OVERVIEW: These techniques extrapolate past data into the future. The premise is that there is some underlying pattern in the value of the variable being forecast.
GENERAL APPROACH: To choose the appropriate technique, first do the following:
STEP 1: Date Examination - Graphical Analysis
• What is the pattern in the data?
• Try plotting the historical data on a chart
• Look for a trend line by fitting a simple line or curvilinear trend curve to the data in a freehand method.
• Look for cyclical patterns, if any, and/or major turning points
• Choose an appropriate technique. Table A2 presents different techniques and their capabilities in recognizing various patterns. For example,
• If the trend line is horizontal or reasonably stable (little or no slope), try simple versions of:
• Moving averages, or
• Exponential smoothing
If slope is evident, try
• Double moving averages, or
• Double exponential smoothing
Fluctuating patterns can be handled with:
• Decompositional models, or more complex approaches such as:
• Box-Jenkins models
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