Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/335681 
Erscheinungsjahr: 
2026
Schriftenreihe/Nr.: 
IWH Discussion Papers No. 1/2026
Verlag: 
Halle Institute for Economic Research (IWH), Halle (Saale)
Zusammenfassung: 
Forecasts that minimize mean squared forecast error (MSE) often exhibit excessive volatility, limiting their practical applicability. We address this accuracy smoothness trade-off by introducing a Multivariate Smooth Sign Accuracy (M-SSA) framework, which extracts smoothed components from leading indicators to enhance the signal-to-noise ratio and control the forecast volatility and timing. Applied to quarterly German GDP growth, our method yields smoothed forecasts that can improve forecasting accuracy, particularly over medium-term horizons. We find that while smoother forecasts tend to lag slightly around turning points, this can be offset by adjusting the forecast horizon. These findings highlight the practicality of the M-SSA framework for both forecasters and policymakers,
Schlagwörter: 
forecast smoothing
Smooth Sign Accuracy
time-series filtering
JEL: 
C53
E37
E66
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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