ARMA Models

ARMA models, which stand for Autoregressive Moving Average models, are statistical tools used to analyze and forecast time series data, such as stock prices or weather patterns. The "autoregressive" part indicates that the model uses past values of the data to predict future values, while the "moving average" component uses past forecast errors to improve the predictions. Together, these elements help capture the underlying patterns and trends in the data, enabling more accurate forecasts based on historical information. They are widely used in economics, finance, and other fields requiring data analysis over time.