Empirical Methods
Empirical Methods
Module Coordinator/Lecturers
Study Programmes
Masterstudiengang Finance (MSc FI 20)
(01.09.2020)
Masterstudiengang Innovative Finance (MSc IF 24)
(01.09.2024)
Project Description
This course provides students with the knowledge of relevant methodologies in finance, especially in asset pricing. Students will learn to test market efficiency, estimate and test asset pricing models, and forecast stock returns. The course emphasizes practical implementation using R, based on "Tidy Finance with R".
Key topics covered are:
Key topics covered are:
- Introduction to empirical methods in finance and R
- Market efficiency and testing for random walks
- Asset pricing models and portfolio sorts
- Fama-MacBeth regressions
- Return forecasts and predictability
- Integrating financial economics concepts with empirical tests
Teaching Method
- Use R and related tools proficiently for empirical analysis.
- Utilize online platforms for data collection, collaboration, and presentation.
- Leverage technology for efficient and accurate empirical research.
Learning Results
After successful completion of the course, students will
Professional competence
Technological competence
Professional competence
- demonstrate proficiency in empirical methods relevant to finance.
- exhibit a deep understanding of market efficiency, asset pricing models, and return forecasting tech-niques.
- possess the ability to critically analyse and interpret empirical findings in financial data.
- master statistical and econometric techniques applicable to financial data.
- show expertise in using R for conducting empirical research and data analysis.
- design and execute robust empirical tests for financial hypotheses.
- collaborate effectively on empirical research projects.
- communicate empirical findings clearly and engage in scholarly discussions.
- appreciate diverse perspectives in empirical research and analysis.
- conduct independent research and engage in self-directed learning.
- apply critical thinking and problem-solving skills in the context of empirical finance.
- reflect on personal biases and methodological approaches.
Technological competence
- apply data analysis in financial data in R and RStudio.
- Understand, use and adapt advanced empirical methods in R.
- Leverage technology for efficient and accurate empirical research.
Literature
- Scheuch, C., & Voigt, S. (2024). Tidy Finance with R.
- Bali, T. G., Engle, R. F., & Murray, S. (2016). Empirical Asset Pricing: The Cross Section of Stock Returns. Wiley.
- Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2012). The Econometrics of Financial Markets. Princeton University Press.
Assessment Methods
Short paper presentation (10%), Empirical project report (60%), Project presenta-tion (30%); Attendance is mandatory (80%)