Autoregressive Moving Average

An Autoregressive Moving Average (ARMA) model is a statistical tool used to analyze and forecast time series data, such as stock prices or weather patterns. It combines two concepts: autoregression, which predicts current values based on past observations, and moving averages, which use past errors or shocks to improve predictions. Essentially, ARMA models leverage the relationships within past data points and errors to identify patterns and make accurate forecasts. They are widely used in fields where understanding and predicting sequential data is crucial, balancing past values and residuals to capture the underlying data dynamics.