Stata Programming and Applications in Finance

FIN544 Stata Programming and Applications in Finance

Autumn 2020

  • Topics

    The course focuses on programming in Stata. Programming techniques in Stata will be introduced and applications to real datasets will be covered with the goal of identifying causal relations in empirical corporate finance. The course first covers basic aspects of Stata (for example, data management and importing of data). Subsequently, we will cover bootstrapping, panel data, diff-in-diff estimators, as well as machine learning among other things. 

  • Learning outcome

    After completing the course, students will be able to:

    Skills.

    - use Stata to implement  modern technics  to identify causal relations in empirical corporate finance

    Knowledge. 

    - identify causal relations in empirical corporate finance

  • Teaching

    The course takes place over seven weeks and is taught via Zoom. Each week consists of a 30 minute pre-recorded video lecture and a 60-minute synchronous lecture. 

  • Required prerequisites

    Successful completion of PhD-level empirical corporate finance course.

  • Requirements for course approval

    None.

  • Assessment

    Students are required to deliver four written individual assignments during the course.

  • Grading Scale

    Pass-fail

  • Computer tools

    STATA

  • Literature

    Christopher F. Baum, An Introduction to Stata Programming, Second Ed., Stata Press

Overview

ECTS Credits
2.5
Teaching language
English
Semester

Spring 2020. Postponed to fall 2020 due to Covid.

Course responsible

Eric de Bodt, Professor of Finance