Heinisch, KatjaVan Norden, SimonWildi, MarcLeibniz-Institut für Wirtschaftsforschung Halle2026-02-182026https://epflicht.bibliothek.uni-halle.de/handle/123456789/1176321949782697urn:nbn:de:gbv:3:2-123456789-1176323Forecasts 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, especially in settings where forecast revisions or policy adjustments are costly.1 Online-Ressource (III, 31 Seiten, Seite A1-A5, 1,01 MB) : Diagrammeenghttp://rightsstatements.org/vocab/InC/1.0/330