Using the Best Buy revenue data:
a) Fit the sales data using the Holt-Winters Multiplicative Seasonal model.
b) Find the optimal smoothing constants (?, ?, and ?) using the Solver. Set the Solver to minimize the MSE, and be sure to constrain the smoothing parameters to be between 0 and 1. What are the optimal values?
c) Using the model that you have created, forecast quarterly revenues for the next year.
d) According to FactSet, analysts are forecasting the following revenues for the next year. How do your numbers compare?
Alpha 0.4600
Beta 0.0621
Gamma 0.8864
MSE 303,469
MAPE 3.69%
a) See the fit at left.
b) The optimal parameters are:
a = 0.4600, b = 0.0621, g = 0.8864
c) See forecasts in F33:F36
d) Our model is forecasting lower sales in each quarter than analysts expectations, though generally closer to expectations than the additive model.
e) The multiplicative has a lower MSE and also lower MAPE, indicating a better fit.
FactSet Sales Estimates for BBY as of 30 July 2017
8,656.24 97.14%
8,989.16 97.19%
14,261.90 92.92%
8,536.60 96.94%
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