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Earnings Autocorrelation and the Post-Earnings-Announcement Drift: Experimental Evidence

Published online by Cambridge University Press:  24 July 2023

Josef Fink ,
Stefan Palan Open the ORCID record for Stefan Palan [Opens in a new window]  and
Erik Theissen Open the ORCID record for Erik Theissen [Opens in a new window]
Josef Fink
Affiliation:
McKinsey and Company Vienna [email protected]
Stefan Palan*
Affiliation:
University of Graz Institute of Banking and Finance
Erik Theissen
Affiliation:
University of Mannheim Finance area [email protected]
*
[email protected] (corresponding author)
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Abstract

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Post-earnings-announcement drift (PEAD) is one of the most solidly documented asset pricing anomalies. We use the controlled conditions of the experimental lab to investigate whether earnings autocorrelation is the driving cause of this anomaly. We observe PEAD in settings with uncorrelated and correlated earnings surprises, confirming that earnings autocorrelation is not a necessary condition for PEAD. Instead, it acts as an accelerator: PEAD is stronger when earnings surprises are correlated. We further show that market prices underadjust to fundamental value changes, and that trading strategies can profitably exploit the PEAD.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 59 , Issue 6 , September 2024 , pp. 2799 - 2837
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank Jennifer Conrad and Elena Asparouhova—respectively, the editor and referee of the current version—as well as two anonymous reviewers of a previous submission, Ray Ball, Te Bao, Bruno Biais, Peter Bossaerts, Jürgen Brandner, Peiran Jiao, Alexander Kempf, Michael Kirchler, Olaf Korn, Christian Leuz, Roland Mestel, Kerstin Mitterbacher, Stefan Nagel, Thomas Post, Ryan Riordan, Andrea Schertler, Thomas Stöckl, Martin Weber, Yilong Xu, and the participants of the 2019 Austrian Working Group on Banking and Finance workshop, the 2020 virtual finance workshop at Radboud University, the 2021 Experimental Finance conference, and seminar participants at the UC Louvain, the University of Cologne, the University of Graz, the University of Maastricht, and the University of Mannheim for valuable comments. We also thank Adele Theiler for research assistance. This work was supported by the Austrian Science Fund FWF (project no. P32124-G27). The research project was approved by the IRB of the University of Graz (case ID 39/57/63). The authors have no conflicts of interest to disclose.

References

Ackert, L. F.; Church, B. K.; and Qi, L.. “An Experimental Examination of Portfolio Choice.” Review of Finance, 20 (2016), 1427–1447.CrossRefGoogle Scholar
Andries, M.; Bianchi, M.; Huynh, K. K.; and Pouget, S.. “Return Predictability, Expectations, and Investment: Experimental Evidence.” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3710466 (2022).Google Scholar
Asparouhova, E.; Hertzel, M.; and Lemmon, M.. “Inference from Streaks in Random Outcomes: Experimental Evidence on Beliefs in Regime Shifting and the Law of Small Numbers.” Management Science, 55 (2009), 1766–1782.CrossRefGoogle Scholar
Assenza, T.; Bao, T.; Hommes, C.; and Massaro, D.. “Experiments on Expectations in Macroeconomics and Finance.” Research in Experimental Economics, 17 (2014), 11–70.CrossRefGoogle Scholar
Ball, R. “The Earnings-Price Anomaly.” Journal of Accounting and Economics, 15 (1992), 319–345.CrossRefGoogle Scholar
Ball, R., and Bartov, E.. “How Naive is the Stock Market’s Use of Earnings Information?” Journal of Accounting and Economics, 21 (1996), 319–337.CrossRefGoogle Scholar
Ball, R., and Brown, P.. “An Empirical Evaluation of Accounting Income Numbers.” Journal of Accounting Research, 6 (1968), 159–178.CrossRefGoogle Scholar
Ball, R.; Kothari, S.; and Watts, R.. “The Economic Determinants of the Relation Between Earnings Changes and Stock Returns.” Accounting Review, 68 (1993), 622–638.Google Scholar
Bathke, A.; Morton, R.; Notbohm, M.; and Zhang, T.. “Objective Estimation Versus Subjective Perceptions of Earnings Patterns and Post-Earnings-Announcement Drift.” Accounting and Finance, 54 (2014), 305–334.CrossRefGoogle Scholar
Bathke, A. W. Jr; Lorek, K. S.; and Willinger, G. L.. “The Security Market’s Reaction to Firms’ Quarterly Earnings Evidencing Varying Degrees of Autocorrelation.” Advances in Accounting, 22 (2006), 29–43.CrossRefGoogle Scholar
Battalio, R. H., and Mendenhall, R. R.. “Earnings Expectations, Investor Trade Size, and Anomalous Returns Around Earnings Announcements.” Journal of Financial Economics, 77 (2005), 289–319.CrossRefGoogle Scholar
Battalio, R. H., and Mendenhall, R. R.. “Post-Earnings Announcement Drift: Bounds on Profitability for the Marginal Investor.” Financial Review, 46 (2011), 513–539.CrossRefGoogle Scholar
Ben-Rephael, A.; Da, Z.; and Israelsen, R. D.. “It Depends on Where You Search: Institutional Investor Attention and Underreaction to News.” Review of Financial Studies, 30 (2017), 3009–3047.CrossRefGoogle Scholar
Benjamin, D. J.; Berger, J. O.; Johannesson, M.; Nosek, B. A.; Wagenmakers, E.-J.; Berk, R.; Bollen, K. A.; Brembs, B.; Brown, L.; Camerer, C.; Cesarini, D.; Chambers, C. D.; Clyde, M.; Cook, T. D.; de Boeck, P.; Dienes, Z.; Dreber, A.; Easwaran, K.; Efferson, C.; Fehr, E.; Fidler, F.; Field, A. P.; Forster, M.; George, E. I.; Gonzalez, R.; Goodman, S.; Green, E.; Green, D. P.; Greenwald, A. G.; Hadfield, J. D.; Hedges, L. V.; Held, L.; Ho, T. Hua; Hoijtink, H.; Hruschka, D. J.; Imai, K.; Imbens, G.; Ioannidis, J. P. A.; Jeon, M.; Jones, J. H.; Kirchler, M.; Laibson, D.; List, J.; Little, R.; Lupia, A.; Machery, E.; Maxwell, S. E.; McCarthy, M.; Moore, D. A.; Morgan, S. L.; Munafó, M.; Nakagawa, S.; Nyhan, B.; Parker, T. H.; Pericchi, L.; Perugini, M.; Rouder, J.; Rousseau, J.; Savalei, V.; Schönbrodt, F. D.; Sellke, T.; Sinclair, B.; Tingley, D.; van Zandt, T.; Vazire, S.; Watts, D. J.; Winship, C.; Wolpert, R. L.; Xie, Y.; Young, C.; Zinman, J.; and Johnson, V. E.. “Redefine Statistical Significance.” Nature Human Behaviour, 2 (2018), 6–10.CrossRefGoogle ScholarPubMed
Bernard, V. Stock Price Reactions to Earnings Announcements: A Summary of Recent Anomalous Evidence and Possible Explanations, Vol. 1. New York, NY: Russell Sage Foundation (1993).Google Scholar
Bernard, V., and Thomas, J.. “Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?” Journal of Accounting Research, 27 (1989), 1–36.CrossRefGoogle Scholar
Bernard, V., and Thomas, J.. “Evidence that Stock Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings.” Journal of Accounting and Economics, 13 (1990), 305–340.CrossRefGoogle Scholar
Bhattacharya, N.; Olsson, P.; and Park, H.. “Predictability of Analyst Earnings Forecast Errors and Institutional and Individual Investors’ Reactions to Earnings News.” Journal of Accounting, Auditing and Finance, 36 (2020), 1–28.Google Scholar
Bloomfield, R.; Libby, R.; and Nelson, M.. “Do Investors Overrely on Old Elements of the Earnings Time Series?” Contemporary Accounting Research, 20 (2003), 1–31.CrossRefGoogle Scholar
Booth, G. G.; Kallunki, J.-P.; and Martikainen, T.. “Delayed Price Response to the Announcements of Earnings and its Components in Finland.” European Accounting Review, 6 (1997), 377–392.CrossRefGoogle Scholar
Bossaerts, P., and Plott, C.. “The CAPM in Thin Experimental Financial Markets.” Journal of Economic Dynamics and Control, 26 (2002), 1093–1112.CrossRefGoogle Scholar
Bossaerts, P., and Plott, C.. “Basic Principles of Asset Pricing Theory: Evidence from Large-Scale Experimental Financial Markets.” Review of Finance, 8 (2004), 135–169.CrossRefGoogle Scholar
Caginalp, G.; Porter, D.; and Hao, L.. “Asset Market Reactions to News: An Experimental Study.” ESI Working Paper, Chapman University (2011).Google Scholar
Calegari, M., and Fargher, N. L.. “Evidence that Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings: An Experimental Markets Approach.” Contemporary Accounting Research, 14 (1997), 397–433.CrossRefGoogle Scholar
Chakrabarty, B.; Moulton, P.; and Wang, X.. “Attention: How High-Frequency Trading Improves Price Efficiency Following Earnings Announcements.” Journal of Financial Markets, 59 (2022), 100690.CrossRefGoogle Scholar
Chan, W. C. “Stock Price Reaction to News and No-News: Drift and Reversal After Headlines.” Journal of Financial Economics, 70 (2003), 223–260.CrossRefGoogle Scholar
Chen, X.; He, W.; Tao, L.; and Yu, J.. “Attention and Underreaction-Related Anomalies.” Management Science, 69 (2022), 636–659.CrossRefGoogle Scholar
Chordia, T.; Goyal, A.; Sadka, G.; Sadka, R.; and Shivakumar, L.. “Liquidity and the Post-Earnings-Announcement Drift.” Financial Analysts Journal, 65 (2009), 18–32.CrossRefGoogle Scholar
Chordia, T.; Subrahmanyam, A.; and Tong, Q.. “Have Capital Market Anomalies Attenuated in the Recent Era of High Liquidity and Trading Activity?” Journal of Accounting and Economics, 58 (2014), 41–58.CrossRefGoogle Scholar
Daniel, K.; Hirshleifer, D.; and Sun, L.. “Short- and Long-Horizon Behavioral Factors.” Review of Financial Studies, 33 (2020), 1673–1736.CrossRefGoogle Scholar
DellaVigna, S., and Pollet, J. M.. “Investor Inattention and Friday Earnings Announcements.” Journal of Finance, 64 (2009), 709–749.CrossRefGoogle Scholar
Doyle, J. T.; Lundholm, R. J.; and Soliman, M. T.. “The Extreme Future Stock Returns Following I/B/E/S Earnings Surprises.” Journal of Accounting Research, 44 (2006), 849–887.CrossRefGoogle Scholar
Fama, E. “Market Efficiency, Long-Term Returns, and Behavioral Finance.” Journal of Financial Economics, 49 (1998), 283–306.CrossRefGoogle Scholar
Fama, E. F., and French, K. R.. “Common Risk Factors in the Returns on Stocks and Bonds.” Journal of Financial Economics, 33 (1993), 3–56.CrossRefGoogle Scholar
Feng, L., and Seasholes, M. S.. “Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?” Review of Finance, 9 (2005), 305–351.CrossRefGoogle Scholar
Fink, J. “A Review of the Post-Earnings-Announcement Drift.” Journal of Behavioral and Experimental Finance, 29 (2021) 100446.CrossRefGoogle Scholar
Fischbacher, U. “z-Tree: Zurich Toolbox for Ready-Made Economic Experiments.” Experimental Economics, 10 (2007), 171–178.CrossRefGoogle Scholar
Francis, J.; Lafond, R.; Olsson, P.; and Schipper, K.. “Information Uncertainty and Post-Earnings-Announcement-Drift.” Journal of Business Finance and Accounting, 34 (2007), 403–433.CrossRefGoogle Scholar
Frazzini, A. “The Disposition Effect and Underreaction to News.” Journal of Finance, 61 (2006), 2017–2046.CrossRefGoogle Scholar
Freeman, D. J.; Kimbrough, E. O.; Petersen, G. M.; and Tong, H. T.. “Instructions.” Journal of the Economic Science Association, 4 (2018), 165–179.CrossRefGoogle Scholar
Freeman, R. N., and Tse, S.. “The Multiperiod Information Content of Accounting Earnings: Confirmations and Contradictions of Previous Earnings Reports.” Journal of Accounting Research, 27 (1989), 49–79.CrossRefGoogle Scholar
Friedman, D.; Harrison, G. W.; and Salmon, J. W.. “The Informational Efficiency of Experimental Asset Markets.” Journal of Political Economy, 92 (1984), 349–408.CrossRefGoogle Scholar
Frydman, C., and Nave, G.. “Extrapolative Beliefs in Perceptual and Economic Decisions: Evidence of a Common Mechanism.” Management Science, 63 (2017), 2340–2352.CrossRefGoogle Scholar
Goldstein, M.; Irvine, P.; Kandel, E.; and Wiener, Z.. “Brokerage Commissions and Institutional Trading Patterns.” Review of Financial Studies, 22 (2009), 5175–5212.CrossRefGoogle Scholar
Hirshleifer, D. A.; Lim, S. S.; and Teoh, S. H.. “Driven to Distraction: Extraneous Events and Underreaction to Earnings News.” Journal of Finance, 64 (2009), 2289–2325.CrossRefGoogle Scholar
Hlavac, M. stargazer: Well-Formatted Regression and Summary Statistics Tables. Bratislava: Central European Labour Studies Institute (CELSI) (2018). R package version 5.2.2.Google Scholar
Hou, K.; Xiong, W.; and Peng, L.. “A Tale of Two Anomalies: The Implications of Investor Attention for Price and Earnings Momentum.” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=976394 (2009).CrossRefGoogle Scholar
Hung, M.; Li, X.; and Wang, S.. “Post-Earnings-Announcement Drift in Global Markets: Evidence from an Information Shock.” Review of Financial Studies, 28 (2015), 1242–1283.CrossRefGoogle Scholar
Ikenberry, D. L., and Ramnath, S.. “Underreaction to Self-Selected News Events: The Case of Stock Splits.” Review of Financial Studies, 15 (2002), 489–526.CrossRefGoogle Scholar
Janssen, D.-J.; Li, J.; Qiu, J.; and Weitzel, U.. “The Disposition Effect and Underreaction to Private Information.” Journal of Economic Dynamics and Control, 113 (2020), 103856.CrossRefGoogle Scholar
Jiang, H.; Li, S.; and Wang, H.. “Pervasive Underreaction: Evidence from High-Frequency Data.” Journal of Financial Economics, 141 (2021), 573–599.CrossRefGoogle Scholar
Karpoff, J. M. “The Relation Between Price Changes and Trading Volume: A Survey.” Journal of Financial and Quantitative Analysis, 22 (1987), 109–126.CrossRefGoogle Scholar
Ke, B., and Ramalingegowda, S.. “Do Institutional Investors Exploit the Post-Earnings Announcement Drift?” Journal of Accounting and Economics, 39 (2005), 25–53.CrossRefGoogle Scholar
Kieren, P.; Müller-Dethard, J.; and Weber, M.. “Can Agents Add and Subtract When Forming Beliefs?” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3644226 (2020).CrossRefGoogle Scholar
Kim, D., and Kim, M.. “A Multifactor Explanation of Post-Earnings Announcement Drift.” Journal of Financial and Quantitative Analysis, 38 (2003), 383–398.CrossRefGoogle Scholar
Kirchkamp, O. “Importing z-Tree Data into R.” Journal of Behavioral and Experimental Finance, 22 (2019), 1–2.CrossRefGoogle Scholar
Kleinlercher, D., and Stöckl, T.. “Thou Shalt Not Trade—An Analysis of the Violations of No-Trade Predictions in Experimental Asset Markets.” Journal of Behavioral and Experimental Finance, 32 (2021), 100590.CrossRefGoogle Scholar
Kothari, S. P.; Lewellen, J.; and Warner, J. B.. “Stock Returns, Aggregate Earnings Surprises and Behavioral Finance.” Journal of Financial Economics, 79 (2006), 537–568.CrossRefGoogle Scholar
Leifeld, P. “texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables.” Journal of Statistical Software, 55 (2013), 1–24.CrossRefGoogle Scholar
Leitner, J., and Leopold-Wildburger, U.. “Experiments on Forecasting Behavior with Several Sources of Information - A Review of the Literature.” European Journal of Operational Research, 213 (2011), 459–469.CrossRefGoogle Scholar
Li, J. “Slow Price Adjustment to Public News in After-Hours Trading.” Journal of Trading, 11 (2016), 16–31.CrossRefGoogle Scholar
Louhichi, W. “Adjustment of Stock Prices to Earnings Announcements: Evidence from Euronext Paris.” Review of Accounting and Finance, 7 (2008), 102–115.CrossRefGoogle Scholar
Maines, L., and Hand, J.. “Individuals’ Perceptions and Misperceptions of Time Series Properties of Quarterly Earnings.” Accounting Review, 71 (1996), 317–336.Google Scholar
Martineau, C. “Rest in Peace Post-Earnings Announcement Drift.” Critical Finance Review, 11 (2022), 613–646.CrossRefGoogle Scholar
McLean, R. D., and Pontiff, J.. “Does Academic Research Destroy Stock Return Predictability?” Journal of Finance, 71 (2016), 5–32.CrossRefGoogle Scholar
Meursault, V.; Liang, P.; Routledge, B.; and Scanlon, M.. “PEAD.txt: Post-Earnings-Announcement Drift Using Text.” Journal of Financial and Quantitative Analysis, 58 (2023), 2299–2326.CrossRefGoogle Scholar
Milgrom, P., and Stokey, N.. “Information, Trade and Common Knowledge.” Journal of Economic Theory, 26 (1982), 17–27.CrossRefGoogle Scholar
Nam, J.; Wang, J.; and Zhang, G.. “Strategic Trading Against Retail Investors with Loss-Aversion.” International Review of Economics & Finance, 17 (2008), 45–55.CrossRefGoogle Scholar
NASDAQ. “NASDAQ Nordic Market Model.” Available at https://www.nasdaq.com/docs/2023/07/03/Nasdaq-Nordic-Market-Model-2023_06_.pdf (2023). (accessed 3 August 2023).Google Scholar
Ng, J.; Rusticus, T. O.; and Verdi, R. S.. “Implications of Transaction Costs for the Post-Earnings Announcement Drift.” Journal of Accounting Research, 46 (2008), 661–696.CrossRefGoogle Scholar
Noussair, C. N., and Tucker, S.. “Cash Inflows and Bubbles in Asset Markets with Constant Fundamental Values.” Economic Inquiry, 54 (2016), 1596–1606.CrossRefGoogle Scholar
Odean, T. “Are Investors Reluctant to Realize Their Losses?” Journal of Finance, 53 (1998), 1775–1798.CrossRefGoogle Scholar
Palan, S. “A Review of Bubbles and Crashes in Experimental Asset Markets.” Journal of Economic Surveys, 27 (2013), 570–588.CrossRefGoogle Scholar
Palan, S. “GIMS - Software for Asset Market Experiments.” Journal of Behavioral and Experimental Finance, 5 (2015), 1–14.CrossRefGoogle ScholarPubMed
Pavlova, I., and Parhizgari, A.. “In Search of Momentum Profits: Are They Illusory?” Applied Financial Economics, 21 (2011), 1617–1639.CrossRefGoogle Scholar
Plott, C., and Sunder, S.. “Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models.” Journal of Political Economy, 90 (1982), 663–698.CrossRefGoogle Scholar
Plott, C. R. “Properties of Disequilibrium Adjustment in Double Auction Markets.” In Handbook of Experimental Economics Results, Vol. 1, Plott, C. R.; and Smith, V. L., eds. Amsterdam, Netherlands: North-Holland (2008), 16–21.CrossRefGoogle Scholar
Powell, O. “Numeraire Independence and the Measurement of Mispricing in Experimental Asset Markets.” Journal of Behavioral and Experimental Finance, 9 (2016), 56–62.CrossRefGoogle Scholar
R Core Team. “R: A Language and Environment for Statistical Computing.” Vienna, Austria: R Foundation for Statistical Computing (2017).Google Scholar
Rangan, S., and Sloan, R.. “Implications of the Integral Approach to Quarterly Reporting for the Post-Earnings-Announcement Drift.” Accounting Review, 73 (1998), 353–371.Google Scholar
Rendleman, R.; Jones, C.; and Latane, H.. “Further Insight into the Standardized Unexpected Earnings Anomaly: Size and Serial Correlations Effect.” Financial Review, 22 (1987), 131–144.CrossRefGoogle Scholar
Richardson, S.; Tuna, I.; and Wysocki, P.. “Accounting Anomalies and Fundamental Analysis: A Review of Recent Research Advances.” Journal of Accounting and Economics, 50 (2010), 410–454.CrossRefGoogle Scholar
Sadka, R. “Momentum and Post-Earnings Announcement Drift Anomalies: The Role of Liquidity Risk.” Journal of Financial Economics, 80 (2006), 309–349.CrossRefGoogle Scholar
Smith. “Markets as Economizers of Information: Experimental Examination of the ‘Hayek Hypothesis’.” Economic Inquiry, 20 (1982), 165–179.CrossRefGoogle Scholar
Sun, Q. “Stock Price Discovery in Earnings Season.” International Journal of Business and Finance Research, 9 (2015), 1–15.Google Scholar
Tirole, J. “On the Possibility of Speculation Under Rational Expectations.” Econometrica, 50 (1982), 1163–1181.CrossRefGoogle Scholar
Truong, C. “Post Earnings Announcement Drift and the Roles of Drift-Enhanced Factors in New Zealand.” Pacific-Basin Finance Journal, 18 (2010), 139–157.CrossRefGoogle Scholar
Truong, C. “Post-Earnings Announcement Abnormal Return in the Chinese Equity Market.” Journal of International Financial Markets, Institutions and Money, 21 (2011), 637–661.CrossRefGoogle Scholar
Weber, M., and Welfens, F.. “How Do Markets React to Fundamental Shocks?: An Experimental Analysis on Underreaction and Momentum.” Working Paper, University of Mannheim (2007).CrossRefGoogle Scholar
Wickham, H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag (2016).CrossRefGoogle Scholar
You, H., and Zhang, X.. “Financial Reporting Complexity and Investor Underreaction to 10-k Information.” Review of Accounting Studies, 14 (2009), 559–586.CrossRefGoogle Scholar
Zhang, G., and Zhang, S.. “Information Efficiency of the US Credit Default Swap Market: Evidence from Earnings Surprises.” Journal of Financial Stability, 9 (2013), 720–730.CrossRefGoogle Scholar
Zhu, H. kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax (2019). R package version 1.1.0.Google Scholar
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