Forecasting Flashcards

When the smoothing parameter α in exponential smoothing is set close to 1, the forecast:

Answer: Places almost all weight on the most recent observation

An α near 1 means the new forecast is almost entirely the most recent actual value, making the model very responsive to the latest data.

Autocorrelation in forecast residuals most directly indicates:

Answer: The model has not fully captured the data's time-series structure

Autocorrelated residuals signal that predictable patterns remain unexploited by the model, implying the forecasting specification is incomplete.

A leading indicator is best defined as a variable that:

Answer: Tends to change before the economy as a whole

Leading indicators peak and trough before the overall economy, making them useful for anticipating future economic turning points.

In an ARIMA(p,d,q) model, the 'd' parameter represents:

Answer: The order of differencing applied to achieve stationarity

Differencing (d times) removes unit roots and non-stationarity so that the ARIMA model's AR and MA components can be applied reliably.

Forecast bias is present when:

Answer: The mean forecast error is consistently positive or negative

Bias means the forecast systematically over- or under-predicts; an unbiased forecast has errors that average to zero over time.

Which scenario calls for multiplicative rather than additive decomposition?

Answer: Seasonal variation grows proportionally with the trend level

Multiplicative decomposition is appropriate when seasonal fluctuations fan out as the trend level rises, because the seasonal effect scales with the series.

The Akaike Information Criterion (AIC) is used in forecasting primarily to:

Answer: Compare models by balancing fit and parsimony

AIC penalizes model complexity, rewarding good fit while discouraging over-parameterization, making it a standard tool for model selection.