BPE_CARA Time Series

Faculty of Economics and Administration
Spring 2026
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
doc. Ing. Daniel Němec, Ph.D. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský, Ph.D. (assistant)
Ing. Mgr. Vlastimil Reichel, Ph.D. (lecturer)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Guaranteed by
doc. Ing. Daniel Němec, Ph.D.
Department of Economics – Faculty of Economics and Administration
Contact Person: Mgr. Jarmila Šveňhová
Supplier department: Department of Economics – Faculty of Economics and Administration
Prerequisites
It is recommended to successfully complete the course Introduction to Econometrics (BPE_ZAEK).
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 7 fields of study the course is directly associated with, display
Course objectives
The course is devoted to mathematical-statistical approaches to the analysis of economic processes described by time series. The introductory part of the course is focused on univariate time series analysis using the Box-Jenkins methodology. The students will learn the procedures of identification of a suitable model of the time series, the criteria for the suitable model verification (including the statistics and tests based on model predictions), and the problems of seasonality. The second part of the course deals with the models with trend, unit root tests and univariate trend decomposition. The last section of the course will be devoted to multiequation time-series models.
All studied areas will place emphasis on the students' ability to use the gained knowledge in practice.
The main objective of the course is to provide the students with knowledge and skills, which are necessary for practical utilization of the time series analysis.
Learning outcomes
At the end of the course the students should be able:
- to analyze real data;
- to create a suitable model for the data;
- to construct future forecasts;
- to evaluate and interpret obtained model outcomes;
- to basically understand scientific texts from the field of time series econometrics.
Syllabus
  • 1. Stationary time-series models (ARMA models, stationarity, ACF, PACF, Box-Jenkins model selection, forecasting, seasonality and structural changes).
  • 2. Models with trends (deterministic and stochastic trends, unit root tests, univariate decomposition methods).
  • 3. Multiequation time series models (intervention analysis, VAR models, impulse response function).
  • 4. Cointegration and error-correction models (cointegration and common trends, testing for cointegration, VEC models).
  • 5. Modelling volatility.
  • 6. Switching and state.space models (an introduction).
Literature
    required literature
  • ENDERS, Walter. Applied econometric time series. 4th ed. Hoboken: Wiley, 2015, x, 485. ISBN 9781118808566. URL info
  • BROOKS, Chris. Introductory econometrics for finance. Fourth edition. Cambridge: Cambridge University Press, 2019, xxxi, 696. ISBN 9781108422536. info
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Seventh edition. Boston: Cengage Learning, 2020, xxi, 826. ISBN 9781337558860. info
    recommended literature
  • HEISS, Florian. Using R for introductory econometrics. 2nd edition. Düsseldorf: Florian Heiss, 2020, 368 stran. ISBN 9788648424364. info
  • HEISS, Florian and Daniel BRUNNER. Using Python for introductory econometrics. 1st edition. Düsseldorf: Florian Heiss, 2020, 418 stran. ISBN 9788648436763. info
Teaching methods
lectures, computer lab practices, class discussions, group semestral projects, individual final project (oral exam)
Assessment methods
The course consists of lectures and seminars. The course is concluded by the final individual project and its defence (oral exam). Students can attend the exam if they fulfil these conditions: active attendance at the seminars and successful solution of the semestral projects (homework). In the case of going abroad (Erasmus), it is not mandatory to fulfil the condition of active participation in exercises. The remaining requirements remain unchanged.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught every week.
General note: Přednášky jsou dostupné online a ze záznamu.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2026, recent)
  • Permalink: https://is.muni.cz/course/econ/spring2026/BPE_CARA