Syllabus

Title
2087 S3EMF1 Empirical Methods in Finance I
Instructors
Dr. Oliver Rehbein
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/02/22 to 09/25/22
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Tuesday 10/18/22 01:30 PM - 02:30 PM D3.0.222
Tuesday 10/25/22 02:00 PM - 05:00 PM D5.1.002
Tuesday 11/08/22 12:30 PM - 04:00 PM D4.0.047
Tuesday 11/15/22 01:30 PM - 05:00 PM TC.4.17
Tuesday 11/22/22 01:30 PM - 05:00 PM EA.5.030
Tuesday 11/29/22 01:30 PM - 05:00 PM D4.0.136
Tuesday 12/06/22 01:30 PM - 05:00 PM D3.0.237
Tuesday 12/20/22 02:00 PM - 05:00 PM D4.0.136

Contents

In this course, students learn to differentiate between correlation and causality in financial applications. First, the course covers the importance of causality and the theory behind separating it from simple correlations. Then students learn how to establish a relationship between two variables in a dataset using simple OLS regressions and finally the most common methods to establish causal effects in econometric applications. They will also get a first introduction to working with data in statistical software. They will also learn to read and interpret modern finance research on a variety of topics.

Learning outcomes

After completing this class the students will have the ability to:

  • differentiate between correlation and causal effects
  • understand basic relationships in financial datasets
  • understand different methods of finding causal effects in finance applications

Moreover, after completing this class the students will have the ability to:

  • give small presentations in class
  • interact with their peers to find answers to challenging questions

Apart from this, after completing this classstudents will have the ability to:

  • read and interpret modern applied economics (finance) research
  • interpret regression outputs
  • evaluate and criticize finance research, including their own (and their peers)

Attendance requirements

Students collect points for class participation in various ways, which will be part of the final grade. Participation points can be collected only through in-person attendance, but not all lectures have to be attended to achieve full points, leaving room for absence because of illness or other reasons.

Teaching/learning method(s)

Participation: In class participation, quick quizzes, in-class-discussions.

Two assignments: Picked out of 6, 5-Minite presentation of assignment, proof of work.

Assessment

  • Class Participation: 15 points
  • Assignments: 40 points
  • Exam: 50 points

For 105/100 points i.e. 5 Bonus points

Readings

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

Recommended previous knowledge and skills

Prior knowledge in Econometrics / Statistics will be extremely helpful

Availability of lecturer(s)

Please ask content-related questions in class, so all students can benefit. Feel free to reach out via email for all other inquiries: oliver.rehbein@wu.ac.at

Last edited: 2022-10-18



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