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Financial Econometrics

Due to the corona pandemic, the teaching of this course for the Winter Semester 2020/21 will begin on November 2, 2020 and it will be offered exclusively in digital form, i.e. the lectures and the exercise sessions will be recorded and uploaded on ILIAS. 


Registration for the lecture

Students have to sign in for this course in HISinOne. The registration in ILIAS will be carried out automatically.

Registration for the exam

Please note that the registration for the lecture does not automatically mean that you are registered for the exam! A separate registration for the exam is mandatory!
You can find the current examination dates as well as further information on the registration for the examination as well as the deadlines for registration and deregistration of the examinations on the homepage of the examination office.


In ILIAS, the course can be accessed without a password until November 9, 2020, 08:59 am. Starting with November 9, 2020, 9:00 am, password will be required in order to access the course material, the recorded videos of lectures and exercises sessions as well as the updates and relevant information in ILIAS. The password will be sent to all registered students via ILIAS on November 9, 2020 at 9:00 am.

Instructors Dr. Ekaterina Kazak (University of Manchester, U.K.) will give one guest lecture and one tutorial on the topic Portfolio Analysis






Statistics, Mathematics, Econometrics, Time Series Analysis, Principles of Finance

Qualification Target

This course aims at endowing students with the necessary econometric knowledge and tools for undergoing empirical research on financial data.



The course covers the fundamentals of financial econometrics and empirical finance with emphasis on both theoretical foundations and empirical applications. The course aims at sharpening students’ view on the limitations of the theoretical models and their empirical applications as well as at equipping students with a profound knowledge of financial data handling and programming skills in Python.

The main topics covered are:

  1. Empirical Properties of Financial Data
  2. Univariate GARCH Models
  3. Univariate Stochastic Volatility Models
  4. Application: Value at Risk and Expected Shortfall
  5. Multivariate GARCH Models
  6. Application: Portfolio Analysis
  7. High-Frequency Finance
  8. Realized (Co)variance Models
Main References
  • Campbell, J. Y., A. W. Lo and A. C. MacKinlay (1997): The Econometrics of Financial Markets, Princeton University Press. eBook
  • Francq, C. and Zakoian J. M. (2011): GARCH Models: Structure, Statistical Inference and Financial Applications, eBook
  • Franses & van Dijk (2000): Nonlinear Time Series Models in Empirical Finance, Cambridge University Press Cambridge. eBook
  • Gourieroux C. and J. Jasiak (2001): Financial Econometrics, Princeton University Press. eBook
  • Hayashi, F. (2002): Econometrics, Princeton University Press.
  • McNeil, A. J., R. Frey and P. Embrechts: Quantitative Risk Management: Concepts, Techniques and Tools, Princeton University Press.
  • Tsay, R. S. (2005): Analysis of Financial Time Series, 3rd ed., John Wiley & Sons. eBook
  • Andersen T., Davis R., Kreiß J. and Mikosch T. (2009): Handbook of Financial Time Series, Springer. eBook
  • Due to the Corona pandemic, the exam on 17. February 2021 will take place online.
  • The retake exam on 2 August 2021 at 9am will be in person and not online.In the exam you are allowed to take with you a non-programmable pocket calculator, a hardcopy of a German-English dictionary book as well as a one-sided A4 hand-written cheat sheet.
    It takes place in the Aula (KG I).


100% final exam (90 minutes)

Target Group

The course can be chosen as an elective 6 ECTS course in:

  • M.Sc. BWL (Volkswirtschaftslehre / Quantitative Methoden/Wirtschaftsinformatik)
  • M.Sc. VWL (Accounting, Finance and Taxation / Business Analytics / Constitutional Economics and Competition Policy / Empirical Economics / Network Economics and IT Risk Management)
  • M.Sc. in Economics (Finance / Information Systems and Network Economics)