Question

For general exponential smoothing forecasts, if the parameter Alpha =1, the resulting forecast is called:

1 - Naïve
2 - Erroneous
3 - Unstable
4 - Stable

Answer 1

When the parameter Alpha is set to 1 in general exponential smoothing forecasts, the resulting forecast is called Naïve, which means that the forecast for the next period is simply equal to the actual value of the current period.

Step-by-step explanation:

When the parameter Alpha is set to 1 in general exponential smoothing forecasts, the resulting forecast is called Naïve. This means that the forecast for the next period is simply equal to the actual value of the current period.

This is because an Alpha value of 1 eliminates the effect of any previous forecast errors and focuses entirely on the most recent observation. Therefore, the forecast will always be the same as the actual value, resulting in a stable forecast.

Answer 2

For general exponential smoothing forecasts, if the parameter Alpha =1, the resulting forecast is called Naïve. Therefore, the correct option is 1 - Naïve.

Step-by-step explanation:

In exponential smoothing forecasts, the parameter Alpha determines the weight given to the most recent observation. When Alpha equals 1, it signifies that only the most recent observation is considered in forecasting the future values. This results in what is known as a Naïve forecast.

A Naïve forecast method assumes that the future value will be the same as the most recent observed value. In this scenario, the forecast doesn't incorporate any historical data or trend, making it simplistic and solely reliant on the latest observation. When Alpha equals 1, the forecast essentially mirrors the most recent value, indicating a lack of adjustment or smoothing for the data.

Such a forecast might be suitable for short-term predictions when abrupt changes or sudden fluctuations are expected in the data, but it's generally not advisable for longer-term forecasts or scenarios where historical trends significantly affect future outcomes. Therefore, an Alpha value of 1 in exponential smoothing leads to a Naïve forecast, which lacks complexity or adjustment based on historical patterns, rendering it basic and solely reliant on the most recent data point. Therefore, the correct option is 1 - Naïve.