CBE Forecasting 4

Question 1

Which of the following best describes a stationary time series?

Accepted Answer

A series with constant mean, variance, and autocovariance over time

Answer

Stationarity requires that statistical properties—mean, variance, and autocovariance—do not depend on the point in time at which the series is observed.

Question 2

A company's sales forecasts show that actual sales are always below the forecast. This suggests the forecasts are:

Accepted Answer

Overestimates (positively biased)

Answer

If actual sales consistently fall below forecasts, the model is systematically predicting too high—a positive bias in the forecast.

Question 3

Holt's double exponential smoothing extends simple exponential smoothing by also smoothing:

Accepted Answer

The trend component

Answer

Holt's method adds a second smoothing equation for the trend, allowing forecasts to project a changing level rather than a flat one.

Question 4

Theil's U statistic is used to evaluate a forecast by comparing it to:

Accepted Answer

A random walk (naïve) forecast

Answer

Theil's U compares the root mean squared error of a model forecast to that of a naïve no-change forecast; U < 1 means the model outperforms the naïve benchmark.

Question 5

In regression forecasting, multicollinearity primarily causes problems by:

Accepted Answer

Making individual coefficient estimates unstable and hard to interpret

Answer

Multicollinearity inflates standard errors of correlated predictors, making coefficients unreliable even if overall model fit is high.

(CBE) Certified Business Economist Practice Test

(CBE) Certified Business Economist Practice Test

CBE Forecasting 4