When ? has a low value in a simple exponential smoothing forecast, which of the
ID: 422073 • Letter: W
Question
When ? has a low value in a simple exponential smoothing forecast, which of the following is true?
Less weight is placed on the previous period’s forecast and the model responds more slowly to changes in the most recent period’s demand.
Less weight is placed on the previous period’s forecast and the model responds more rapidly to changes in the most recent period’s demand.
More weight is placed on the previous period’s forecast and the model responds more slowly to changes in the most recent period’s demand.
More weight is placed on the previous period’s forecast and the model responds more rapidly to changes in the most recent period’s demand.
How does the exponential smoothing technique determine a next-period forecast?
By averaging recent historical demand to generate a forecast.
By calculating a weighted average of n-period observations using varied weights.
By identifying a causal variable, which is a predictor of demand, and using linear regression to identify the forecast equation.
By using the current period’s forecast, adjusted by a weighted difference between the current period’s actual data and the forecast.
a.Less weight is placed on the previous period’s forecast and the model responds more slowly to changes in the most recent period’s demand.
b.Less weight is placed on the previous period’s forecast and the model responds more rapidly to changes in the most recent period’s demand.
c.More weight is placed on the previous period’s forecast and the model responds more slowly to changes in the most recent period’s demand.
d.More weight is placed on the previous period’s forecast and the model responds more rapidly to changes in the most recent period’s demand.
Explanation / Answer
Formula of forecast for exponential smoothing can be written as per following :
Ft = alpha x At-1 + ( 1 – alpha ) x Ft- 1
Where,
Ft, Ft-1 = forecasts for period t and t- respectively
At-1 = actual data for period t-1
Alpha = Exponential smoothing constant
Thus when alpha is less , less weight is placed on previous period’s actual data. Since alpha is low , 1 – alpha will be high and therefore more weight is placed on previous period’s forecast .
Since less weight will be placed on actual Data on most recent period’s forecast , model will respond more slowly to changes in most recent period’s demand
ANSWER : c) MORE WEIGHT IS PLACED ON PREVIOUS PERIOD’S FORECAST AND THE MODEL RESPONDS MORE SLOWLY TO CHANGES IN THE MOST RECENT PERIOD’S DEMAND
Ft = alpha x At-1 + ( 1 – alpha) x Ft-1 = Ft-1 + alpha x ( At-1 – Ft-1 )
Ft-1 = Current period’s forecast
Ft = Future period’s forecast
Therefore , future period’s forecast is determined basis current current period’s forecast which is adjusted by a weighted difference between the current period’s actual data and the forecast
ANSWER : d ) BY USING THE CURRENT PERIOD’S FORECAST , ADJUSTED BY A WEIGHTED DIFFERENCE BETWEEN THE CURRENT PERIOD’S ACTUAL DATA AND THE FORECAST
ANSWER : c) MORE WEIGHT IS PLACED ON PREVIOUS PERIOD’S FORECAST AND THE MODEL RESPONDS MORE SLOWLY TO CHANGES IN THE MOST RECENT PERIOD’S DEMAND
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.