1. COURSE DESCRIPTION:
The development of Vietnam’s economy in the volatile background of the world economy and the Industrial Revolution 4.0 has promoted economic policymakers and business administrators to pay more attention to data analysis and time series forecasting in many different fields. In particular, the advent of Vietnam’s stock market, along with the volatility of many domestic and foreign economic indicators has promoted time series forecasting to become an important activity in most fields such as economics, finance, and administration. The need for analysis and forecasting in Vietnam is on the rise because good analysis and forecasting can significantly support the formation of policies, strategies, plans as well as many daily decisions of our country’s management agencies and enterprises. Therefore, researchers, policymakers and future administrators need to be equipped with a basic knowledge of quantitative forecasting methods, statistical analysis techniques, skills using today’s common forecasting and data analysis software such as Eviews, SPSS… In addition, for students majoring in economics and business, finance and administration, the subject of Time Series Model in economic and business analysis and forecasting becomes more and more practical. Because this subject provides necessary data analysis techniques to do scientific research and graduation thesis. Students access the knowledge of the subject not only from the perspective of the fundamental knowledge of the most necessary mathematical formulas, from close real-life situations but also in the form of ‘application’, ‘practice’ on Eviews software about most common univariate and multivariate forecasting models today. The group of univariate forecasting models is divided into two types: simple and advanced. Simple models will focus on Holt, Holt-Winters, and ARIMA methods for forecasting single indicators such as sales, inventories, goods prices, and macroeconomic indicators such as GDP, CPI, interest rates, money supply. Advanced models include ARCH\ GARCH models to forecast highly fluctuating time series such as oil prices, gold prices, exchange rates, and stock prices. The multivariate model group mainly focuses on Granger causal models to forecast the relationship between economic indicators for the purpose of testing economic hypothesis into policy analysis. Because econometrics (basic) has equipped students with cross-sectional data regression models to forecast elasticity, the subject of Time Series Model in economic and business analysis and forecasting will not mention this issue in detail, but only review it to apply to forecasting. The time series model in economic and business analysis and forecasting is a highly practical, interesting, but also potentially challenging subject. Understanding the concepts and applying them to solving different exercises is very important. This requires students to spend a lot of time practicing, especially practicing on computers.
2. COURSE CONTENT
|
No. |
Chapter |
Time Allocation |
Contribution to CLO |
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|
In class |
Essays, Assignment, practices |
Guided selfed- study |
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|
Theory |
Exercise |
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|
1 |
Chapter 1. An overview of predictive analytics in economics and business |
3 |
1 |
1 |
6,5 |
1,6,7,8 |
|
2 |
Chapter 2. Building databases and analyzing time series data in economics and business |
3 |
1 |
1 |
6 |
1,6,7,8 |
|
3-4 |
Chapter 3. Some problems of probability and statistics in economics and business |
6 |
2 |
2,5 |
10 |
1,6,7,8 |
|
5-6 |
Chapter 4. Time series models in simple forecasting |
6 |
2 |
2 |
10 |
2,6,7,8 |
|
7-8 |
Chapter 5: Forecast by regression analysis |
6 |
2 |
2 |
10 |
2,6,7,8 |
|
9-10 |
Chapter 6: Predictive models ARIMA |
6 |
2 |
4 |
10 |
3,6,7,8 |
|
11-12 |
Chapter 7: ARCH/GARCH models |
6 |
2 |
5 |
15 |
3,6,7,8 |
|
13-14 |
Chapter 8: Cause and effect models |
6 |
2 |
5 |
15 |
4,5,6,7,8 |
|
15 |
Review and test |
3 |
1 |
1,4,5,6,7,8 |
||
|
Total (hours) |
30 |
15 |
22,5 |
82,5 |
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3. METHOD, FORM OF EXAMINATION
3.1. Periodic Assessment
|
Form |
Content |
Criteria |
CLO |
Proportion |
|
|
Formative |
Attendance |
Check your attendance in class. Check the level of participation in the lesson and completing all the requirements of the lecturers |
Number of times attending in class and the process of participating in the lesson |
1,2,5,6,7,8 |
10% |
|
Quiz, midterm test; Report |
.The contents of the course |
Multiple choice or essay test in about 60 minutes |
4,5,6,7,8 |
30% |
|
|
Summative |
Final test |
The contents of the course
|
60-minute Practice
|
3,4,5,6,7,8 |
60% |
|
|
|
|
Total: |
100% |
|
3.2. Criteria
* General criteria: Process assessment and integrated assessment based on student participation in learning and student completion of assessment content
* Evaluation of the process
|
No. |
Content |
Evaluation form |
Notes |
|
1 |
Attendance, discipline and mental attitude |
Scoring each attendance: each class attended and has a sense of discipline, good spirit and attitude is 0.4 point |
|
|
2 |
Oral presentation |
Completing 1 question correctly gets 10 points |
The average score of sections 2 and 3 is used to determine the addition of points to the midterm exam score |
|
3 |
Homeworks |
Completing the assigned volume of exercises will get 10 points |
* Overall evaluation
- Midterm test
- Form: Essays
- Contents: Problems using time series models in economic and business forecasting have been studied
- Criteria:
- Set problem 2 points
- Build a time series model 3 points
- Using time series for forecasting 5 points
Total: 10 points
- Final exam
- Form: Practice on computer
- Content: Problems using time series models in economic and business forecasting have been studied
– Criteria:
- Set problem 2 points
- Build a time series model 3 points
- Using time series for forecasting 3 points
- Present the result 2 points
Total: 10 points