Is the research agenda for calendar anomalies “much do about nothing”?

Sproule, Robert and Gosselin, Gabriel (2023): Is the research agenda for calendar anomalies “much do about nothing”?

Abstract

Calendar anomalies are a class of financial market phenomena which links periodic, time-specific dummy variables and variations in the market price of an asset. Prior studies which report a calendar anomaly are seen by some as refutations of the efficient market hypothesis. In this paper, we estimate, test for the presence of, and find no evidence of, the day-the-week effects in the S&P 500, 2013-2023. That is, in this paper, we show that the daily-dummy variables (both individually and collectively) are independent of the S&P 500. This finding supports those who have argued that the day�the-week effects, and (by extension) all calendar anomalies, are “chimera delivered by intensive data mining” or, quite simply, such anomalies are “much ado about nothing.”

• Item Type: MPRA Paper
• Language: English
• Keywords: Efficient market hypothesis, Behavioral finance, Calendar anomalies, Day�of-the-week effects, Ordinary least-squares estimation, Newey-West (1987) standard error correction, S&P 500 Index
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates; G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading

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