Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/335681 
Year of Publication: 
2026
Series/Report no.: 
IWH Discussion Papers No. 1/2026
Publisher: 
Halle Institute for Economic Research (IWH), Halle (Saale)
Abstract: 
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,
Subjects: 
forecast smoothing
Smooth Sign Accuracy
time-series filtering
JEL: 
C53
E37
E66
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.