Oct 19, 2019   8:54 a.m. Kristián
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Course syllabus I1-ACAR - Time series applications (FCE - WS 2019/2020)

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University: Slovak University of Technology in Bratislava
Faculty: Faculty of Civil Engineering
Course unit code: I1-ACAR
Course unit title: Time series applications
Mode of delivery, planned learning activities and teaching methods:
lecture2 hours weekly (on-site method)
laboratory/construction practice2 hours weekly (on-site method)

Credits allocated: 5
Recommended semester/trimester: Mathematical and Computational Modeling - master (compulsory), 1. semester
Level of study: 2.
Prerequisites for registration: none
Assesment methods:
Obtain at least 22 points during the semester (including 12 points from projects in exercises); obtain at least 34 points on the test (along with points during the semester at least 56 points)
Learning outcomes of the course unit:
Formulation and solution of real problems in the field of time series modelling. Acquiring fundamental knowledge about different types of non-linear time series models. After the course completion a student will be able to use a statistical test to determine, whether a linear or a non-linear model is more suitable for a given time series, and in the case of non-linear model to choose from class of non-linear regime-switching models, and finally he will be able to apply the knowledge for time series description and prediction.
Course contents:
- Tests for linearity/nonlinearity of time series.
- Nonlinear models of time series of type TAR (Threshold AutoRegressive). Nonlinear models of time series of the SETAR and STAR types (Self-Exciting Transition Autoregressive and Smooth Transition Autoregressive) and MSW-AR (Markov Switching AutoRegressive).
- Selection of an appropriate type of nonlinear model for a given time series, parameter estimation and tests of appropriateness.
- Applications of nonlinear time series models for the description and forecasting future values of the series.
Recommended or required reading:
VAN DIJK, D. -- FRANSES, P. Non-linear time series models in empirical finance. Cambridge: Cambridge University Press, 2000.
ARLTOVÁ, M. -- ARLT, J. Finanční časové řady – Vlastnosti, metody modelování, příklady a aplikace. Praha: GRADA Publ, 2003.
ARLT, J. -- ARLTOVÁ, M. Ekonomické časové řady: Vlastnosti, metody modelování, příklady a aplikace. Praha : Grada Publishing, 2007. 285 p. ISBN 978-80-247-1319-9.

Language of instruction: slovak or english
Courses evaluation:
Assessed students in total: 31

19,4 %16,1 %19,4 %22,6 %22,5 %0 %
Name of lecturer(s): doc. Ing. Tomáš Bacigál, PhD. (examiner, instructor, lecturer, person responsible for course) - slovak, english
prof. RNDr. Magdaléna Komorníková, PhD. (tutor) - slovak, english
Last modification: 21. 3. 2019
Supervisor: doc. Ing. Tomáš Bacigál, PhD. and programme supervisor

Last modification made by Ing. Marián Dubík on 03/21/2019.

Type of output: