SubjectsSubjects(version: 945)
Course, academic year 2023/2024
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Advanced Course in Time Series - NMST605
Title: Časové řady pro pokročilé
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Zuzana Prášková, CSc.
Class: Pravděp. a statistika, ekonometrie a fin. mat.
Classification: Mathematics > Probability and Statistics
Is interchangeable with: NSTP152, NSTP151
Annotation -
Last update: T_KPMS (07.05.2014)
Selected topics in time series for PhD students: limit theorems for serially dependent observations, asymptotic properties of estimations. Spectral analysis of time series, periodogram and estimation of spectral density. Vector time series, stationarity, correlations and spectrum, cointegration. Nonstationary and nonlinear time series, financial time series.
Aim of the course -
Last update: T_KPMS (06.05.2014)

The aim of the subject is to provide information on advanced theoretical results and new developments in time series analysis. Further, the aim is to school the students in theoretical procedures and methods of research in this field.

Course completion requirements -
Last update: doc. RNDr. Zuzana Prášková, CSc. (29.10.2019)

oral exam

Literature -
Last update: doc. RNDr. Zuzana Prášková, CSc. (29.10.2019)

Hamilton J. D. (1994): Time Series Analysis, Princeton Univ. Press, Princeton

Lütkepohl H. (2005): New Introduction to Multiple Time Series Analysis. Springer, Berlin.

Brockwell, P. J., Davis, R.A. (2009): Time Series: Theory and Methods. 2nd print. of 1991, Chapters 7-13

Wei W. W. S. (2006): Time Series Analysis. Univariate and multivariate methods. Addison-Wesley, 2nd ed.

Tsay, R. S: (2010): Analysis of Financial Time Series, Wiley, Hoboken, 3rd ed.

Teaching methods -
Last update: T_KPMS (06.05.2014)

Lecture.

Requirements to the exam -
Last update: doc. RNDr. Zuzana Prášková, CSc. (29.10.2019)

submitting a report on numerical solution of a given problem concerning the study subject

Syllabus -
Last update: T_KPMS (07.05.2014)

Limit theorems for serially dependent observations, estimation of basic characteristics, asymptotic properties. Spectral analysis of time series, periodogram and estimation of spectral density. Vector time series, stationarity, correlations and spectrum, cointegration. Nonlinear and nonstationary time series, financial time series.

 
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