Instructor
|
Roumen
Vesselinov, PhD
Department of Statistics
Course webpage www.stat.sc.edu/~vesselin/stat520.html
|
Office LeConte
200-C
Phone (803) 777-5074
E-mail: roumen@sc.edu |
| Purpose |
This
is a course in applied time series analysis and forecasting. Students
will have hands-on experience with applied analysis based on actual
time series from economics,
business cycle, finance, management, and science.
Offered on alternating Spring semesters. |
| Prerequisites |
STAT
516 or MGSC 391; or students must have some understanding of regression
type models.
Talk
to the
instructor to get a permission to register for the course. |
| Textbook |
Introduction
to Time Series and Forecasting,
2nd edition, by P.J. Brockwell and R.A. Davis, Springer, 2002. |
| Software |
ITSM2000 - Comes free with the
textbook with no exparation date. Specialized
software for time series analysis and forecasting. User
friendly with pull down menus and good graphical capabilities. |
| Grading
|
Final grade is
weighted average:
Exam 1 (25%), Exam 2 (25%), Final (30%), Project
(10%), HW
(10%). |
Grading (%):
A 93; B+ 88; B
83; C+ 78; C 70;
D+ 67; D 60; F
<60;
|
Distance
Ed.
|
Courses
Video
|
| Topics* |
1.
Box-Jenkins ARIMA
2. Seasonal ARIMA models
3. Unit roots
4. Cointegration
5. Granger causality
6. Vector Autoregression (VAR) models
7. Vector Error Correction (VEC) models
8. Intervention analysis and structural change
9. State-Space models |
10.
Markov regime-switching model
11.
ARCH models
12. GARCH models
13. Smoothing
14. Forecasting techniques
- add-factor approach
- simultaneous equations models
15. Simulations |