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Forecasting
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===Naïve approach=== Naïve forecasts are the most cost-effective forecasting model, and provide a benchmark against which more sophisticated models can be compared. This forecasting method is only suitable for time series [[data]].<ref name="otexts.org" /> Using the naïve approach, forecasts are produced that are equal to the last observed value. This method works quite well for economic and financial time series, which often have patterns that are difficult to reliably and accurately predict.<ref name="otexts.org"/> If the time series is believed to have seasonality, the seasonal naïve approach may be more appropriate where the forecasts are equal to the value from last season. In time series notation: :<math>\hat{y}_{T+h|T} = y_T </math>
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