Are There Sectoral Anomalies Too? The Pitfalls of Unreported Multiple Hypothesis Testing and a Simple Solution

  • Michael Greenstone
  • Paul Oyer


The recent emphasis on sector-specific investment strategies has led to the emergence of industry-specific calendar anomalies, notably the technology sector “summer swoon”. A standard t-test implies that these price movements provide arbitrage opportunities. However, this test fails to account for the many tests that may have preceded the swoon’s discovery. We propose the use of the Bonferroni correction to account for this unreported testing. Its application reverses the conclusions about the summer swoon and finds no evidence of calendar-based price patterns in any other sector. We also use the Bonferroni correction to revisit previously documented, market-wide, anomalies. Conclusions about the most widely cited anomalies (e.g., the January effect) are unchanged, but evidence for some other “anomalies” is substantially weakened. Our results emphasize that in evaluating a proposed anomaly, sectoral in nature or otherwise, it is crucial to account for the hypotheses that were likely to have been tested but not reported.

calendar anomalies technology stocks data mining Bonferroni correction 


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  1. Ahmed, S.W., “Issues Arising in the Application of Bonferroni Procedures in Federal Surveys.” American Statistical Association Proceedings Survey Research Methods Section 344-349, (1991).Google Scholar
  2. Ariel, R.A., “A Monthly Effect in Stock Returns.” Journal of Financial Economics 18, 161-174, (1987).Google Scholar
  3. Black, F., Estimating Expected Returns, New York: Goldman Sachs, 1992.Google Scholar
  4. Black, “Noise.” Journal of Finance 41, 529-543, (1986).Google Scholar
  5. Dimson, E. and Marsh P., “Murphy's Law and Market Anomalies.” The Journal of Portfolio Management 25, 53-69, (1999).Google Scholar
  6. Fama, E.F, “Market Ef®ciency, Long-term Returns, and Behavioral Finance.” Journal of Financial Economics 49, 283-306, (1998).Google Scholar
  7. French, K., “Stock Returns and the Weekend Effect.” Journal of Financial Economics 8, 55-69, (1980).Google Scholar
  8. Keim, D.B., “Size-related Anomalies and Stock Return Seasonality: Further Empirical Evidence.” Journal of Financial Economics 12, 13-32, (1983).Google Scholar
  9. Lo, AW. and A.C. McKinley, “Data-Snooping Biases in Tests of Financial Asset Pricing Models.” Review of Financial Studies 3, 431-467, (1990).Google Scholar
  10. Marcus, A.J., “The Magellan Fund and Market Efficiency.” The Journal of Portfolio Management 17, 85-88, (1990).Google Scholar
  11. Miller, R.G. Jr, Simultaneous Statistical Inference, New York: Springer-Verlag, 1981.Google Scholar
  12. Richardson, M., “Temporary Components of Stock Prices: A Skeptic's View.” Journal of Business and Economic Statistics 11, 199-207, (1993).Google Scholar
  13. Shaffer, J.P., “Multiple Hypothesis Testing.” Annual Review of Psychology 46, 561-584, (1995).Google Scholar
  14. Sullivan, R., A. Timmermann, and H. White, “Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns.” University of California. San Diego Department of Economics Discussion Paper 98-16, (1998).Google Scholar
  15. Sullivan, R., A. Timmermann, and H. White, “Data-Snooping, Technical Trading Rule Performance, and the Bootstrap.” Journal of Finance 54, 1647-1691, (1999).Google Scholar
  16. Thaler, R.H., “Calendar Effects in the Stock Market” in Richard H. Thaler, The Winner's Curse, Princeton: Princeton University Press, (1992).Google Scholar
  17. Wang, K., Y. Li, and J. Erickson, “A New Look at the Monday Effect.” Journal of Finance 52, 2171-2186, (1997).Google Scholar
  18. White, H., “A Reality Check for Data Snooping.” Working paper, 1997.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Michael Greenstone
    • 1
  • Paul Oyer
    • 2
  1. 1.Robert Wood Johnson Foundation ScholarUniversity of California-BerkeleyBerkeley
  2. 2.J.L. Kellogg Graduate School of ManagementNorthwestern UniversityEvanston

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