EKMZ405 Time Series Models I

3 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Code EKMZ405
Name Time Series Models I
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 3 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi FELA ÖZBEY


Course Goal

The aim of this course is to give the students a good theoretical and empirical understanding of statistical methods used in univariate time series analysis.

Course Content

Stochastic process and time series concepts. The aims of time series analyses in time domain and frequency domain. Components of economic time series. Difference equations: Solving a difference equation by recursive substitution; Roots of difference equations, Stability of difference equations, Impulse-response function, Cumulative impulse-response function, Long-run response. Expectations of processes, stationarity, and ergodicity. Trend stationary and difference stationary processes. White noise process: Prpoerties of the white noise process; MA(q) processes: Mean of MA(q) processes, Variance of MA(q) processes, Autocovariances of MA(q) processes; AR(p) processes: Mean of AR(p) processes, Variance of AR(p) processes, Autocovariance of AR(p) processes, Stationarity of AR(p) processes; Integrated processes: Random walk process, ARIMA(p,d,q) processes. Invertibility for MA(q) processes. Stationarity and invertibility of ARMA processes; Overparametrization of the ARMA models. The Box-Jenkins method of ARIMA model identification. Autocorrelation and partian autocorrelation functions of AR, MA, and ARMA processes. Unit root tests.

Course Precondition

None

Resources

Mehmet Çınar , Mustafa Sevüktekin (2014), Ekonometrik Zaman Serileri Analizi: EViews Uygulamalı, Dora Yayıncılık James Douglas Hamilton, (1994) Time Series Analysis, Princeton University Press, ISBN: 9780691042893

Notes

Gebhard Kirchgässner, Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Springer, ISBN: 978-3-540-73291-4


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Defines time series concept.
LO02 Solves difference equations by recursive substitution.
LO03 Checks whether a difference equation satisfies stability conditions.
LO04 Calcuates dynamic multipliers (impulse-response functions).
LO05 Calcuates cumulative dynamic multipliers (cumulative impulse-response functions).
LO06 Calcuates the long-run response to a shock.
LO07 Distinguishes between trend stationary and difference stationary process.
LO08 Lists statistical properties of the White noise process.
LO09 Checks whether a stochastic process satisfies stationarity conditions.
LO10 Checks whether a stochastic process satisfies invertibility conditions.
LO11 Frees an overparameterized ARMA model from overparameterization.
LO12 Applies appropriate filters to time series.
LO13 Calculates the mean of a given process.
LO14 Calculates the variance of a given process.
LO15 Calculates autocovariances of a given process.
LO16 Calculates autocorrelations of a given process.
LO17 Calculates partial autocorrelations of a given process.
LO18 Performs unit root tests.
LO19 Chooses the most appropriate model for the underlying univariate time series.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the basic concepts and theorems in the fields of Econometrics, Statistics and Operations research 5
PLO02 Bilgi - Kuramsal, Olgusal Acquires basic Mathematics, Statistics and Operation Research concepts 5
PLO03 Bilgi - Kuramsal, Olgusal Describes the necessary concepts of Business
PLO04 Beceriler - Bilişsel, Uygulamalı Equipped with the foundations of Economics, and develops Economic models 2
PLO05 Beceriler - Bilişsel, Uygulamalı Models problems with Mathematics, Statistics, and Econometrics 5
PLO06 Beceriler - Bilişsel, Uygulamalı Has the ability to analyze/interpret at the conceptual level to develop solutions to problems 5
PLO07 Beceriler - Bilişsel, Uygulamalı Collects/analyses data 5
PLO08 Beceriler - Bilişsel, Uygulamalı Interprets the results analyzed with the model 5
PLO09 Beceriler - Bilişsel, Uygulamalı Combines the information obtained from different sources within the framework of academic rules in a field which does not research
PLO10 Beceriler - Bilişsel, Uygulamalı It develops traditional approaches, practices and methods into new working methods when it deems necessary 2
PLO11 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team
PLO12 Yetkinlikler - Öğrenme Yetkinliği In addition to herself/himself professional development, constantly improves in scientific, cultural, artistic and social fields in line with interests and abilities
PLO13 Yetkinlikler - Öğrenme Yetkinliği Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in its field. 2
PLO14 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research
PLO15 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses Turkish and at least one other foreign language, academically and in the business context 2
PLO16 Yetkinlikler - İletişim ve Sosyal Yetkinlik Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form
PLO17 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on current economic and social issues 3
PLO18 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values


Week Plan

Week Topic Preparation Methods
1 Stochastic process and time series concepts. Analysis of time series: time series analysis in time domain, time series analysis in frequency domain. Components of economic time series. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
2 First-order difference equations: Definition, Solving a difference equation by recursive substitution, stability offirst-order difference equations, Impulse-response function. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
3 pth-order difference equations: Definition, Solving a difference equation by recursive substitution, stability offirst-order difference equations, Impulse-response function. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
4 pth-order difference equations: stability conditions and impulse-response functions of p-order difference equations having complex roots. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
5 Lag operator, Differencing operator. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
6 Expectations of processes, stationarity, and ergodicity. Trend stationary and difference stationary processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
7 White noise process, MA(q) processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
8 Midterm Exam Ölçme Yöntemleri:
Yazılı Sınav
9 AR(p) processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
10 Random walk process, ARIMA(p,d,q) processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
11 Invertibility for MA(q) processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
12 Overparametrization of the ARMA models. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
13 The Box-Jenkins method of ARIMA model identification. Autocorrelation and partian autocorrelation functions of AR, MA, and ARMA processes. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
14 Unit root tests Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
15 An overview Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
16 Final Exam Ölçme Yöntemleri:
Yazılı Sınav
17 Final Exam Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 6 6
Final Exam 1 10 10
Total Workload (Hour) 86
Total Workload / 25 (h) 3,44
ECTS 3 ECTS