Assume there is no trend or seasonality in the sales data in Table 1. Suppose you use
Question:
Assume there is no trend or seasonality in the sales data in Table 1. Suppose you use exponential smoothing with a smoothing constant of 10% (i.e., ???? = 0.1). Assume that you begin forecasting at the end of January, using January sales of 308 as your initial estimate of the level (i.e., y1 = y1 = 308).
What is the forecast made at the end of February for the month of May (i.e., y5|2)? (hint: recall, when there is no systematic variability for multiple-step ahead forecast, is the same as one step ahead.
Period | Sales |
January | 308 |
February | 343 |
March | 369 |
April | 403 |
May | 433 |
June | 459 |
Table 1: Monthly Sales
B. You are a manager of a sportswear shopping store and you want to forecast sales of swimsuits for August 2018 using a four-period weighted moving average WMA(4). The sales for April, May, June, and July are:
Month | Actual Sales |
April | 300 |
May | 400 |
June | 500 |
July | 600 |
You set the weights for April, May, June, and July at 0.1, 0.2, 0.3, and 0.4, respectively. You found that WMA(4) is (show your calculations
Quantitative Analysis for Management
ISBN: 978-0132149112
11th Edition
Authors: Barry render, Ralph m. stair, Michael e. Hanna