International Financial Markets
Autoregressive (AR) models are statistical tools used for forecasting time series data, where the current value of a series is regressed on its previous values. These models assume that past values have a direct influence on future values, making them particularly useful in predicting trends and patterns in financial markets. By analyzing historical data, AR models help in understanding how exchange rates might evolve based on their own past behavior.
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