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Empirical Methods

Empirical Methods

Studiengänge
Masterstudiengang Finance (MSc FI 20) (01.09.2020)
Masterstudiengang Innovative Finance (MSc IF) (01.09.2024)
Inhalt
  • 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:Introduction to empirical methods in finance and RMarket efficiency and testing for random walksAsset pricing models and portfolio sortsFama-MacBeth regressionsReturn forecasts and predictabilityIntegrating financial economics concepts with empirical tests
Lehrmethode
  • 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.
Lernergebnisse
After successful completion of the course, students will
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.
Methodological competence
  • 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.
Social competence
  • collaborate effectively on empirical research projects.
  • communicate empirical findings clearly and engage in scholarly discussions.
  • appreciate diverse perspectives in empirical research and analysis.
Personal competence
  • 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.
Literatur
  • 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.
Prüfungsmodalitäten
Short paper presentation (10%), Empirical project report (60%), Project presentation (30%); Attendance is mandatory (80%)
Modulnummer:
6110588
Semester:
SS 26
ECTS-Credits:
3
Lehre:
28 L / 21 h
Selbststudium:
69 h
Sprache:
Englisch
Plansemester:
1