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Predicting Accounting Misconduct: The Role of Firm-Level Investor Optimism

  • Shantaram Hegde
  • Tingyu Zhou
Original Paper

Abstract

Motivated by a large literature on how firm-specific resources (such as leadership and management skills, strategies, organizational capabilities and intellectual properties) drive firm performance, we propose and find that heterogeneity in investor optimism regarding firm-specific attributes plays a very important role in influencing the managerial propensity to manipulate financial statements. When firm-level investor optimism is moderate, the incidence of accounting misconduct increases, but it decreases when investors are highly optimistic. Further, market reaction to the announcement of financial restatements is more negative when investors held more optimistic firm-specific beliefs at the time of initial misstatement. These findings are robust to alternative firm-specific optimism measures linked to analysts, general investors and unsophisticated individual investors, controls for market-wide consumer sentiment unexplained by macroeconomic factors, economy-wide and industry-level optimism, potential selection bias and reverse causality. Our analysis highlights the importance of firm-level investor optimism in predicting, preventing and detecting accounting misconduct.

Keywords

Investor optimism Financial reporting Accounting misconduct Irregularity Earnings management Market reactions 

JEL Classification

G10 G14 G34 G38 

Notes

Acknowledgements

We are very grateful to Steven Dellaportas (the editor) and two anonymous referees for their very helpful comments. We thank Jonathan M. Karpoff, Allison Koester, D. Scott Lee and Gerald S. Martin who generously shared with us the Federal Securities Regulation (FSR) database. We thank Andrew J. Leone for generously sharing the General Accountability Office (GAO) data on classification of errors and irregularities. We appreciate insightful comments from Assaf Eisdorfer, Efdal Misirli, John Clapp, Joseph Golec, John Glascock and seminar participants at University of Connecticut, the 2016 Annual Meeting of Southern Finance Association (SFA) and the 4th India Finance Conference.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10551_2018_3848_MOESM1_ESM.pdf (372 kb)
Supplementary material 1 (PDF 373 kb)

References

  1. Aboody, D., Even-Tov, O., Lehavy, R., & Trueman, B. (2018). Overnight returns and firm-specific investor sentiment. Journal of Financial and Quantitative Analysis.  https://doi.org/10.1017/S0022109017000989.
  2. Agrawal, A., & Cooper, T. (2015). Insider trading before accounting scandals. Journal of Corporate Finance, 34, 169–190.CrossRefGoogle Scholar
  3. Amiram, D., & Kalay, A. (2017). Industry characteristics, risk premiums, and debt pricing. The Accounting Review, 92, 1–27.CrossRefGoogle Scholar
  4. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58, 277–297.CrossRefGoogle Scholar
  5. Badertscher, B. A., Hribar, S. P., & Jenkins, N. T. (2011). Informed trading and the market reaction to accounting restatements. The Accounting Review, 86, 1519–1547.CrossRefGoogle Scholar
  6. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61, 1645–1680.CrossRefGoogle Scholar
  7. Ball, B. (2009). Market and political/regulatory perspectives on the recent accounting scandals. Journal of Accounting Research, 47, 277–323.CrossRefGoogle Scholar
  8. Barber, B., Odean, T., & Zhu, N. (2009). Do retail trades move markets? Review of Financial Studies, 22, 151–186.CrossRefGoogle Scholar
  9. Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. Quarterly Journal of Economics, 116, 261–292.CrossRefGoogle Scholar
  10. Bardos, K. S., Golec, J., & Harding, J. P. (2011). Do investors see through mistakes in reported earnings? Journal of Financial and Quantitative Analysis, 46, 1917–1946.CrossRefGoogle Scholar
  11. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.CrossRefGoogle Scholar
  12. Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55, 24–36.CrossRefGoogle Scholar
  13. Berkman, H., Koch, P., Tuttle, L., & Zhang, Y. (2012). Paying attention: Overnight returns and the hidden cost of buying at the open. Journal of Financial and Quantitative Analysis, 47, 715–741.CrossRefGoogle Scholar
  14. Bhattacharya, U., & Marshall, C. D. (2012). Do they do it for the money? Journal of Corporate Finance, 18, 92–104.CrossRefGoogle Scholar
  15. Bradshaw, M. T., Richardson, S. A., & Sloan, R. G. (2006). The relation between corporate financing activities, analysts forecasts and stock returns. Journal of Accounting and Economics, 42, 53–85.CrossRefGoogle Scholar
  16. Brochet, F., Ferri, F., & Miller, G. S. (2016). Market valuation of anticipated governance changes: Evidence from contentious shareholder meetings. Columbia Business School Research Paper No. 16-47, 2016.Google Scholar
  17. Burks, J. J. (2011). Are investors confused by restatements after Sarbanes–Oxley? Accounting Review, 86, 507–539.CrossRefGoogle Scholar
  18. Burns, N., & Kedia, S. (2006). the impact of performance-based compensation on misreporting. Journal of Financial Economics, 79, 35–67.CrossRefGoogle Scholar
  19. Burns, N., Kedia, S., & Lipson, M. (2010). Institutional ownership and monitoring: Evidence from financial misreporting. Journal of Corporate Finance, 16, 443–455.CrossRefGoogle Scholar
  20. Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and applications. New York: Cambridge University Press.CrossRefGoogle Scholar
  21. Carcello, J. V., Neal, T. L., Palmrose, Z. V., & Scholz, S. (2011). CEO involvement in selecting board members, audit committee effectiveness, and restatements. Contemporary Accounting Research, 28, 396–430.CrossRefGoogle Scholar
  22. Carter, M., & Lynch, L. (2001). An examination of executive stock option repricing. Journal of Financial Economics, 61, 207–225.CrossRefGoogle Scholar
  23. Cohen, J., Ding, Y., Lesage, C., & Stolowy, H. (2017). Media bias and the persistence of the expectation gap: An analysis of press articles on corporate fraud. Journal of Business Ethics, 144, 637–659.CrossRefGoogle Scholar
  24. Collins, D. W., Kothari, S. P., & Rayburn, J. D. (1987). Firm size and the information content of prices with respect to earnings. Journal of Accounting and Economics, 9, 111–138.CrossRefGoogle Scholar
  25. Crutchley, C. E., Jensen, M., & Marshall, B. B. (2007). Climate for scandal: Corporate environments that contribute to accounting fraud. Financial Review, 42, 53–73.CrossRefGoogle Scholar
  26. Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (2001). Overconfidence, arbitrage, and equilibrium asset pricing. Journal of Finance, 56, 921–965.CrossRefGoogle Scholar
  27. Dechow, P. M., Ge, W. L., Larson, C. R., & Sloan, R. G. (2011). Predicting material accounting misstatements. Contemporary Accounting Research, 28, 17–82.CrossRefGoogle Scholar
  28. Dechow, P., Hutton, A., & Kim., J., & Sloan, R. (2012). Detecting earnings management: a new approach. Journal of Accounting Research, 50(2), 275–334.CrossRefGoogle Scholar
  29. Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1996). Causes and consequences of earnings misstatement: An analysis of firms subject to enforcement actions by the SEC. Contemporary Accounting Research, 13, 1–36.CrossRefGoogle Scholar
  30. Dichev, I. D., & Skinner, D. J. (2002). Large-sample evidence on the debt covenant hypothesis. Journal of Accounting Research, 40, 1091–1123.CrossRefGoogle Scholar
  31. Dyck, A., Morse, A., & Zingales, L. (2010). Who blows the whistle on corporate fraud? Journal of Finance, 65, 2213–2253.CrossRefGoogle Scholar
  32. El-Gazzar, S. M. (1998). Pre-disclosure information and institutional ownership: A cross-sectional examination of market revaluations during earnings announcement periods. The Accounting Review, 73, 119–129.Google Scholar
  33. Erickson, T., Jiang, C. H., & Whited, T. M. (2014). Minimum distance estimation of the errors-in-variables model using linear cumulant equations. Journal of Econometrics, 183, 211–221.CrossRefGoogle Scholar
  34. Erickson, T., & Whited, T. M. (2012). Treating measurement error in Tobin’s q. Review of Financial Studies, 25, 1286–1329.CrossRefGoogle Scholar
  35. Fama, E. F., & French, K. R. (1997). Industry costs of equity. Journal of Financial Economics, 43, 153–193.CrossRefGoogle Scholar
  36. Files, R., Swanson, E., & Tse, S. (2009). Stealth disclosure of accounting restatements. The Accounting Review, 84, 1495–1520.CrossRefGoogle Scholar
  37. General Accounting Office (GAO). (2002). Financial statement restatements—Trends, market impacts, regulatory responses, and remaining challenges (GAO-03-138). Washington, DC: Report to Congressional Committees.Google Scholar
  38. General Accountability Office (GAO). (2006). Financial restatements: Update of public company trends, market impacts, and regulatory enforcement activities (GAO-06-678). Washington, DC: Report to Congressional Committees.Google Scholar
  39. Gong, G., Li, L., & Zhou, L. (2013). Earnings non-synchronicity and voluntary disclosure. Contemporary Accounting Research, 30, 1560–1589.CrossRefGoogle Scholar
  40. Harris, J. D., & Bromiley, P. (2006). Incentives to cheat: The influence of executive compensation and firm performance on financial misrepresentation. Organization Science, 18, 350–367.CrossRefGoogle Scholar
  41. Hass, L. H., Tarsalewska, M., & Zhan, F. (2016). Equity incentives and corporate fraud in China. Journal of Business Ethics, 138, 723–742.CrossRefGoogle Scholar
  42. Hawawini, G., Subramanian, V., & Verdin, P. (2003). Is performance driven by industry- or firm-specific factors? A new look at the evidence. Strategic Management Journal, 24, 1–16.CrossRefGoogle Scholar
  43. Healy, P. M. (1985). The effect of bonus schemes on accounting decisions. Journal of Accounting and Economics, 7, 85–107.CrossRefGoogle Scholar
  44. Hennes, K. M., Leone, A. J., & Miller, B. P. (2008). The importance of distinguishing errors from irregularities in restatement research: The case of restatements and CEO/CFO turnover. The Accounting Review, 83, 1487–1519.CrossRefGoogle Scholar
  45. Hertzberg, A. (2005). Managerial incentives, misreporting, and the timing of social learning: A theory of slow booms and rapid recessions. Working Paper, Northwestern University.Google Scholar
  46. Hirshleifer, D. (2001). Investor psychology and asset pricing. Journal of Finance, 56, 1533–1597.CrossRefGoogle Scholar
  47. Hribar, P., & Jenkins, N. T. (2004). The effect of accounting restatements on earnings revisions and the estimated cost of capital. Review of Accounting Studies, 9, 337–356.CrossRefGoogle Scholar
  48. Hribar, P., & McInnis, J. (2012). Investor sentiment and analysts’ earnings forecast errors. Management Science, 58, 293–307.CrossRefGoogle Scholar
  49. Hribar, P., Melessa, S., Small, R., & Wilde, J. (2017). Does managerial sentiment affect accrual estimates? Evidence from the banking industry. Journal of Accounting and Economics, 63, 26–50.CrossRefGoogle Scholar
  50. Huber, P. J. (1967). The behavior of maximum likelihood estimates under non-standard conditions. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, pp.221–233). Berkely, CA: University of California Press.Google Scholar
  51. Hutton, A. P., Lee, L. F., & Shu, S. Z. (2012). Do managers always know better? The relative accuracy of management and analyst forecasts. The Accounting Review, 50, 1217–1244.Google Scholar
  52. Jones, K. L., Krishnan, G. V., & Melendrez, K. D. (2008). Do Models of discretionary accruals detect actual cases of fraudulent and restated earnings? An empirical analysis. Contemporary Accounting Research, 25, 499–531.CrossRefGoogle Scholar
  53. Karpoff, J., Koester, A., Lee, D., & Martin, G. (2017). Proxies and databases in financial misconduct research. The Accounting Review, 92, 129–163.CrossRefGoogle Scholar
  54. Kayo, E. K., & Kimura, H. (2011). Hierarchical determinants of capital structure. Journal of Banking & Finance, 35, 358–371.CrossRefGoogle Scholar
  55. Kedia, S., & Philippon, T. (2009). The economics of fraudulent accounting. Review of Financial Studies, 22, 2169–2199.CrossRefGoogle Scholar
  56. Kinney, W. R., Jr., Palmrose, Z. V., & Scholz, S. (2004). Auditor independence, non-audit services, and restatements: Was the U.S. government right? Journal of Accounting Research, 42, 561–588.CrossRefGoogle Scholar
  57. Kothari, S. P., Leone, A., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39, 163–197.CrossRefGoogle Scholar
  58. Lambrecht, B. (2001). The impact of debt financing on entry and exit in a duopoly. Review of Financial Studies, 14, 765–804.CrossRefGoogle Scholar
  59. Lemmon, M., & Portniaguina, E. (2006). Consumer confidence and asset prices: Some empirical evidence. Review of Financial Studies, 19(1), 499–530.Google Scholar
  60. Li, F., Lundholm, R., & Minnis, M. (2012). A measure of competition based on 10-k filings. The Accounting Review, 51, 399–436.Google Scholar
  61. Liu, M. H. (2011). Analysts’ incentives to produce industry-level versus firm-specific information. Journal of Financial and Quantitative Analysis, 46, 757–784.CrossRefGoogle Scholar
  62. Loughran, T., & Ritter, J. (2000). Uniformly least powerful tests of market efficiency. Journal of Financial Economics, 55, 361–389.CrossRefGoogle Scholar
  63. Malmendier, U., & Tate, G. (2005). CEO overconfidence and corporate investment. Journal of Finance, 60, 2661–2700.CrossRefGoogle Scholar
  64. McGahan, A., & Porter, M. (2002). What do we know about variance in accounting profitability? Management Science, 48, 834–851.CrossRefGoogle Scholar
  65. Myers, R. (2016). The rising risk of being CFO. CFO magazine, December 15, 2016. http://ww2.cfo.com/risk-management/.
  66. Nguyen, D., Hagendorff, J., & Eshraghi, A. (2016). Can Bank Boards Prevent Misconduct? Review of Finance, 20, 1–36.CrossRefGoogle Scholar
  67. Palmrose, Z. V., Richardson, V. J., & Scholz, S. (2004). Determinants of market reactions to restatement announcements. Journal of Accounting and Economics, 37, 59–89.CrossRefGoogle Scholar
  68. Petersen, M. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22, 435–480.CrossRefGoogle Scholar
  69. Piotroski, J. D., & Roulstone, D. T. (2004). The influence of analysts, institutional investors, and insiders on the incorporation of market, industry, and firm-specific information into stock prices. The Accounting Review, 79, 1119–1151.CrossRefGoogle Scholar
  70. Porter, M. (1991). Towards a dynamic theory of strategy. Strategic Management Journal, 12, 95–117.CrossRefGoogle Scholar
  71. Povel, P., Singh, R., & Winton, A. (2007). Booms, busts, and fraud. Review of Financial Studies, 20, 1219–1254.CrossRefGoogle Scholar
  72. Rauh, J., & Sufi, A. (2012). Explaining corporate capital structure: Product markets, leases, and asset similarity. Review of Finance, 16, 115–155.CrossRefGoogle Scholar
  73. Rogers, W. H. (1993). Regression standard errors in clustered samples. Stata Technical Bulletin, 13, 19–23.Google Scholar
  74. Roll, R. (1988). R2. Journal of Finance, 43(3), 541–566.Google Scholar
  75. Russo, J. E., & Schoemaker, P. (1992). Managing overconfidence. Sloan Management Review, 33, 7–17.Google Scholar
  76. Scheinkman, J. A., & Xiong, W. (2003). Overconfidence and speculative bubble. Journal of Political Economy, 111, 1183–1220.CrossRefGoogle Scholar
  77. Schmalensee, R. (1985). Do markets differ much? American Economic Review, 75, 341–351.Google Scholar
  78. Simpson, A. (2013). Does investor sentiment affect earnings management? Journal of Business Finance and Accounting, 40, 869–900.CrossRefGoogle Scholar
  79. Song, F., & Thakor, A. V. (2006). Information control, career concerns, and corporate governance. Journal of Finance, 61, 845–1896.CrossRefGoogle Scholar
  80. Wang, T. Y. (2011). Corporate securities fraud: Insights from a new empirical framework. Journal of Law Economics and Organization, 29(3), 535–568.CrossRefGoogle Scholar
  81. Wang, T. Y., & Winton, A. (2014). Product market interactions and corporate fraud. Working Paper. University of Minnesota.Google Scholar
  82. Wang, T. Y., Winton, A., & Yu, X. Y. (2010). Corporate fraud and business conditions: Evidence from IPOs. Journal of Finance, 65, 2255–2292.CrossRefGoogle Scholar
  83. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817–838.CrossRefGoogle Scholar
  84. Williams, R. (2012). Using the margins command to estimate and interpret adjusted predictions and marginal effects. The Stata Journal, 12, 308–331.Google Scholar
  85. Young, S., & Peng, E. (2013). An analysis of accounting frauds and the timing of analyst coverage decisions and recommendation revisions: Evidence from the US. Working Paper.Google Scholar
  86. Zhao, Y., & Chen, K. H. (2008). The influence of takeover protection on earnings management. Journal of Business Finance & Accounting, 35, 347–375.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Finance Department, School of BusinessUniversity of ConnecticutStorrsUSA
  2. 2.Department of Risk Management/Insurance, Real Estate and Legal StudiesFlorida State UniversityTallahasseeUSA

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