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Review of Accounting Studies

, Volume 14, Issue 4, pp 559–586 | Cite as

Financial reporting complexity and investor underreaction to 10-K information

  • Haifeng You
  • Xiao-jun Zhang
Article

Abstract

We study the immediate and delayed market reaction to U.S. Securities and Exchange Commission (SEC) EDGAR 10-K filings. Unusual trading volumes and stock-price movements are documented during the days around the 10-K filing dates. The abnormal price movements are positively associated with future accounting profitability, indicating that 10-K reports contain useful information about future firm performance. In addition, investors’ reaction to 10-K information seems sluggish, as demonstrated by the stock-price drift during the 12-month period after 10-K filing. We find that investors’ underreaction tends to be stronger for firms with more complex 10-K reports.

Keywords

Stock price drift 10-K filing Financial reporting complexity 

JEL Classification

D8 D53 G14 M41 

Notes

Acknowledgments

This paper has benefited greatly from comments and suggestions of an anonymous referee, Patricia Dechow, Shai Levi, and Katherine Schipper (editor). The editorial assistance of Joseph Cadora and the financial support of the Center for Financial Reporting and Management at University of California are gratefully acknowledged.

References

  1. Abarbanell, J., & Bernard, V. (1992). Test of analysts’ overreaction/underreaction to earnings information as an explanation for anomalous stock price behavior. Journal of Finance, 47(3), 1181–1207.CrossRefGoogle Scholar
  2. Asthana, S., Balsam, S., & Sankaraguruswamy, S. (2004). Differential response of small versus large investors to 10-K filings on EDGAR. Accounting Review, 79, 571–589.CrossRefGoogle Scholar
  3. Barber, B., & Lyon, J. D. (1997). Detecting long-run abnormal returns: The empirical power and specification of test statistics. Journal of Financial Economics, 43, 341–372.CrossRefGoogle Scholar
  4. Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49, 307–343.CrossRefGoogle Scholar
  5. Bernard, V., & Thomas, J. (1989). Post-earnings announcement drift: Delayed price response or risk premium. Journal of Accounting Research, 27, 1–36.CrossRefGoogle Scholar
  6. Brandt, M., Kishore, R., Santa-Clara, P., & Venkatachalam, M. (2007). Earnings announcements are full of surprises. Working paper, Duke University.Google Scholar
  7. Brav, A., & Heaton, J. (2002). Competing theories of financial anomalies. Review of Financial Studies, 15, 575–606.CrossRefGoogle Scholar
  8. Carhart, M. (1997). On persistence in mutual fund performance. Journal of Finance, 52, 57–82.CrossRefGoogle Scholar
  9. Chordia, T., & Shivakumar, L. (2006). Earnings and price momentum. Journal of Financial Economics, 80, 627–656.CrossRefGoogle Scholar
  10. Dechow, P., & Dichev, I. (2002). The quality of accounting and earnings: The role of accrual estimation errors. The Accounting Review, 77, 35–59.CrossRefGoogle Scholar
  11. Easton, P., & Zmijewski, M. (1993). SEC form 10K/10Q reports and annual reports to shareholders: Reporting lags and squared market model prediction errors. Journal of Accounting Research, 31, 113–129.CrossRefGoogle Scholar
  12. Fama, E., & French, K. (1992). The cross-section of expected stock returns. Journal of Finance, 47, 427–465.CrossRefGoogle Scholar
  13. Fama, E., & French, K. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56.CrossRefGoogle Scholar
  14. Foster, T., Jenkins, D., & Vickrey, D. (1983). Additional evidence on the incremental information content of the 10-K. Journal of Business Finance and Accounting, 10(1), 57–66.CrossRefGoogle Scholar
  15. Francis, J., LaFond, R., Olsson, P., & Schipper, K. (2007). Information uncertainty and post-earnings-announcement-drift. Journal of Business Finance and Accounting, 34, 403–433.CrossRefGoogle Scholar
  16. Garfinkel, J., & Sokobin, J. (2006). Volume, opinion divergence, and returns: A study of post-earnings announcement drift. Journal of Accounting Research, 44, 85–112.CrossRefGoogle Scholar
  17. Givoly, D., & Lakonishok, J. (1980). Financial analysts’ forecast of earnings: The value to investors. Journal of Banking and Finance, 4, 221–233.CrossRefGoogle Scholar
  18. Gleason, C., & Lee, C. (2003). Analyst forecast revisions and market price discovery. The Accounting Review, 78, 193–225.CrossRefGoogle Scholar
  19. Griffin, P. (2003). Got information? Investor response to form 10-K and form 10-Q EDGAR filings. Review of Accounting Studies, 8, 433–466.CrossRefGoogle Scholar
  20. Hirshleifer, D. (2001). Investor psychology and asset pricing. Journal of Finance, 56, 1533–1598.CrossRefGoogle Scholar
  21. Hirst, E., & Hopkins, P. (1998). Comprehensive income reporting and analysts’ valuation judgments. Journal of Accounting Research, 36(Supplement), 47–75.CrossRefGoogle Scholar
  22. Hong, H., & Stein, J. (1999). A unified theory of underreaction, momentum trading and overreaction in asset markets. Journal of Finance, 54, 2143–2184.CrossRefGoogle Scholar
  23. Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48, 65–91.CrossRefGoogle Scholar
  24. Jiang, G., Lee, C., & Zhang, Y. (2005). Information uncertainty and expected returns. Review of Accounting Studies, 10, 185–221.CrossRefGoogle Scholar
  25. Li, F. (2006). Do stock market investors understand the risk sentiment of corporate annual reports? Working paper, University of Michigan.Google Scholar
  26. Livnat, J., & Mendenhall, R. (2006). Comparing the post-earnings-announcement drift for surprises calculated from analyst and time-series forecasts. Journal of Accounting Research, 44, 177–205.CrossRefGoogle Scholar
  27. Mitchell, M., & Stafford, E. (2000). Managerial decisions and long-term stock price performance. Journal of Business, 73, 287–329.CrossRefGoogle Scholar
  28. McEwen, R., & Hunton, J. (1999). Is analyst forecast accuracy associated with accounting information use? Accounting Horizons, 13(1), 83–96.CrossRefGoogle Scholar
  29. Petersen, M. (2006) Estimating standard errors in finance panel data sets: Comparing approaches. Northwestern University Working Paper.Google Scholar
  30. Plumlee, M. (2003). The effect of information complexity on analysts’ use of that information. The Accounting Review, 78, 275–296.CrossRefGoogle Scholar
  31. Qi, D., Wu, W., & Haw, I. (2000). The incremental information content of SEC 10-K reports filed under the EDGAR system. Journal of Accounting Auditing and Finance, 15, 25–46.Google Scholar
  32. Rangan, S., & Sloan, R. (1998). Implications of the integral approach to quarterly reporting for the post-earnings announcement drift. The Accounting Review, 73, 353–371.Google Scholar
  33. Sloan, R. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings? The Accounting Review, 71, 289–315.Google Scholar
  34. Stice, E. (1991). The market reaction to 10-K and 10-Q filings and to subsequent the Wall Street Journal earnings announcements. The Accounting Review, 66, 23–41.Google Scholar
  35. Stickel, S. (1991). Common stock returns surrounding earnings forecast revisions: More puzzling evidence. The Accounting Review, 66(April), 402–416.Google Scholar
  36. Womack, K. (1996). Do brokerage analysts’ recommendations have investment value? Journal of Finance, 51(March), 137–167.CrossRefGoogle Scholar
  37. Zhang, F. (2006). Information uncertainty and stock returns. Journal of Finance, 61, 105–137.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Barclays Global InvestorsSan FranciscoUSA
  2. 2.Haas School of BusinessUniversity of CaliforniaBerkeleyUSA

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