VARMA (Vector Autoregressive Moving Average)

VARMA (Vector Autoregressive Moving Average) is a statistical model used to analyze and forecast multiple interconnected time series data, such as economic indicators or stock prices. It captures how current values depend on past values (autoregression) and past forecast errors (moving average), considering the relationships among several variables simultaneously. This model helps identify complex dynamic patterns and predict future trends by understanding both the historical influence and interconnectedness of multiple data streams, making it valuable for decision-making in finance, economics, and engineering.