Information Package / Course Catalogue
Time Series Analysis
Course Code: ECN536
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

The aim of this course is to provide students with theoretical and practical knowledge about time series analysis techniques.

Course Content

Introduction to time series and basic concepts, graphs and indicators, statistical properties and stationarity, time series models, model estimation, model identification and diagnostic analysis, causality analysis in time series...

Name of Lecturer(s)
Lec. Elif Meryem YURDAKUL ŞİPAL
Learning Outcomes
1.Have knowledge about the basic concepts of time series analysis.
2.Develop the ability to construct time series graphs and identify important patterns such as trends, seasonality and cycles.
3.Develop the ability to predict future values using time series models.
4.Develop skills in understanding, analyzing and forecasting time series data.
5.Learn the basic methods needed to effectively analyze economic data and forecast future trends, seasonality and cycles.
Recommended or Required Reading
1.Cem KADILAR & Hatice Öncel ÇEKİM - Zaman Serileri Analizine Giriş, Seçkin Yayınları.
2.Rob J. HYNDMAN & George ATHANASOPOULOS - Forcasting: Principles and Practice, OTexts.
3.Erol EĞRİOĞLU & Eren BAŞ - Zaman Serileri ve Öngörü Yöntemleri (R Uygulamalı), Nobel Akademik Yayıncılık.
4.Robert H. SHUMWAY & David S. STOFFER - Time Series Analysis and Its Applications with R Examples, Springer.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to time series and basic concepts
Week 2 - Theoretical
Graphs and indicators of time series
Week 3 - Theoretical
Statistical properties of time series and stationarity
Week 4 - Theoretical
Time series models: AR models
Week 5 - Theoretical
Time series models: MA models
Week 6 - Theoretical
Time series models: ARIMA models
Week 7 - Theoretical
Seasonal time series models
Week 8 - Theoretical
Seasonal time series models
Week 9 - Intermediate Exam
Midterm Examination
Week 10 - Theoretical
Model estimation
Week 11 - Theoretical
Model identification and diagnostic analysis
Week 12 - Theoretical
Causality analysis in time series
Week 13 - Theoretical
Models of change in time series: Structural breaks
Week 14 - Theoretical
ARCH and GARCH models in time series models
Week 15 - Theoretical
Panel data time series analysis
Week 16 - Final Exam
Final Examination
Week 17 - Final Exam
Final Examination
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140114
Lecture - Practice140228
Individual Work140228
Midterm Examination123225
Final Examination128230
TOTAL WORKLOAD (hours)125
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
OÇ-1
2
2
4
3
3
3
2
OÇ-2
2
2
5
4
3
3
3
OÇ-3
2
2
5
4
3
3
2
OÇ-4
2
2
4
3
2
2
3
OÇ-5
2
2
5
4
3
3
2
Adnan Menderes University - Information Package / Course Catalogue
2026