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CEO stock options and analysts’ forecast accuracy and bias

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Abstract

This paper investigates the relationship between CEO stock options and analysts’ earnings forecast accuracy and bias. A higher level of stock options may induce managers to undertake riskier projects, to change and/or reallocate their effort, and to possibly engage in gaming (such as opportunistic earnings and disclosure management). These managerial behaviors result in an increase in the complexity of forecasting and hence, less accurate analysts’ forecasts. Analysts’ optimistic forecast bias may also increase as the level of stock options pay increases. Because forecast complexity increases with stock options pay, analysts, needing greater access to management’s information to produce accurate forecasts, have incentives to increase the optimistic bias in their forecasts. Alternatively, a higher level of stock options pay may lead to improved disclosure because it better aligns managers’ and shareholders’ interests. The improved disclosure, in turn, may result in more accurate and less biased analysts’ forecasts. Our empirical evidence indicates that analysts’ earnings forecast accuracy decreases and forecast optimism increases as the level of CEO stock options increases. This evidence suggests that the incentive alignment effects of stock options are more than offset by the investment, effort allocation and gaming incentives induced by stock options grants to CEOs.

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Notes

  1. Other reasons for granting stock options are to attract and retain executives, to conserve cash, to reduce reported accounting expense, and to defer taxes.

  2. Although there is evidence relating earnings management to stock options compensation, little is known about whether this earnings management actually results in higher payouts or about its effect on other goals of the firm.

  3. Ke and Yu (2006) and Chen and Matsumoto (2006) are examples of recent research on analysts’ incentives for access to management, i.e., the management relations hypothesis.

  4. Furthermore, Feltham and Xie (1994) show that, if there are multiple tasks and multiple public signals that are influenced by the manager’s action, it is unlikely that the market price provides an efficient single performance measure. Therefore, overly relying on stock-based compensation may lead to incongruent behavior by CEOs, further increasing the difficulty of the forecasting task.

  5. However, in related research Hribar and Nichols (2007) provide evidence that not controlling for operating volatility increases the risk of over-rejecting the null hypothesis of no earnings management.

  6. Although Aboody and Kasznik (2000) study only fixed schedule awards, we argue that the incentive to maximize the stock options pay by manipulating the stock price at the grant date is present for all stock options awards, and that the incentive is especially strong for firms that make multiple grants in a given year. We note that a large number of our sample firms made multiple grants in the same fiscal year thus increasing this incentive. It is also interesting to note that the stock options award dates are generally not publicly known until the issue of proxy statements which are available only 2–3 months after the fiscal year end (Yermack 1997).

  7. To be consistent with the prior literature on executive pay (Core et al. 1999; Hanlon et al. 2003), we omit financial institutions and agricultural companies. However, for completeness, we also conducted the analysis with these companies included in the sample. Our main conclusions are unaffected by this inclusion.

  8. We repeat all our analyses using 3-month-ahead forecasts to examine the robustness of our results to the forecast horizon. Most results for the three-month forecasts mirror those presented for the nine-month forecasts.

  9. The sample firms represent a variety of industries, with the largest representation being retail (8%), electronic equipment (6.7%), business services (5.3%) and telecommunications (6%).

  10. As a sensitivity check, when using lagged OPTIONS, we delete observations that have a new CEO in the current year. Our main results are robust to deletion of these observations.

  11. Gu (2003) argues that inclusion of earnings level as a control variable will induce spurious relationships between the variable capturing forecast efficiency and other control variables. Our main results are stronger when we exclude earnings level as a control variable.

  12. Prior research on forecast accuracy and bias (e.g., Duru and Reeb 2002) does not control for differences in growth. Our results are robust to the exclusion of GROWTH as a control variable in the regressions.

  13. The variance inflation factors for variables in our main regressions are all below three, indicating that there are no severe multicollinearity problems.

  14. We also estimate the regression without the absolute value of earnings surprise (ABSESUP) that might be mechanically related to accuracy. The main results are not affected by the exclusion of that variable. We note that inclusion of ABSESUP can only weaken the hypothesized relationship between ACCURACY and OPTIONS because ABSESUP is closely related to ACCURACY.

  15. We also estimate the model without earnings surprise (ESUP), negative earnings surprise (NEGESUP), and level of earnings (LEVEARN) that might be mechanically related to bias. The relationship between level of options and bias is not affected by the omission of those variables.

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Acknowledgments

We thank Zhaoyang Gu, Emad Mohd, Mohamed Shehata, K. (Shiva) Sivaramakrishnan, Scott Whisenant, Yoonseok Zang, Jian Zhou, the anonymous reviewers, and workshop participants at the University of Houston, Drexel University, Wilfrid Laurier University, the 2005 American Accounting Association Meeting, the 2005 Canadian Academic Accounting Association Meeting, and the 2005 European Accounting Association Meeting, for helpful comments, and Alper Ozesen and Li Wang for research assistance. We gratefully acknowledge the contribution of Thompson Financial for providing forecast data, available through the Institutional Brokers Estimate System (I/B/E/S). These data have been provided as part of a broad academic program to encourage earnings expectations research. We also thank the Social Sciences and Humanities Research Council of Canada (SSHRC) for their financial support.

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Authors and Affiliations

  1. DeGroote School of Business, McMaster University, Hamilton, ON, L8S 4M4, Canada

    Kiridaran Kanagaretnam

  2. C.T. Bauer College of Business, University of Houston, Houston, TX, 77204, USA

    Gerald J. Lobo

  3. School of Business and Economics, Wilfrid Laurier University, Waterloo, ON, N2L 3C5, Canada

    Robert Mathieu

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  1. Kiridaran Kanagaretnam
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  2. Gerald J. Lobo
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  3. Robert Mathieu
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Correspondence to Gerald J. Lobo.

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Kanagaretnam, K., Lobo, G.J. & Mathieu, R. CEO stock options and analysts’ forecast accuracy and bias. Rev Quant Finan Acc 38, 299–322 (2012). https://doi.org/10.1007/s11156-011-0229-0

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