General Information
Target Audience
Students interested in understanding and using regression-based forecasting techniques applicable to Finance, Marketing, Strategy and Economics.
Format
12 weekly sessions
Course Mission
The course provides an introduction to forecasting techniques based on time-series methods (ARIMA) and single-equation econometric (‘regression’) equations. We will also touch more briefly on multiple-equation econometric models and volatility forecasting (‘ARCH’ techniques). The forecasting applications considered span demand and price forecasting and financial variables. The course is “hands-on”, requiring use of the toolkit of techniques in Econometric Views (EVIEWS) – an econometrics package widely used in the forecasting community. Relatively little time is devoted to non-econometric forecasting techniques.
Evaluation and Grade Distribution
| Component | Due Date | Weight |
|---|---|---|
| Midterm Test #1 | Week 6 (in class) | 30% |
| Midterm Test #2 | Week 11 (in class) | 30% |
| Term Paper | End of term | 40% |
Required Resources
- Required: EViews – Student Version 9.0 or 10.0, Quantitative Micro Software. Downloadable; the minimal student version is a free download.
- Recommended: R.S. Pindyck and D.L. Rubinfeld (PR), Econometric Models & Economic Forecasts (virtually any edition). New York: McGraw Hill (This or any equivalent econometrics text is recommended; PR and several other econometric/forecasting texts will be placed on reserve in the Rotman library)