|
|
|
| Unexpected Equity Expansion and Analysts' EPS Forecasts |
| WU Weili, LIU Jie, ZHANG Zheng
|
School of Finance, Central University of Finance and Economics;
College of Economics, Fujian Agriculture and Forestry University;
Guanghua School of Management, Peking University |
|
|
|
Abstract Data of analysts' earnings per share (EPS) forecasts are widely used in empirical studies as a proxy for analysts' predictions of target companies' future fundamentals. However, EPS forecasts depend not only on analysts' predictions of companies' future net profits, but also on predictions of companies' future total number of shares. If a target company's equity expansion after the release of analysts' earnings forecasts exceeds analysts' expectations, EPS forecasts no longer represent analysts' predictions of the company's future fundamentals. However, the extant domestic empirical literature does not adequately cover this problem. This paper proposes an adjustment method that can truly reflect analysts' predictions of a company's future fundamentals. Using our adjusted EPS forecasts, we show in two specific empirical research scenarios that when using EPS forecast data, if the impact of unexpected equity expansion is not excluded, erroneous empirical results may be obtained.
First, when evaluating the optimistic bias and forecast error in analysts' EPS forecasts, if we neglect the effects of unexpected equity expansion, the optimistic bias and forecast error of EPS forecasts are systematically overestimated. We find that the relative optimistic bias and relative forecast error of the original EPS forecasts are significantly higher than those of the adjusted EPS forecasts. Second, when investigating the factors affecting the optimistic bias and forecast error of EPS forecasts, if we ignore unexpected equity expansion, we may obtain biased empirical results. In this study, we use optimistic bias and forecast error as the explained variables to construct two pairs of regression models. The results indicate that after excluding the impact of unexpected equity expansion, the significance levels and even the sign of the regression coefficients of the explanatory variables change.
In fact, ignoring the impact of unexpected equity expansion will cause other severe problems in empirical research. First, ignoring any unexpected equity expansion may lead researchers to misunderstand analyst forecast revisions, which are generally considered as adjustments to the predictions of a company's future fundamentals, but may in fact result from the company's equity expansion. Second, ignoring unexpected equity expansion may lead one to overestimate the dispersion of analysts' EPS forecasts. Differences in different analysts' EPS forecasts may be the result of their differing information on the equity scale, rather than differences in their predictions of company fundamentals. Third, ignoring unexpected equity expansion may lead to an underestimation of the research capabilities and information quality of analysts who release their EPS forecasts early. Analysts who release their EPS forecasts later than others not only have more accurate information about company fundamentals, but also more accurate information on the equity scale. Therefore, analysts who publish later than others may have more accurate EPS forecasts, but this does not mean that these analysts' forecasts of company fundamentals are more accurate. More accurate EPS forecasts can be generated when more accurate information on the equity scale is available.
The contributions of this paper are as follows. First, data from analysts' EPS forecasts are widely studied and used in empirical research. However, these data rely on analysts' predictions of a company's future net profits and future total number of shares. Therefore, after analysts make their predictions, if the company undergoes capital expansion that exceeds analysts' expectations, then the predicted EPS will not represent analysts' forecasts of the company's future fundamentals. In general, the domestic empirical literature does not account for this problem. This paper constructs a new indicator called “adjusted EPS forecast” to represent analysts' real forecasts of a company's future fundamentals. Second, under two specific empirical research scenarios, this paper proves that when using EPS forecasts in empirical research, if the impact of unexpected equity expansion is ignored, erroneous empirical results may be obtained. Finally, this paper points out the errors that may be caused by ignoring unexpected equity expansion in other empirical research scenarios.From a practical perspective, this paper provides a method for the financial industry to accurately interpret and use analysts' EPS forecast data.
|
|
Received: 14 January 2019
Published: 02 November 2020
|
|
|
|
|
| [1] |
李心丹、俞红海、陆蓉和徐龙炳,2014,《中国股票市场“高送转”现象研究》,《管理世界》第11期,第133～145页。
|
| [2] |
谭松涛、阚铄和崔小勇,2016,《互联网沟通能够改善市场信息效率吗？——基于深交所“互动易”网络平台的研究》,《金融研究》第3期,第174～188页。
|
| [3] |
吴超鹏、郑方镳和杨世杰,2013,《证券分析师的盈余预测和股票评级是否具有独立性？》,《经济学(季刊)》第3期,第935～958页。
|
| [4] |
吴偎立、张峥和乔坤元,2016,《信息质量,市场评价与激励有效性——基于新财富最佳分析师评选的证据》,《经济学(季刊)》第1期,第723～744页。
|
| [5] |
游家兴、邱世远和刘淳,2013,《证券分析师盈余预测“变脸”行为研究——基于分析师声誉的博弈模型与实证检验》,《管理科学学报》第6期,第67～84页。
|
| [6] |
游家兴、周瑜婷和肖珉,2017,《凯恩斯选美竞赛与分析师预测偏差行为——基于高阶预期的研究视角》,《金融研究》第7期,第192～206页。
|
| [7] |
Barth M E, Hutton A P. 2004. “Analyst Earnings Forecast Revisions and the Pricing of Accruals” ,Review of Accounting Studies, 9(1): 59～96.
|
| [8] |
Brown L D. 1993. “Earnings Forecasting Research: Its Implications for Capital Markets Research” ,International Journal of Forecasting, 9(3): 295-320.
|
| [9] |
Clement M B. 1999. “Analyst Forecast Accuracy: Do Ability, Resources, and Portfolio Complexity Matter？” ,Journal of Accounting and Economics, 27(3): 285～303.
|
| [10] |
Das S, Levine C B, Sivaramakrishnan K. 1998. “Earnings Predictability and Bias in Analysts' Earnings Forecasts” ,Accounting Review: 277～294.
|
| [11] |
Diether K B, Malloy C J, Scherbina A. 2002. “Differences of Opinion and the Cross Section of Stock Returns” ,Journal of Finance, 57(5): 2113～2141.
|
| [12] |
Gleason C A, Lee C M C. 2003. “Analyst Forecast Revisions and Market Price Discovery” ,Accounting Review, 78(1): 193～225.
|
| [13] |
Gu Z, Wu J S. 2003. “Earnings Skewness and Analyst Forecast Bias” ,Journal of Accounting and Economics, 35(1): 5～29.
|
| [14] |
Hong H, Kubik J D. 2003. “Analyzing the Analysts Career Concerns and Biased Earnings Forecasts” ,Journal of Finance, 58(1) : 313～351.
|
| [15] |
Lang M H, Lins K V, Miller D P. ADRs. 2003. “Analysts, and Accuracy: Does Cross Listing in the United States Improve a Firm's Information Environment and Increase Market Value？” ,Journal of Accounting Research, 41(2): 317～345.
|
| [16] |
Hribar P, McInnis J. 2012. “Investor Sentiment and Analysts' Earnings Forecast Errors” ,Management Science, 58(2): 293～307.
|
| [17] |
Huberts L C, Fuller R J. 1995. “Predictability Bias in the US Equity Market” ,Financial Analysts Journal, 51(2): 12～28.
|
| [18] |
Johnson T C. 2004. “Forecast Dispersion and the Cross Section of Expected Returns” ,Journal of Finance, 59(5): 1957～1978.
|
| [19] |
Merkley K, Michaely R, Pacelli J. 2017. “Does the Scope of the Sell-side Analyst Industry Matter？ An Examination of Bias, Accuracy, and Information Content of Analyst Reports” ,Journal of Finance, 72(3): 1285～1334.
|
| [20] |
Payne J L, Thomas W B. 2003. “The Implications of Using Stock-split Adjusted I/B/E/S Data in Empirical Research” ,Accounting Review, 78(4): 1049～1067.
|
| [21] |
Stickel S E. 1991. “Common Stock Returns Surrounding Earnings Forecast Revisions: More Puzzling Evidence” ,Accounting Review: 402～416.
|
| [22] |
Stickel S E. 1992. “Reputation and Performance Among Security Analysts” The Journal of Finance, 47(5): 1811～1836.
|
| [23] |
White H. 1980. “A Heteroskedasticity-consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity” Econometrica: 817～838.
|
|
|
|
