Chapter 9 Forecasting Techniques
Instructions: Please submit your work in one single Excel file with one tab/worksheet for each problem.
Forecasting Models for Stationary Time Series
1. (40 points) The Excel file Closing Stock Prices provides data for four stocks and the Dow Jones Industrial Average over a one-month period.
a. Develop a spreadsheet model for forecasting each of the stock prices using a simple two-period and three-period moving average. Compute MAD to determine which model is better?
b. Develop a spreadsheet model for forecasting each of the stock prices using simple exponential smoothing with a smoothing constant of 0.1 and 0.5. Compute MAD to determine which model is better?
Forecasting Models for Time Series with a Linear Trend
2. (20 points) Consider the data in the Excel file Consumer Price Index.
a. Use double exponential smoothing to find forecasts for the next two years.
b. Use simple linear regression to find forecasts for the next two years.
Forecasting Time Series with Seasonality
3. (20 points) Develop a multiple regression model with categorical variables that incorporate seasonality for forecasting for the data in the Excel file Coal Consumption.
Regression Forecasting with Causal Variables
4. (20 points) Data in the Excel file Microprocessor Data shows the demand for one type of chip used in industrial equipment from a small manufacturer.
a. Construct a chart of the data. What appears to happen when a new chip is introduced?
b. Develop a causal regression model to forecast demand that includes both time and the introduction of a new chip as explanatory variables.
