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 |
|
|
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 |