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Holiday effect on stock price reactions to analyst recommendation revisions

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Abstract

The study explores the holiday effect on stock price reactions to analyst recommendation revisions and on post-recommendation price drifts. Based on the Mood Maintenance Hypothesis and on the literature documenting lower stock trading activity before holidays, I hypothesize that if a recommendation revision is issued before a holiday, then investors striving to maintain their positive pre-holiday mood, may be less willing to make influential trading decisions, and therefore, may underreact to the recommendation revision, leading to stronger post-recommendation price drift. Analyzing a large sample of analyst recommendation revisions, I document that, compared to “regular” recommendation revisions, pre-holiday recommendation revisions are followed by: (i) significantly weaker event-day stock price reactions, and (ii) significantly more pronounced post-event price drifts, whose magnitude increases over longer post-event periods (up to 6 months). Both effects are more pronounced for small and more volatile stocks and remain robust after accounting for additional company- (size, market model beta, historical volatility) and event-specific (number of recommendation categories changed in the revision, analyst experience) factors.

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Notes

  1. The two datasets are merged based on either CUSIP or exchange tickers combined with the requirement that the period these identifiers are used in the datasets overlap.

  2. In order to test if the holiday effect on stock price reactions to analyst recommendation revisions is not predominantly driven by any one of the public holidays, I have repeated my analysis by consecutively omitting one of the nine public holidays at a time (that is, excluding from my analysis the recommendation revisions, which took place prior to this specific holiday). The results (available upon request from the author) are homogeneous (and similar to those reported in “Results description” section for the whole list of holidays), indicating that all the public holidays have exerted approximately similar effects on the way investors treated recommendation revisions.

  3. Alternatively, I calculate ARs using Market-Adjusted Returns (MAR)—return differences from the market index, and the Fama-French three-factor model. The results (available upon request from the author) remain qualitatively similar to those reported in “Results description” section.

  4. I choose to analyze post-recommendation periods of one, three and six months following, for example, Loh (2010) and Gavriilidis et al. (2016).

  5. It should be noted that pre-holiday recommendation revisions make up slightly less than 3% of the study's working sample. Still, 2168 (2416) pre-holiday recommendation upgrades (downgrades) accumulated over the 15-year sampling period are sufficient for obtaining statistically significant results.

  6. I have repeated the tests, whose results are reported in “Holiday effect on post-recommendation stock returns within different stock groups” and “Multifactor analysis” sections, for the post-event time windows employed in Table 4. The holiday effect on CAR (2, 5) remained weak and nonsignificant, so that the results for CAR (6, 21), CAR (6, 63) and CAR (6, 126) were very similar to those for CAR (2, 21), CAR (2, 63) and CAR (2, 126), respectively, as reported in Tables 5, 6 and 7. The detailed results are available upon request from the author.

  7. The results for medium capitalization stocks indicate that these stocks are less influenced by the holiday effect (on both event-day ARs and post-event drifts) than low capitalization stocks, and more influenced by the holiday effect than high capitalization stocks. The detailed results are available upon request from the author. Overall, the results demonstrate that the holiday effect on stock price reactions to recommendation revisions decreases with market capitalization.

  8. The sample partition approach by both market capitalization and historical stock volatility is similar to the one employed by Kliger and Kudryavtsev (2010).

  9. The results for medium volatility stocks indicate that these stocks are less influenced by the holiday effect (on both event-day ARs and post-event drifts) than high volatility stocks, and more influenced by the holiday effect than low volatility stocks. The detailed results are available upon request from the author. Overall, the results demonstrate that the holiday effect on stock price reactions to recommendation revisions increases with historical stock volatility.

  10. I have also performed the analysis of event-day and post-event ARs for three subsamples partitioned by the CAPM stock beta calculated over Days − 251 to − 1. In line with Baker and Wurgler (2006), I have documented that the holiday effect on stock price reactions to recommendation revisions (expressed both in weaker event-day price reactions and higher post-event price drifts) increases with stock beta. The detailed results are available upon request from the author.

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Authors and Affiliations

  1. The Economics and Management Department, The Max Stern Yezreel Valley Academic College, 19300, Emek Yezreel, Israel

    Andrey Kudryavtsev

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  1. Andrey Kudryavtsev
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Correspondence to Andrey Kudryavtsev.

Appendix

Appendix

See Tables 1, 2, 3, 4, 5, 6 and 7.

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Kudryavtsev, A. Holiday effect on stock price reactions to analyst recommendation revisions. J Asset Manag 19, 507–521 (2018). https://doi.org/10.1057/s41260-018-0095-6

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