Example compute a 3 period moving average forecast

• Notes
• 15
• 86% (74) 64 out of 74 people found this document helpful

This preview shows page 6 - 9 out of 15 pages.

Example: Compute a 3-period moving average forecast given demand for shopping carts for the last five periods. Period Demand 1 42 2 40 3 43 4 40 5 41 t
6
DBH3 * A possible disadvantage is that all values in the average are weighted equally. For example, in a 10-period moving average, each value has weight of 1/10. Hence, the oldest value has the same weight as the most recent value. Decreasing the number of values in the average increases in weight of more recent values. Example 2: Given the following data: Period No. of complaints 1 60 2 65 3 55 4 58 5 64 (a) Use naive approach to make the forecast for the next period. (b) Compute a 3-period moving average forecast. Weighted moving average: A weighted average is similar to the moving average, except that it assigns more weight to the most recent values in a time series. For example, the most recent value might be assigned a value of 0.4, the next most recent value a weight of 0.3, the next after that a weight of 0.2, and the next after that a weight of 0.1. Note that the sum of the weights is 1.0. The weighted moving average can be computed by the following formula 1 1 2 2 ) 2 ( 2 ) 1 ( 1 ...... t t n t n n t n n t n t A w A w A w A w A w F The advantage of a weighted average over a simple moving average is that the weighted average is more reflective of the most recent occurrences. However, the choice of the weight is somewhat arbitrary and generally involves the use of trial and error to find a suitable weighting scheme. Example 1: Given the demand for shopping carts for the last five periods. Period Demand 1 42 2 40 3 43 4 40 5 41 (a) Compute a weighted moving average forecast using a weight of 0.4 for the most recent period, 0.3 for the next most recent, 0.2 for the next, and the next after that a weight of 0.1. (b) If the actual demand for period 6 is 39, forecast demand for period 7 using the same weights as in part (a). 7
DBH3
Example 2: Given the following data: Period No. of complaints 1 60 2 65 3 55 4 58 5 64 (a) Compute a weighted moving average forecast using a weight of 0.4 for the most
• • • 