Which statement best describes the impact of forecast horizon on accuracy?

Which statement best describes the impact of forecast horizon on accuracy?

• A. Accuracy is unaffected by horizon
• B. Accuracy improves with longer horizons
• C. The horizon length does not matter when data quality is high
• D. Forecast accuracy declines the further out you try to predict

Answer: (D)

Forecast horizon is about how far into the future you’re predicting. As you extend that horizon, uncertainty grows. The further out you forecast, the more potential events, changes in trends, or shifts in drivers can occur, and you’re relying on patterns that may not hold. Errors can also compound because you often base longer-range forecasts on shorter-range projections, spreading the uncertainty downward through the forecast. That combination means predictions become less accurate the farther out you go. So the statement that forecast accuracy declines the further out you try to predict best describes the effect.

Forecast horizon is about how far into the future you’re predicting. As you extend that horizon, uncertainty grows. The further out you forecast, the more potential events, changes in trends, or shifts in drivers can occur, and you’re relying on patterns that may not hold. Errors can also compound because you often base longer-range forecasts on shorter-range projections, spreading the uncertainty downward through the forecast. That combination means predictions become less accurate the farther out you go. So the statement that forecast accuracy declines the further out you try to predict best describes the effect.