Question

Which of the following values of the smoothing constant would cause exponential smoothing to respond the slowest to forecast errors (i.e., less error would be factored into subsequent forecasts)?

a. 0.1
b. 0.4
c. 0.2
d. 0.3

Answer 1

Answer:b

Explanation:

Exponential smoothing is a time series forecasting approach for univariate data that can be extended to assist data with a systematic trend or seasonal element.

Forecast for next month is given by

`F_t=F_(t-1)+\alpha (D_(t-1)-F_(t-1))`

where

`F_t=Forecast\ for\ next\ month`

`F_(t-1)=Forecast\ Predicted\ for\ this\ month`

`D_(t-1)=Demand\ for\ this\ month`

`\alpha =smoothing\ constant`

If value of
`\alpha` approaches to 1 then it can be said that it is very responsive

and it is close to 0 then it is stable.

So correct answer is 0.4 i.e. option b