Review of Accounting Studies

, Volume 18, Issue 2, pp 386–413 | Cite as

Using earnings conference calls to identify analysts with superior private information

  • William J. MayewEmail author
  • Nathan Y. Sharp
  • Mohan Venkatachalam


We examine the extent to which analysts who participate in earnings conference calls by asking questions possess superior private information relative to analysts who do not ask questions. Using a large sample of earnings conference call transcripts over the period 2002–2005, we find that annual earnings forecasts issued immediately after a conference call are both more accurate and timelier for participating analysts relative to nonparticipating analysts. These results hold after controlling for observable analyst characteristics, suggesting conference call participation can serve as a mechanism to identify analysts possessing superior private information. The economic magnitude of the superior private information contained in participating analyst forecasts is small but comparable with magnitudes reported in prior studies with respect to other analyst characteristics. Our mediation analysis does not support the notion that the superior private information stems exclusively from the information received during the call. Therefore, from a regulatory stand point, our results suggest that regulatory intervention to allow for equal participation during conference calls may be unwarranted.


Conference calls Private information benefits Financial analysts Regulation FD Forecast accuracy Forecast timeliness 

JEL Classification

M41 G24 G29 G38 K22 



We appreciate helpful comments and suggestions from three anonymous referees, Larry Brown, Michael Clement, Yonca Ertimur, Jennifer Francis, Richard Frankel, Doron Nissim (the editor), Beverley Walther, Hal White, Richard Willis, Yong Yu, the managing director and director of research at a prominent sell-side research firm, members of the National Investor Relations Institute (NIRI) Triangle chapter and seminar participants at the Duke Accounting mini-brown bag, Fuqua summer brown bag, Texas A&M summer brown bag, Southeast Summer Accounting Research Conference at the University of Georgia, Washington University at St. Louis, and the AAA Financial Accounting and Reporting Section 2010 Midyear meeting.


  1. Bagnoli, M., Watts, S., & Zhang, Y. (2008). Reg-FD and the competitiveness of all-star analysts. Journal of Accounting and Public Policy, 27, 295–316.CrossRefGoogle Scholar
  2. Baron, R. M., & Kenny, D. A. (1986). The moderator mediator variable distinction in social psychological-research—Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.CrossRefGoogle Scholar
  3. Barron, O. E., Byard, D., & Kim, O. (2002). Changes in analysts’ information around earnings announcements. The Accounting Review, 77(4), 821–846.CrossRefGoogle Scholar
  4. Barron, O. E., Kim, O., Lim, S. C., & Stevens, D. E. (1998). Using analysts’ forecasts to measure properties of analysts’ information environment. The Accounting Review, 73(4), 421–433.Google Scholar
  5. Brochet, F., Miller, G., & Srinivasan, S. (2010). Do analyst/manager relations travel: An analysis of executives changing employers. Working paper, Harvard Business School and University of Michigan.Google Scholar
  6. Brown, L. (2001). How important is past analyst forecast accuracy? Financial Analysts Journal, 57(6), 44–49.CrossRefGoogle Scholar
  7. Brown, L., & Mohd, E. (2003). The predictive value of analyst characteristics. Journal of Accounting, Auditing and Finance, 18(4), 625–647.Google Scholar
  8. Bushee, B., Matsumoto, D., & Miller, G. (2004). Managerial and investor response to disclosure regulation: The case of Reg FD and conference calls. The Accounting Review, 79(3), 617–643.CrossRefGoogle Scholar
  9. Chen, S., & Matsumoto, D. (2006). Favorable versus unfavorable recommendations: The impact on analyst’ access to management-provided information. Journal of Accounting Research, 40(4), 657–689.CrossRefGoogle Scholar
  10. Clement, M. B. (1999). Analyst forecast accuracy: Do ability, resources and portfolio complexity matter? Journal of Accounting and Economics, 27(June), 285–303.CrossRefGoogle Scholar
  11. Clement, M., & Tse, S. (2003). Do investors respond to analysts’ forecast revisions as if forecast accuracy is all that matters? The Accounting Review, 78(1), 227–249.CrossRefGoogle Scholar
  12. Clement, M. B., & Tse, S. (2005). Financial analyst characteristics and herding behavior in forecasting. Journal of Finance, 60(1), 307–341.CrossRefGoogle Scholar
  13. Cohen, L., Frazzini, A., & Malloy, C. (2010). Hiring cheerleaders: Board appointments of “independent” directors. Working paper, AQR Capital Management and Harvard University.Google Scholar
  14. Cox, C. (2005). Response letter to Senator Ron Wyden regarding issuer retaliation against research analysts. Securities and Exchange Commission (September 1, 2005).Google Scholar
  15. Davis, A. (2004). Wall street, companies it covers, agree on honesty policy. The Wall Street Journal (March 11, 2004): C1.Google Scholar
  16. Diamond, D. (1985). Optimal release of information by firms. Journal of Finance, 40(4), 1071–1094.CrossRefGoogle Scholar
  17. Erdos & Morgan, (2008). Investor perception study (13th ed.). Conducted on behalf of IR Magazine. Google Scholar
  18. Frankel, R., Johnson, M., & Skinner, D. (1999). An empirical examination of conference calls as a voluntary disclosure medium. Journal of Accounting Research, 37, 133–150.CrossRefGoogle Scholar
  19. Groysberg, B., Healy, P. M., & Maber, D. A. (2011). What drives sell-side analyst compensation at high-status banks? Journal of Accounting Research, 49(4), 969–1000. Google Scholar
  20. Hollander, S., Pronk, M., & Roelofsen, E. (2010). Does silence speak? An empirical analysis of disclosure choices during conference calls. Journal of Accounting Research, 48(3), 531–563.CrossRefGoogle Scholar
  21. Huber, P. J. (1967). The behavior of maximum likelihood estimates under nonstandard conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1, 221–223.Google Scholar
  22. Johnson, T. (2005). The 2005 All-America research team. Institutional Investor, 39(10), 52–90.Google Scholar
  23. Jones, S. (2005). Mechanism is in place to resolve analyst-company disputes. Investment News. CFA Institute (October 10, 2005).Google Scholar
  24. Ke, B., & Yu, Y. (2006). The effect of issuing biased earnings forecasts on analysts’ access to management and survival. Journal of Accounting Research, 44, 965–1000.CrossRefGoogle Scholar
  25. Kim, O., & Verrecchia, R. (1997). Pre-announcement and event-period private information. Journal of Accounting and Economics, 24(3), 395–419.CrossRefGoogle Scholar
  26. Libby, R., Hunton, J., Tan, H. T., & Seybert, N. (2008). Relationship incentives and the optimistic/pessimistic pattern in analysts’ forecasts. Journal of Accounting Research, 46(1), 173–198.CrossRefGoogle Scholar
  27. Lowengard, M. (2006). Guide to icing analysts. IR Magazine (July 2006).Google Scholar
  28. Mackinnon, D. P., & Dwyer, J. H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17(2), 144–158.CrossRefGoogle Scholar
  29. Mackinnon, D. P., Warsi, G., & Dwyer, J. H. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30(1), 41–62.CrossRefGoogle Scholar
  30. Matsumoto, D., Pronk, M., & Roelofsen, E. (2011). What makes conference calls useful? The information content of managers’ presentations and analysts’ discussion sessions. The Accounting Review, 86(4), 1383–1414.CrossRefGoogle Scholar
  31. Mayew, W. (2008). Evidence of management discrimination among analysts during earnings conference calls. Journal of Accounting Research, 46(3), 627–659.CrossRefGoogle Scholar
  32. Mayew, W., & Venkatachalam, M. (2012). The power of voice: Managerial affective states and future firm performance. Journal of Finance, 67(1), 1–44.CrossRefGoogle Scholar
  33. Mayo, M. (2002). Testimony for “Accounting and investor protection issues raised by Enron and other public companies.” U.S. Senate Committee on Banking, Housing and Urban Affairs Hearing (March 19, 2002).Google Scholar
  34. Mayo, M. (2006). Why independent research is still rare. CFA Magazine, 17(3), 6–7.Google Scholar
  35. Mayo, M. (2010). Testimony before the financial crisis inquiry commission. January 13, 2010.
  36. McNichols, M., & O’Brien, P. (1997). Self-selection and analyst coverage. Journal of Accounting Research, 35(Supplement), 167–199.Google Scholar
  37. Mohanram, P. S., & Sunder, S. V. (2006). How has regulation fair disclosure affected the functioning of financial analysts? Contemporary Accounting Research, 23(2), 491–525.CrossRefGoogle Scholar
  38. Morgenson, G. (2005). S.E.C. looks at company’s retaliation on analysts. The New York Times Section 3 (September 23, 2005).Google Scholar
  39. Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731.CrossRefGoogle Scholar
  40. Preacher, K. J., & Leonardelli, G. J. (2001). Calculation for the Sobel Test: An interactive calculation tool for mediation tests 2001 [cited March 2001]. Available from
  41. Ramnath, S., Rock, S., & Shane, P. (2008). The financial analyst forecasting literature: A taxonomy and suggestions for future research. International Journal of Forecasting, 24, 34–75.CrossRefGoogle Scholar
  42. Richardson, S., Teoh, S. W., & Wysocki, P. (2004). The walk-down to beatable analyst forecasts: The role of equity issuance and insider trading incentives. Contemporary Accounting Research, 21(4), 885–924.CrossRefGoogle Scholar
  43. Rosenbaum, P., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.CrossRefGoogle Scholar
  44. Schipper, K. (1991). Commentary on analysts’ forecasts. Accounting Horizons, 5(December), 105–119.Google Scholar
  45. Securities Industry Association (SIA). (2005). Letter to SEC re: Comment on release no. 34-51545, sr-nyse-2005-24, and Chairman Donaldson’s remarks on issuer retaliation. Securities Industry Association (May 11, 2005).Google Scholar
  46. Skinner, D. (2003). Should firms disclose everything to everybody? A discussion of “open vs. closed conference calls: The determinants and effects of broadening access to disclosure”. Journal of Accounting and Economics, 34, 181–187.CrossRefGoogle Scholar
  47. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological methodology, 13, 290–312.Google Scholar
  48. Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. Sociological methodology, 16, 159–186.Google Scholar
  49. Verrecchia, R. (1982). Information acquisition in a noisy rational expectations economy. Econometrica, 50(6), 1415–1430.CrossRefGoogle Scholar
  50. Westphal, J., & Clement, M. (2008). Sociopolitical dynamics in relations between top managers and security analysts: Favor rendering, reciprocity and analyst stock recommendations. Academy of Management Journal, 51(5), 873–897.CrossRefGoogle Scholar
  51. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • William J. Mayew
    • 1
    Email author
  • Nathan Y. Sharp
    • 2
  • Mohan Venkatachalam
    • 1
  1. 1.Fuqua School of BusinessDuke UniversityDurhamUSA
  2. 2.Mays Business SchoolTexas A&M UniversityCollege StationUSA

Personalised recommendations