Graduate Education Institute · Islamic Economics and Finance (English) · Master
Course Objective
The aim of this course is to introduce students to application of advanced econometric techniques for time series analysis, such as cointegration (VAR/VECM) and Wavelets. Statistical softwares Microfit and R will be used throughout this course. By the end of this course, the students are expected to produce quality project papers using real financial data.
Course Content
This is a practical course on econometric methods designed to enable students to carry out their own research projects. The course covers the following time series techniques: a) VAR/VECM analysis including unit root test, VAR lag order selection, cointegration tests, long run structural modeling, vector error correction model, vector decomposition, impulse response function, and persistence profile; and b) Wavelets analysis including wavelet variances, correlations, cross-correlations, and wavelet coherence.
Course Learning Outcomes
- Use multivariate time-series models such as VAR/VECM and ARDL to analyse time series data.
- Develop fundamental research skills (such as data collection, data processing, and model estimation and interpretation) in applied time series analysis.
- Use existing R packages for analysing time series data.
- Run and interpret time-series models.
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 16 | 3 | 48 |
| Out of Class Study Period | 15 | 4 | 60 |
| Midterm | 1 | 7 | 7 |
| Quiz | 0 | 0 | 0 |
| Assignment | 1 | 25 | 25 |
| Practice | 0 | 0 | 0 |
| Final | 1 | 20 | 20 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | The Basics of Regression Analysis | Notes 1 |
| 2 | Introduction to Time Series Analysis | Notes 1 |
| 3 | Unit Root Tests, VAR Lag Order Selection, Cointegration Analysis | Notes 2 |
| 4 | Long Run Structural Modelling | Notes 2 |
| 5 | Vector Error Correction Model | Notes 2 |
| 6 | Variance Decomposition | Notes 2 |
| 7 | Impulse Response and Persistence Profile | Notes 2 |
| 8 | Midterm Exam | Midterm Exam |
| 9 | Autoregressive Distributed Lag (ARDL) | Notes 3 |
| 10 | Introduction to Wavelet Analysis | Notes 4 |
| 11 | Wavelet Variance and Correlations | Notes 4 |
| 12 | Wavelet Cross-Correlations | Notes 4 |
| 13 | Wavelet Coherence | Notes 4 |
| 14 | Project Presentations | Project Presentations |
| 15 | Revision | Revision |
| 16 | Final Exam | Final Exam |