Moving averages are useful in forecasting stationary time series as they tend to smooth out random variations.

Question

Quizplus · Accepted Answer

Moving averages are commonly used as a smoothing technique to remove random noise from time series data. This process helps to identify underlying patterns and trends that may be useful in forecasting future values. However, moving averages may not be as effective in forecasting non-stationary time series, where there may be trends or patterns that change over time.

Moving Averages Are Useful in Forecasting Stationary Time Series as They