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Time-Series Behavior Of Quarterly Earnings - Preliminary Evidence

Citations

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Cited by:

  1. Lawrence D. Brown & Mark E. Zmijewski, 1987. "The effect of labor strikes on security analysts' forecast superiority and on the association between risk†adjusted stock returns and unexpected earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 4(1), pages 61-75, September.
  2. Ball, Ray & Bartov, Eli, 1996. "How naive is the stock market's use of earnings information?," Journal of Accounting and Economics, Elsevier, vol. 21(3), pages 319-337, June.
  3. John Affleck†Graves & Larry R. Davis & Richard R. Mendenhall, 1990. "Forecasts of earnings per share: Possible sources of analyst superiority and bias," Contemporary Accounting Research, John Wiley & Sons, vol. 6(2), pages 501-517, March.
  4. He, Shuoyuan & Narayanamoorthy, Ganapathi (Gans), 2020. "Earnings acceleration and stock returns," Journal of Accounting and Economics, Elsevier, vol. 69(1).
  5. Sen, Kaustav, 2009. "Earnings surprise and sophisticated investor preferences in India," Journal of Contemporary Accounting and Economics, Elsevier, vol. 5(1), pages 1-19.
  6. Jose M. Carabias, 2018. "The real-time information content of macroeconomic news: implications for firm-level earnings expectations," Review of Accounting Studies, Springer, vol. 23(1), pages 136-166, March.
  7. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
  8. Josef Fink, 2020. "A Review of the Post-Earnings-Announcement Drift," Working Paper Series, Social and Economic Sciences 2020-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
  9. Xinyue Cui & Zhaoyu Xu & Yue Zhou, 2020. "Using Machine Learning to Forecast Future Earnings," Papers 2005.13995, arXiv.org.
  10. Rä‚Zvan Popa, 2020. "Improving Earnings Predictions With Neural Network Models," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 26, pages 77-96, December.
  11. Pagach, Donald P. & Warr, Richard S., 2020. "Analysts versus time-series forecasts of quarterly earnings: A maintained hypothesis revisited," Advances in accounting, Elsevier, vol. 51(C).
  12. Edwards, John Richard & Dean, Graeme & Clarke, Frank & Wolnizer, Peter, 2013. "Accounting academic elites: The tale of ARIA," Accounting, Organizations and Society, Elsevier, vol. 38(5), pages 365-381.
  13. Jumming Hsu & Xu-Ming Wang & Chunchi Wu, 1998. "The Role of Earnings Information in Corporate Dividend Decisions," Management Science, INFORMS, vol. 44(12-Part-2), pages 173-191, December.
  14. O. M. Joy & C. P. Jones, 1979. "Earnings Reports And Market Efficiencies: An Analysis Of The Contrary Evidence," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 2(1), pages 51-63, March.
  15. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
  16. Zana Grigaliuniene, 2013. "Time-Series Models Forecasting Performance In The Baltic Stock Market," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 4(1).
  17. Dechow, Patricia & Ge, Weili & Schrand, Catherine, 2010. "Understanding earnings quality: A review of the proxies, their determinants and their consequences," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 344-401, December.
  18. Carabias, Jose M., 2018. "The real-time information content of macroeconomic news: implications for firm-level earnings expectations," LSE Research Online Documents on Economics 86399, London School of Economics and Political Science, LSE Library.
  19. Sanghyuk Byun & Kristin C. Roland, 2022. "Quarterly earnings thresholds: Making the case for prior quarter earnings," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(5-6), pages 690-716, May.
  20. Richard M. Morton, 1998. "The Incremental Informativeness of Stock Prices for Future Accounting Earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 15(1), pages 57-81, March.
  21. Callen, Jeffrey L. & Kwan, Clarence C. Y. & Yip, Patrick C. Y. & Yuan, Yufei, 1996. "Neural network forecasting of quarterly accounting earnings," International Journal of Forecasting, Elsevier, vol. 12(4), pages 475-482, December.
  22. Stanimir Markov & Ane Tamayo, 2006. "Predictability in Financial Analyst Forecast Errors: Learning or Irrationality?," Journal of Accounting Research, Wiley Blackwell, vol. 44(4), pages 725-761, September.
  23. Carnes, Thomas A. & Jones, Jefferson P. & Biggart, Timothy B. & Barker, Katherine J., 2003. "Just-in-time inventory systems innovation and the predictability of earnings," International Journal of Forecasting, Elsevier, vol. 19(4), pages 743-749.
  24. James C. Mckeown & Hossein Shalchi, 1988. "A comparative examination of the time†series properties and predictive ability of annual historical cost and general price level adjusted earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 4(2), pages 485-507, March.
  25. repec:mth:ijafr8:v:9:y:2019:i:1:p:74-88 is not listed on IDEAS
  26. Hannu, Schadewitz, 1997. "Financial and nonfinancial information in interim reports: Determinants and implications," MPRA Paper 44292, University Library of Munich, Germany.
  27. Linnainmaa, Juhani T. & Torous, Walter & Yae, James, 2016. "Reading the tea leaves: Model uncertainty, robust forecasts, and the autocorrelation of analysts’ forecast errors," Journal of Financial Economics, Elsevier, vol. 122(1), pages 42-64.
  28. Sean Shun Cao & Ganapathi S. Narayanamoorthy, 2012. "Earnings Volatility, Post–Earnings Announcement Drift, and Trading Frictions," Journal of Accounting Research, Wiley Blackwell, vol. 50(1), pages 41-74, March.
  29. Qing Cao & Mark Parry & Karyl Leggio, 2011. "The three-factor model and artificial neural networks: predicting stock price movement in China," Annals of Operations Research, Springer, vol. 185(1), pages 25-44, May.
  30. Lorek, Kenneth S., 2014. "A critical assessment of the time-series literature in accounting pertaining to quarterly accounting numbers," Advances in accounting, Elsevier, vol. 30(2), pages 315-321.
  31. Syouching Lai & Hungchih Li, 2006. "The predictive power of quarterly earnings per share based on time series and artificial intelligence model," Applied Financial Economics, Taylor & Francis Journals, vol. 16(18), pages 1375-1388.
  32. Brown, Lawrence D., 1996. "Influential accounting articles, individuals, Ph.D. granting institutions and faculties: A citational analysis," Accounting, Organizations and Society, Elsevier, vol. 21(7-8), pages 723-754.
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