COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Time Series Models I * ECMZ   405 7 3 3 3

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction English
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Asst.Prof.Dr. Fela ÖZBEY
Instructors
Dr. Öğr. ÜyesiFELA ÖZBEY1. Öğretim Grup:A
 
Assistants
Goals
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.
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. Autoregressive Conditional Heteroskedasticity Models: ARCH, GARCH, TARCH, EGARCH, IGARCH, ARCH-M models. Autoregressive Regime-switching models: TAR, SETAR, ESTAR, LSTAR models.

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explains Econometric concepts
2
Acquires basic Mathematics, Statistics and Operation Research concepts
3
Equipped with the foundations of Economics, and develops Economic models
4
Describes the necessary concepts of Business
5
Models problems with Mathematics, Statistics, and Econometrics
6
Estimates the model consistently and analyzes & interprets its results
7
Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems
8
Collects, edits, and analyzes data
9
Uses a package program of Econometrics, Statistics, and Operation Research
10
Effectively works, take responsibility, and the leadership individually or as a member of a team
11
Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study
12
Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied
13
Uses Turkish and at least one other foreign language, academically and in the business context
14
Good understanding, interpretation, efficient written and oral expression of the people involved
15
Improves his/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development
16
Questions traditional approaches and their implementation while developing alternative study programs when required
17
Recognizes and implements social, scientific, and professional ethic values
18
Follows actuality, and interprets the data about economic and social events

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
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
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
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
4 Lag operator, Differencing operator. Students will be prepared by studying relevant subjects from source books according to the weekly program
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
6 White noise process, MA(q) processes, Students will be prepared by studying relevant subjects from source books according to the weekly program
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
8 Midterm Exam Students will be prepared by studying relevant subjects from source books according to the weekly program
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
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
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
12 Autoregressive Conditional Heteroskedasticity Models: TARCH, EGARCH, IGARCH, ARCH-M models Students will be prepared by studying relevant subjects from source books according to the weekly program
13 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
14 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
15 An overview Students will be prepared by studying relevant subjects from source books according to the weekly program
16-17 Final Exam Students will be prepared by studying relevant subjects from source books according to the weekly program

Recommended or Required Reading
Textbook
Additional Resources