Stock returns and investors' mood: Good day sunshine or spurious correlation?
Jae Kim ()
International Review of Financial Analysis, 2017, vol. 52, issue C, 94-103
This paper critically evaluates the significant weather effect on stock return reported in two seminal studies of investors' mood on stock market. It is found that their research design of maximizing statistical power by pooling as many data points as possible is statistically flawed, with a consequence that the test is severely biased against the null hypothesis of no effect. Coupled with small effect size estimates and test statistics inflated by massive sample sizes, this strongly suggests spurious statistical significance as an outcome of Type I error. The alternatives to the p-value criterion for statistical significance soundly support the null hypothesis of no weather effect. As an application, the effect of daily sunspot numbers on stock return is examined. Under the same research design as that of a seminal study, the number of sunspots is found to be highly statistically significant although its economic impact on stock return is negligible.
Keywords: Anomaly; Data mining; Market efficiency; Sunspot numbers; Weather effect (search for similar items in EconPapers)
JEL-codes: G12 G14 (search for similar items in EconPapers)
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Working Paper: Stock Returns and Investors’ Mood: Good Day Sunshine or Spurious Correlation? (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:52:y:2017:i:c:p:94-103
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