An Autoregressive (AR) model is a statistical framework used in time series analysis that predicts future values of a variable based on its own past values. In financial markets, autoregressive models are used to forecast stock prices, volatility, and economic indicators like GDP growth and inflation. The AR model assumes that past behaviour of a series contains useful information about its future trajectory. More advanced models, such as ARIMA (Autoregressive Integrated Moving Average), combine autoregressive components with moving averages for enhanced forecasting accuracy.
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