Which statement describes Time Series forecasting methods within quantitative forecasting?

• A. They rely on causal factors to forecast demand
• B. They use qualitative judgments
• C. They base forecasts on historical data and patterns
• D. They are exclusively used for financial forecasting

Answer: (C)

Time series forecasting relies on patterns found in past data to predict future values. It assumes that historical behavior—such as overall trends, seasonal patterns, cycles, and random variation—will continue in the future. By analyzing these patterns in the data itself, the forecast is generated without needing explicit external causal drivers. That’s why describing time series methods as basing forecasts on historical data and patterns is the best fit.

The other ideas don’t match time series: using causal factors means building forecasts from relationships with other variables (drivers), which is not the defining feature of time series. Relying on qualitative judgments involves subjective opinions rather than data-driven patterns. And time series techniques are applied across many domains, not just financial forecasting.