TÜRKÇE
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Information
| Code | ECMZ405 |
| Name | Time Series Models I |
| Term | 2022-2023 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi FELA ÖZBEY |
| Course Instructor |
Dr. Öğr. Üyesi FELA ÖZBEY
(A Group)
(Ins. in Charge)
|
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. 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
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 | Bilgi - Kuramsal, Olgusal | 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 follows the current developments in the field / constantly renews itself | 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 | 4 |
| 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 | Mid-Term 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 | 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 | 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 | ||