The Accuracy and Informativeness of Management Earnings Forecasts: A Review and Unifying Framework†
The Accuracy and Informativeness of Management Earnings Forecasts: A Review and Unifying Framework†
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管理层盈利预测的准确性和信息性：回顾和统一框架†
DOI：
10.1111/1911-3838.12294
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发表时间：
2022
影响因子：
1.7
通讯作者：
Ewald Aschauer
中科院分区：
文献类型：
--
作者：
Nicolai A. Preussner;Ewald Aschauer
本文综合了有关管理层盈余预测（MF）和适应机制的文献，将现有理论整合到一个统一的框架中，并讨论了 MF 准确性和信息性的主要决定因素。所提出的模型通过强调公司管理层、财务分析师和投资者之间的动态和多时期相互作用来完善现有理论，从而简化对预测周期内复杂关系的评估。此外，我们还分析金融分析师和投资者预期偏见和误导性信息的时间和程度。总体而言，文献综述有力地支持了 MF 的范围和可信度与股票回报、股票流动性和分析师报道范围之间的正相关性。盈利预测往往存在乐观偏差，与预测不确定性、盈利灵活性、财务困境、投资者情绪以及管理者薪酬的股价依赖性呈正相关。公司成长、法律责任和诉讼风险与预测悲观情绪显着相关。我们还发现，MF 的准确性随着之前的预测准确性、公司规模、分析师覆盖范围、分析师协议、管理资格和公司治理水平而提高。此外，投资者并未预见到可预测的预测偏差的全部范围，导致盈利预测和实际盈利公布后股价出现系统性波动。该研究的结果对研究人员、公司经理、投资者、金融分析师和监管机构具有重大影响。尽管管理者可以通过提供精确的、捆绑的和分类的预测来提高预测的可信度，但外部利益相关者应该仔细分析预测的前因和特征，以评估预期 MF 偏差的方向和幅度。
This paper synthesizes the literature on management earnings forecasts (MFs) and adaption mechanisms, combines existing theories into a unifying framework, and discusses the primary determinants of MF accuracy and informativeness. The proposed model refines existing theories by emphasizing the dynamics and multiperiod interactions among firm management, financial analysts, and investors, thereby simplifying the assessment of the complex relations within the forecast cycle. Furthermore, we analyze when and to what extent financial analysts and investors anticipate bias and misleading information. Overall, the literature review provides strong support for a positive correlation between the extent and credibility of MFs, on the one hand, and stock returns, share liquidity, and analyst coverage, on the other hand. Earnings forecasts tend to be optimistically biased, with a positive correlation with forecast uncertainty, earnings flexibility, financial distress, investor sentiment, and the share price dependency of managers' remuneration. Firm growth, legal liability, and litigation risk are significantly associated with forecast pessimism. We also find that MF accuracy increases with previous forecast accuracy, firm size, analyst coverage, analyst agreement, management qualifications, and corporate governance level. Moreover, investors do not anticipate the full extent of predictable forecast bias, leading to systematic share price drifts after the announcement of earnings forecasts and actual earnings. The study's results have substantial implications for researchers, firm managers, investors, financial analysts, and regulators. Although managers may enhance their forecasts' credibility by providing precise, bundled, and disaggregated forecasts, external stakeholders should carefully analyze forecast antecedents and characteristics to assess the direction and magnitude of expected MF bias.