Detail publikace

Does It Pay to Follow Anomalies Research? Machine Learning Approach with International Evidence

Autor: Mgr. Martin Hronec , Tobek, Ondrej
Typ: Články v impaktovaných časopisech
Rok: 2020
Číslo: 255
ISSN / ISBN: 1386-4181
Publikováno v: Journal of Financial Markets
Místo vydání:
Klíčová slova: Anomalies, International Finance, Machine Learning, Neural Network
JEL kódy: G11, G12, G15
Citace: Tobek, O., & Hronec, M. (2020). Does it pay to follow anomalies research? machine learning approach with international evidence. Journal of Financial Markets, 100588.
Granty: GAUK no.: 910680Oceňování aktiv a výběr portfolia ve frekvenční doméně
Abstrakt: We study out-of-sample returns on 153 anomalies in equities documented in the academic literature. We show that machine learning techniques that aggregate all the anomalies into one mispricing signal are profitable around the globe and survive on a liquid universe of stocks. We investigate the value of international evidence for selection of quantitative strategies that outperform out-of-sample. Past performance of quantitative strategies in regions other than the United States does not help to pick out-of-sample winning strategies in the U.S. Past evidence from the U.S., however, captures most of the return predictability outside the U.S.

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