Economics and Finance(English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

FNCE428

Course Name:

Time Series Analysis

Course Semester:

Spring

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	6

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Department Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Öğr.Gör. MUBARIZ HASANOV

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:

The purpose of this course is to equip students with an understanding of econometric analysis. Discussions will range from inferential statistics to econometric model building, estimation, and interpretation. Among topics covered are: the nature of regression analysis, classical linear regression models, model classification and estimation, interval estimation, hypothesis tests, and interpretation of estimated relationships.

Course Content:

Introduction to time series analysis; concepts and methods of time series analysis and their applications; seasonality in time series; stationarity; unit root tests; autoregressive (AR) models; moving average (MA) models; ARIMA models; autocorrelation and partial autocorrelation functions; model specification tests; model estimation techniques; multipliers; statistical inference and forecasting.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) • Appreciate the important features that describe a time series, and perform analyses and computations on series.
2) • Understand the definitions of the important stochastic processes used in time series modeling, and the properties of those models.
3) Appreciate and apply key concepts of estimation and forecasting in a time series context.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	• Introduction to the course • Review of the course syllabus content • Introduction and explanation of the course lessons • Methodology of time series analysis • Overview of econometrics and mathematics • Course syllabus content • Basics of statistics	reading
2)	• Time series models • Difference equations • Solution by iteration and solutions of difference equations Lecture, problem solving and discussion
3)	• Solving homogeneous difference equations • Particular solutions for deterministic processes • The method of undetermined coefficients • Lag operators
4)	• Stochastic difference equation models • Stationarity of time series • ARMA models • Stationarity restrictions for ARMA models
5)	• Autocorrelation (ACF) and partial autocorrelation functions (PACF) • ACF and PACF of stationary series • Box-Jenkins model selection • Seasonality • Parameter instability and structural changes
6)	• Economic time series • Volatility models, ARCH and GARCH models • ARCM-M model • Additional properties of GARCH models
7)	• Maximum likelihood (ML) estimators • ML estimation of GARCH models • Generalization of GARCH models • Volatility impulse responses
8)	• Midterm exam • Stochastic and deterministic trends in time series • De-trending series • Unit roots and regression residuals • Monte-Carlo methods, simulations
9)	• Testing stationarity • ADF and PP unit root tests • KPSS tests of stationarity • Power and size properties of stationarity tests • Structural changes
10)	• Introduction to multi-equation models • Distributed lag models • ARDL models • Limits to structural multivariate estimation
11)	• Vector autoregressive (VAR) models • Identification and estimation • Impulse-response functions • Cholesky decomposition • Testing hypothesis
12)	• Structural VAR models • Identification of structural models • Structural decomposition • Blanchard-Quah decomposition
13)	• Linear combinations of integrated variables • Common trends, cointegration • Cointegration and error correction • Testing for cointegration
14)	• Other tests for cointegration • Characteristic equations, rank, characteristic roots • Johansen-Juselius methodology • Error-correction models • Cointegration tests based on ARDL models Lecture, demonstration with a statistical software, case study and discussion
15)	• Final Exam

Sources

Course Notes / Textbooks:	Applied Econometric Time Series, Fourth Edition
References:	Enders, 2014, Wiley, ISBN: 978-1-118-80856-6Authors Walte

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3
Program Outcomes
1) Explain the advances in the area of economics and finance within the framework of scientific methodology, theories and models.
2) Employ the appropriate tools and analytical techniques to collect and analyze quantitative and qualitative data in the related areas, interpret results and propose solutions.
3) Explain the evolution of financial markets and institutions in a historical context and define how they operate.
4) Recognise the basic principles and regulations in the financial sector.
5) Discover and create entrepreneurial opportunities to successfully establish and develop their own ventures.
6) Recognise, interpret and discuss the current economic issues both at the national and global levels.
7) Have the English proficiency in following and interpreting the developments in the areas of economics and finance and in conducting written and oral communication.
8) Express the role of international capital markets in the global economy; accordingly define the concept of risk in terms of measurement and management.
9) Identify standards of personal, professional, social and business ethics, evaluate the ethical implications of various practices in the related areas, and be aware the importance of ethical behavior in adding value to the society.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Explain the advances in the area of economics and finance within the framework of scientific methodology, theories and models.	5
2)	Employ the appropriate tools and analytical techniques to collect and analyze quantitative and qualitative data in the related areas, interpret results and propose solutions.	5
3)	Explain the evolution of financial markets and institutions in a historical context and define how they operate.	1
4)	Recognise the basic principles and regulations in the financial sector.	2
5)	Discover and create entrepreneurial opportunities to successfully establish and develop their own ventures.	2
6)	Recognise, interpret and discuss the current economic issues both at the national and global levels.	4
7)	Have the English proficiency in following and interpreting the developments in the areas of economics and finance and in conducting written and oral communication.	3
8)	Express the role of international capital markets in the global economy; accordingly define the concept of risk in terms of measurement and management.	2
9)	Identify standards of personal, professional, social and business ethics, evaluate the ethical implications of various practices in the related areas, and be aware the importance of ethical behavior in adding value to the society.	1

Learning Activity and Teaching Methods

Peer Review
Expression
Brainstorming/ Six tihnking hats
Individual study and homework
Reading

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Oral Examination
Individual Project
Group project
Presentation

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Grading

Activities	Number of Activities	Duration (Hours)	Workload
Midterms	40	0	0
Final	60	0	0
Total Workload			0