We propose a method to correct estimates from historical linked data for bias arising from type-I error--"false matches." We estimate the rate of false matching from the disagreement rate in characteristics that should agree across the two linked datasets. Combined with an understanding of the...

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers' results. For the 161 characteristics that were clearly significant in...

Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and...

We provide data and code that successfully reproduces nearly all cross-sectional stock return predictors. Unlike most metastudies, we carefully examine the original papers to determine whether our predictability tests should produce t-stats above 1.96. For the 180 predictors that were clearly...

Daten und ihre ökonomischen Auswirkungen durchdringen alle Bereiche der Wirtschaft. Die sogenannte Datenökonomie ist kein neuer Wirtschaftszweig, sondern eher eine ständige Herausforderung für alle Unternehmen, im Rahmen einer neuen Dimension der Wertschöpfung wettbewerbsfähig und...

Daten und ihre ökonomischen Auswirkungen durchdringen alle Bereiche der Wirtschaft. Die sogenannte Datenökonomie ist kein neuer Wirtschaftszweig, sondern eher eine ständige Herausforderung für alle Unternehmen, im Rahmen einer neuen Dimension der Wertschöpfung wettbewerbsfähig und...

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Unlike most metastudies, we carefully examine the original papers to determine whether our predictability tests should produce t-stats above 1.96. For the 180 predictors that were clearly...