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Information
| Code | IEM709 |
| Name | Time Series Analysis I |
| Term | 2022-2023 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi FELA ÖZBEY |
Course Goal / Objective
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. Analysis of time series: time series analysis in time domain, time series analysis in frequency domain. Components of economic time series. Difference equations: Stability of difference equations, Impulse-response function. Expectations of processes, stationarity, and ergodicity. Trend stationary and difference stationary processes. White noise process, MA(q) processes, AR(p) processes, Random walk process, ARIMA(p,d,q) processes. Invertibility for MA(q) 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: ADF, PP, KPSS, HEGY tests. Autoregressive Conditional Heteroskedasticity Models: ARCH, GARCH, TARCH, GARCH, IGARCH, ARCH-M models. Autoregressive Regime-switching models: TAR, SETAR, ESTAR, LSTAR models.
Course Precondition
None
Resources
James Douglas Hamilton, (1994) Time Series Analysis, Princeton University Press, ISBN: 9780691042893 Gebhard Kirchgässner, Jürgen Wolters (2007), Introduction to Modern Time Series Analysis, Springer, ISBN: 978-3-540-73291-4 Burak Güriş (2020) R Uygulamalı Doğrusal Olmayan Zaman Serileri Analizi, Der Yayınları ISBN: 978-975-353-628-8
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 the concept of stochastic process. |
| LO02 | Defines the concept of time series. |
| LO03 | List the components of economic time series. |
| LO04 | Solves the difference equations by recursive substitution. |
| LO05 | Determines whether a difference equation is stable. |
| LO06 | Calculates the dynamic multipliers of a difference equation. |
| LO07 | Expresses the lags of the variables with the lag operator. |
| LO08 | Uses the differencing operator. |
| LO09 | Recognizes the white noise process. |
| LO10 | Recognizes ARMA processes. |
| LO11 | Recognizes the random walk process. |
| LO12 | Calculates the mean of a process. |
| LO13 | Calculates the autocovariances of a process. |
| LO14 | Calculates the autocorrealtions of a process. |
| LO15 | Calculates the partial autocorrealtions of a process. |
| LO16 | Tests the stationarity of a series. |
| LO17 | Models a time series by using the Box-Jenkins approach. |
| LO18 | Models conditional variance with ARCH family models. |
| LO19 | Tests whether there is a regime-switching an AR model. |
| LO20 | Chooses the most appropriate Autoregressive Regime-switching model for a time series. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explains contemporary concepts about Econometrics, Statistics, and Operation Research | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research | 5 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences | 5 |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | 5 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 5 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 5 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | 3 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | 3 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Searches for new approaches and methods to solve problems being faced | 3 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | 3 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Collects/analyzes data in a purposeful way | 5 |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | 3 |
| PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops solutions for organizations using Econometrics, Statistics, and Operation Research | 3 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research | 5 |
| PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study | 3 |
| PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | |
| PLO18 | 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 | |
| PLO19 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | 3 |
| PLO20 | 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 of first-order difference equations, Impulse-response functions of first-order difference equations. | 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 pth-order difference equation by recursive substitution, stability of pth-order difference equations, Impulse-response functions of pth-order difference equations. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 4 | Lag operator, Differencing operator. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Problem Çözme |
| 5 | 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 |
| 6 | 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 |
| 7 | AR(p) processes, 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 |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | Invertibility for MA(q) processes. 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 |
| 10 | 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 |
| 11 | Autoregressive Conditional Heteroskedasticity Models: ARCH and GARCH models. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 12 | Autoregressive Conditional Heteroskedasticity Models: TARCH, EGARCH 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 | Autoregressive Conditional Heteroskedasticity Models: IGARCH, ARCH-M models. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 14 | Autoregressive Regime-switching models: TAR, SETAR, ESTAR, LSTAR models. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 15 | Autoregressive Regime-switching models: Choosing the most appropriate model. | Students will be prepared by studying relevant subjects from source books according to the weekly program | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Problem Çözme |
| 16 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Term Exams | 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 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||