The course concentrates on the practical use of econometric methods, reviewing the relevant methodology, its use, and possible alternative modeling approaches. The lectures are supplemented by computer classes, where students can gain hands-on experience in applied econometric analysis. During the course, we will especially focus on time series techniques applied to forecasting asset volatility, modeling inflation, exchange rate volatility, and other topics that you may regularly encounter in economic and financial literature. The course focuses on the following topics in econometrics: OLS, IV, ARIMA, GARCH, VAR, cointegration, filters, and limited dependent variables.
If the course reaches its maximum capacity, the course lecturers may deregister students for whom the course is not mandatory.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
The course concentrates on the practical use of econometric methods, reviewing the relevant methodology, its use, and possible alternative modeling approaches. The lectures are supplemented by computer classes, where students can gain hands-on experience in applied econometric analysis. During the course, we will especially focus on time series techniques applied to forecasting asset volatility, modeling inflation, exchange rate volatility, and other topics that you may regularly encounter in economic and financial literature. The course focuses on the following topics in econometrics: OLS, IV, ARIMA, GARCH, VAR, cointegration, filters, and limited dependent variables.
If the course reaches its maximum capacity, the course lecturers may deregister students for whom the course is not mandatory.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Aim of the course -
Students will learn the basics of time series econometrics with an emphasis on how to apply these methods.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Students will learn the basics of time series econometrics with an emphasis on how to apply these methods.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Course completion requirements -
G
Grading - in line with the Dean's decree 17/2018.
Exam at the end of the semester (80% weight)
Term paper (20% weight)
Exam dates:
TBA in the second half of the semester
Please register for the exam using the SIS.
The details regarding the term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Grading - in line with the Dean's decree 17/2018.
Exam at the end of the semester (80% weight)
Term paper (20% weight)
Exam dates:
TBA in the second half of the semester
Please register for the exam using the SIS.
The details regarding the term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Literature -
Selected recommended textbooks on applied econometrics:
Brook, Ch.: Introductory Econometrics for Finance, New York: Cambridge University Press.
Enders, W.: Applied Econometric Time Series, 2nd edition, Hoboken: Wiley, 2003. Harris, R. and R. Sollis: Applied Time Series Modelling and Forecasting, Chichester: Wiley, 2003. Stewart, K. G.: Introduction to Applied Econometrics, Belmont: Thomson Brooks, 2005. Verbeek, M.: A Guide to Modern Econometrics, 2nd edition, Chihester: John Wiley, 2004. Kratzig, M. and H. Lutkepohl ,Applied Time Series Econometrics, New York: Cambridge University Press, 2004. Kočenda, E. and Černý, A.: Elements of Time Series Econometrics: An Applied Approach, Prague: Karolinum Press, 2007.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Selected recommended textbooks on applied econometrics:
Brook, Ch.: Introductory Econometrics for Finance, New York: Cambridge University Press.
Enders, W.: Applied Econometric Time Series, 2nd edition, Hoboken: Wiley, 2003. Harris, R. and R. Sollis: Applied Time Series Modelling and Forecasting, Chichester: Wiley, 2003. Stewart, K. G.: Introduction to Applied Econometrics, Belmont: Thomson Brooks, 2005. Verbeek, M.: A Guide to Modern Econometrics, 2nd edition, Chihester: John Wiley, 2004. Kratzig, M. and H. Lutkepohl ,Applied Time Series Econometrics, New York: Cambridge University Press, 2004. Kočenda, E. and Černý, A.: Elements of Time Series Econometrics: An Applied Approach, Prague: Karolinum Press, 2007.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Teaching methods -
Lectures accompanied by seminars in computer room 016.
The software R will be used during the seminars, and materials will be processed in the interactive Jupyter Notebook .ypinb format (freeware, available on all computers in 016). If you want to work on your computer, ensure in advance Jupyter is properly connected to the R kernel.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Lectures accompanied by seminars in computer room 016.
The software R will be used during the seminars, and materials will be processed in the interactive Jupyter Notebook .ypinb format (freeware, available on all computers in 016). If you want to work on your computer, ensure in advance Jupyter is properly connected to the R kernel.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Course assessment methods and requirements for successful completion, grading scheme -
Grading - in line with the Dean's decree 17/2018.
Exam at the end of the semester (80% weight)
Term paper (20% weight)
The details regarding the research proposal and term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Grading - in line with the Dean's decree 17/2018.
Exam at the end of semester (80% weight)
Term paper (20% weight)
The details regarding the research proposal and term paper are available in Lecture 1.pdf and in separate pdf files posted (during the semester) in the SIS.
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
Syllabus -
1. Introduction
2. OLS and basics
3. Introduction to Time Series
4. ARIMA Modeling
5. GARCH (2 lectures)
6. Introduction to Cointegration
7. Vector Autoregression
8. TSLS, IV
9. Non-linear time series models
10. Limited dependent variable models in finance
11. Time series filters
12. Networks
13. Guest lecture
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
1. Introduction
2. OLS and basics
3. Introduction to Time Series
4. ARIMA Modeling
5. GARCH (2 lectures)
6. Introduction to Cointegration
7. Vector Autoregression
8. TSLS, IV
9. Non-linear time series models
10. Limited dependent variable models in finance
11. Time series filters
Last update: Horváth Roman, prof., Ph.D. (11.02.2026)
