A moving average forecast is defined as:

• A. The last observed value
• B. The average of all prior observations
• C. The average of the last M observations
• D. The weighted mean of prior observations

Answer: (C)

Moving average forecasting relies on smoothing recent data by averaging a fixed number of the most recent observations. The forecast for the next period is simply the average of the last M observations, with each of those points given equal weight. This approach reduces random noise while preserving short-term trends, and the window size M controls how responsive the forecast is: a smaller M tracks recent changes more closely, while a larger M smooths more. Using just the last observed value would be a naïve forecast and ignores all other recent data, whereas averaging all prior observations would continually change as more data accumulate and wouldn’t reflect a fixed, short-term horizon. A weighted mean would assign different importance to past points, which is a different method from the standard moving average.