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retailers. Forecasting the demand for cash on a granular level is crucial in the process to keep logistics costs low, while … being resilient to demand or supply shocks. Whereas to date, cash forecasts with central banks mostly comprise structural … implementation of a forecasting process at the Bundesbank, we benchmark statistical and machine learning methods on demand and supply …
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This paper analyses the forecasting performance of monetary policy reaction functions using U.S. Federal Reserve's Greenbook real-time data. The results indicate that artificial neural networks are able to predict the nominal interest rate better than linear and nonlinearTaylor rule models as...
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Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...
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