Stock market anomalies: An extreme bounds analysis

SSRN Electronic Journal(2023)

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摘要
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.
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关键词
Data-mining,Market efficiency,Model uncertainty
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