working in teams. The
course thus covers a lot of ground, but sets you well on your way for
the Research Seminar in January and your subsequent thesis research.

Teaching Methods

Lectures (4 hrs/week)
Computer lab sessions (2 hrs/week)

Method of Assessment

Written exam (Individual assessment)
Case 1 (Group assessment)
Case 2 (Group assessment)

Literature

Christopher Dougherty, Introduction to Econometrics, Fifth Edition,
Oxford University Press.

Target Audience

Master students Business Administration, specialization Financial
Management.

General Information

Course Code E_BA_FDDA
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator dr. G. Tumer Alkan
Examiner dr. G. Tumer Alkan
Teaching Staff

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Computer lab, Lecture
Target audiences

This course is also available as: