With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

a. smoothing constant.
b. moving average.
c. regression coefficient.
d. mean forecast error.

Step-by-step explanation: A smoothing constant is forecasting model, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value.

This smoothing constant determines how the historical time series values are weighted and it must have a value between 0 and 1.

There are three smoothing constants and they are: alpha, betta and gamma.

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With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the a. smoothing constant. b. moving average. c. regression coefficient. d. mean forecast error.

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With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the

a. smoothing constant.
b. moving average.
c. regression coefficient.
d. mean forecast error.