Arbeitspapier
Does peer-reviewed research help predict stock returns?
Mining 29,000 accounting ratios for t-statistics over 2.0 leads to cross-sectional predictability similar to the peer review process. For both methods, about 50% of predictability remains after the original sample periods. Data mining generates other features of peer review including the rise in returns as original sample periods end, the speed of post-sample decay, and themes like investment, issuance, and accruals. Predictors supported by peer-reviewed risk explanations underperform data mining. Similarly, the relationship between modeling rigor and post-sample returns is negative. Our results suggest peer review systematically mislabels mispricing as risk, though only 18% of predictors are attributed to risk.
- Sprache
-
Englisch
- Erschienen in
-
Series: CFR Working Paper ; No. 24-02
- Klassifikation
-
Wirtschaft
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Andrew Y.
Lopez-Lira, Alejandro
Zimmermann, Tom
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Cologne, Centre for Financial Research (CFR)
- (wo)
-
Cologne
- (wann)
-
2024
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Chen, Andrew Y.
- Lopez-Lira, Alejandro
- Zimmermann, Tom
- University of Cologne, Centre for Financial Research (CFR)
Entstanden
- 2024
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