BPE_CARA Time Series

Faculty of Economics and Administration
Spring 2022
Extent and Intensity
2/2/0. 10 credit(s). Type of Completion: zk (examination).
Taught in person.
doc. Ing. Daniel Němec, Ph.D. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (seminar tutor)
Ing. Mgr. Vlastimil Reichel, Ph.D. (lecturer)
Ing. Mgr. Vlastimil Reichel, Ph.D. (seminar tutor)
Mgr. Jakub Chalmovianský (assistant)
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
basic matrix algebra, elementary probability and mathematical statistics, pssing the course Introduction to econometrics (BPE_ZAEK) (recommended)
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 27 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.
  • 1. Stationary time-series models (ARMA models, stationarity, ACF, PACF, Box-Jenkins model selection, forecasting, seasonality and structural changes).
  • 2. Models with trend (deterministic and stochastic trends, unit root tests, univariate decomposition methods).
  • 3. Multiequation time series models (intervention analysis, VAR models, impulse response function, structural VAR models, Blanchard-Quah decomposition).
  • 4. Cointegration and error-correction models (cointegration and common trends, testing for cointegration, VEC models).
    required literature
  • ENDERS, Walter. Applied econometric time series. 4th ed. Hoboken: Wiley, 2015. x, 485. ISBN 9781118808566. info
    recommended literature
  • CIPRA, Tomáš. Finanční ekonometrie. 1. vyd. Praha: Ekopress, 2008. 538 s. ISBN 9788086929439. info
  • Arlt, Josef; Arltová, Markéta: Ekonomické časové řady. Professional Publishing 2009. ISBN 978-80-86946-85-6.
Teaching methods
lectures, computer labs practices, class discussion, group semestral projects, oral exam
Assessment methods
The course consists of lectures and seminars. The course is concluded by the oral exam. Students can attend the exam if they fulfill these conditions: active attendance at the seminars, successful solution of the semestral projects (homeworks).
Language of instruction
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.
  • Enrolment Statistics (recent)
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