Stock market anomalies: An extreme bounds analysis

Jae H. Kim and Abul Shamsuddin

International Review of Financial Analysis, 2023, vol. 90, issue C

Abstract: We conduct the extreme bounds analysis (EBA) to evaluate the robustness or fragility of a range of stock market anomalies, using U.S. daily data from 1960 to 2023. The EBA is a large-scale sensitivity analysis, able to isolate the effects of potential data-mining or p-hacking under model uncertainty. The anomalies covered include the effects of Halloween, sports event, seasonal affective disorder, weather, political cycle, daylight saving, and lunar phase. We find that the empirical evidence for the anomalies is highly fragile, in terms of effect size estimates and their statistical significance.

Keywords: Data-mining; Market efficiency; Model uncertainty (search for similar items in EconPapers)
JEL-codes: C52 G12 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:90:y:2023:i:c:s1057521923003575

DOI: 10.1016/j.irfa.2023.102841

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