All Days Are Not Created Equal: Understanding Momentum by Learning to Weight Past ReturnsOpen Access

Beckmeyer, Heiner; Wiedemann, Timo

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

By flexibly weighting the information contained in past realized returns, we construct a momentum strategy that outperforms and subsumes the performance of traditional stock momentum. The strategy performs well in crises and continues to work in the most recent decades. We show that the way past returns are weighted is in line with the strategy exploiting an underreaction to the information contained in realized returns, but also investigate alternative behavioral and risk-based explanations. We find that the response to earnings announcements, market-wide jumps and large individual returns realized in the formation period are most informative about future stock returns.

Details zur Publikation

FachzeitschriftJournal of Banking and Finance
Jahrgang / Bandnr. / Volume181
StatusVeröffentlicht
Veröffentlichungsjahr2025
Sprache, in der die Publikation verfasst istEnglisch
DOI10.1016/j.jbankfin.2025.107565
StichwörterMomentum, Machine learning, Big data, Anomalies

Autor*innen der Universität Münster

Beckmeyer, Heiner
Professur für Derivate und Financial Engineering (Prof. Branger)
Wiedemann, Timo
Professur für Derivate und Financial Engineering (Prof. Branger)