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Lecturer(s)
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Zapletal David, doc. Mgr. Ph.D.
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Course content
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Introduction to time series and their characteristics. Decomposition of time series. Modeling of trend component by trend functions. Diagnostic of trend function. Modeling of trend component by moving averages simple, weighted, centered. Exponential smoothing simple, double, Holts method. Modeling of seasonal component simple and regression approach. Holt-Winters method. Time series transformations. Randomness testing. Introduction to Box-Jenkins methodology.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Work with text (with textbook, with book), Methods of individual activities, Skills training
- Participation in classes
- 14 hours per semester
- Home preparation for classes
- 50 hours per semester
- Preparation for a credit (assessment)
- 40 hours per semester
- Preparation for an exam
- 46 hours per semester
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Learning outcomes
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The aim of the course is to acquaint students with basic concepts and methods that are associated with the analysis of univariate time series with emphasis on the application of these methods using appropriate statistical software.
A student who has successfully completed a subject can: to list basic types and characteristics of univariate time series; clarify the principle of time series decomposition on trend, seasonal, cyclical and residual components; apply methods for modeling trend and seasonal components; to clarify the basic concepts of Box-Jenkinson's methodology related to the modeling of non-seasonal univariate time series. A student who successfully completed the subject will: to use the basic methods to verify the suitability of the time series model obtained by the decomposition method; recognize the type of time series and determine its basic characteristics; in the decomposition method: using the commonly available software (Excel) to model the trend and seasonal components of the time series and in particular on the basis of an analysis of the residual component, decide on the suitability of the model used; use a suitable model to construct predictions; in Box-Jenkinson's methodology, using appropriate statistical software for time series that does not show seasonality, suggest a suitable model based on this methodology. A student who successfully completed the subject is able to: to use their expertise and skills to analyze univariate economic time series, in particular by the decomposition method; in particular within the decomposition method, the choice of the model used to justify and justify, or decide that this method is not suitable for analysis of the given time series.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination, Written examination, Student performance assessment
Assignment - active participation in seminars. Passing written test with evaluation at least 60%. Examination - oral.
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Recommended literature
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ARLT, J., ARLTOVÁ, M. Ekonomické časové řady.. Praha, 2007.
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Brebera, David a kol. Sbírka příkladů ze statistiky. Pardubice, 2014.
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Cipra, Tomáš. Finanční ekonometrie. Praha: Ekopress, 2013. ISBN 978-80-86929-93-4.
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Tsay, Ruey S.. Analysis of financial time series. Hoboken: John Wiley & Sons, 2005. ISBN 0-471-69074-0.
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