Registration via LPIS
|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|
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.
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)
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.
Participation: In class participation, quick quizzes, in-class-discussions.
Two assignments: Picked out of 6, 5-Minite presentation of assignment, proof of work.
- Class Participation: 15 points
- Assignments: 40 points
- Exam: 50 points
For 105/100 points i.e. 5 Bonus points
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Prior knowledge in Econometrics / Statistics will be extremely helpful