A Moving Average Model is a statistical tool used in time series analysis to smooth out short-term fluctuations and highlight longer-term trends. It works by averaging a set number of past data points to predict future values. This model is particularly useful in fields like finance and economics, where it helps analysts understand trends in stock prices or economic indicators. In a Moving Average Model, the "moving" aspect refers to the way the average is recalculated as new data becomes available. Common types include the Simple Moving Average (SMA) and the Exponential Moving Average (EMA), each with different methods for weighting past observations.