超预期股本扩张与分析师每股盈余预测

卖方分析师的每股盈余预测在实证文献中被广泛使用。该指标同时依赖于分析师对目标公司未来净利润的预测和对目标公司未来股本数量的预测。因此,如果在分析师发布预测后,目标公司的股本数量发生超出分析师预期的扩张,则每股盈余预测将无法代表分析师对目标公司未来基本面的预测。本文构建了“调整后每股盈余预测”指标,该指标可剔除超预期股本扩张对每股盈余预测的影响,真实反映分析师对目标公司未来基本面的预测。本文应用该指标,在两个具体的实证研究场景中证明了,忽略超预期股本扩张的影响可能得出错误的实证结论。本文还进一步指出了三个忽略超预期股本扩张的影响可能导致错误实证结果的研究场景。     

企业无形资产资本化与分析师盈余预测:理论分析与实证检验

与现有的基于"价值相关性"的无形资产研究不同,本文从资本市场最专业的财务报表使用者———证券分析师的视角出发,研究了财务报表对无形资产反映的充分程度,即无形资产资本化对分析师盈余预测的影响,并进行实证检验。检验的结果表明,企业无形资产资本化程度与分析师盈余预测跟随、盈余预测误差、盈余预测分散性皆呈"负相关"关系。企业无形资产资本化程度越高,分析师盈余预测跟随次数越少,分析师盈余预测误差越小,分析师之间的盈余预测分歧越小,并且对于无形资产价值占公司总价值比例较高的公司,这种负相关关系更为显著。     

现金股利政策与未来盈余预测——基于新冠肺炎疫情冲击分离均衡信号检验北大核心CSSCI

利用2020年年初新冠肺炎疫情外生冲击带来的分离均衡场景,本文实证检验中国沪深.两市A股上市公司分红变动与未来盈余的关系。研究发现,未来盈余“较好”公司事前提高了分红水平,而未来盈余“较差”公司则没有正向分红变动,公司分红变动可显著预测未来盈余;进一步研究发现,分析师预测修正受到分红变动的正向影响,分红的信号传递被分析师所捕捉并用以修正公司估值。     

证券分析师VS统计模型:证券分析师盈余预测的相对准确性及其决定因素

本文使用2005年35家券商对我国上市公司做出的每股盈余预测数据,考察了证券分析师盈余预测相对于统计模型的相对准确性及其决定因素。我们发现,我国证券分析师做出的盈余预测,同以年度历史数据为基础的统计模型得出的盈余预测相比,预测误差较小,证券分析师盈余预测具有一定的优势;但同某些以季度历史数据为基础的统计模型得出的盈余预测相比,预测误差较大,证券分析师盈余预测不具有优势。我们同时考察了决定证券分析师盈余预测相对准确性的决定因素。我们发现,公司每股盈余的波动性越大,公司上市越晚,跟踪公司的分析师越多,证券分析师的优势就越大。我们的研究对证券分析师以及投资者都有一定的启示作用。     

声誉对分析师预测准确性的影响

本文选择今日投资"天眼"明星分析师评选为依据,将样本分为明星和非明星分析师两组,实证检验了分析师声誉对预测准确度的影响。分析师声誉以是否获得"明星分析师"为标准,预测准确度以每股盈利的预测值和实际值之差度量。本文运用了均值统计和多元线性回归进行比对分析,结论是分析师声誉对预测准确度没有显著影响。我国投资者不应仅以明星分析师分析报告作为投资资料唯一来源,而应立足基本面分析,综合考虑市场信息。     

盈余质量、制度环境与分析师预测

本文通过研究2003-2007年证券分析师对我国上市公司盈余预测的特征,发现公司财务报告中的盈余信息质量对分析师预测表现具有显著的影响。结果表明,公司盈余质量越高,分析师预测越准确,分歧度越小。研究还发现,宏观制度环境对分析师盈余预测同样有显著的正面影响。上市公司所处地区的制度环境越好,分析师盈余预测的准确度越高,分歧度越小。同时,完善的制度环境在一定程度上能够削弱盈余信息质量对于分析师预测表现的影响。本文的结论对于加强上市公司财务信息监督和健全宏观制度环境具有参考价值。     

定向增发中的会计业绩效应与财务分析师信息预示

本文以2007-2013年907家定向增发公司为研究样本,考察了定向增发对资源使用效益衡量指标净资产收益率(ROE)与用之于市场决策转化指标每股收益(EPS)之间逻辑关系的影响,以及考察了定向增发环境下财务分析师对增发公司业绩变化的预示能力。研究发现,定向增发存在"EPS业绩效应",即在ROE下降情形下,随着定向增发规模的增大,公司EPS会越来越高。这为解释定向增发存在短期正向宣告效应长期回报不佳现象提供了新思路。尽管定向增发通常意味着信息不对称程度更高,但我们研究发现财务分析师盈余预测调整与公司EPS变化基本一致,并且其预测向上调整预示了定向增发公司有一个更好的未来会计业绩,这表明财务分析师预测活动可作为公司管理层信息披露的替代。     

高铁能提升分析师盈余预测的准确度吗?——来自上市公司的证据

本文搜集了2006-2016年中国201个地级市高铁开通的情况,并匹配了A股1,244家上市公司的面板数据,利用双重差分(DID)模型,研究了高铁开通对证券分析师盈余预测的影响。研究结果显示:高铁通车之后,分析师盈余预测的精准度显著提升,分歧度和乐观度显著下降。进一步考察高铁发挥作用的内在机制,发现高铁开通显著增加了对沿线公司进行实地调研的分析师数量及人均调研次数。高铁开通对分析师盈余预测的影响存在异质性,影响主要体现在信息处理成本较低的企业、公司治理水平较好的企业以及分析师面临买方压力较小的企业中。动态地来看,高铁开通对分析师盈余预测的影响主要体现在通车两年以后。此外,在利用工具变量法、控制飞机出行以减少内生性问题之后,上述结论仍稳健。这说明高铁的开通改善了资本市场的信息环境,使得分析师能够更好地扮演信息中介的角色。文章较早研究了高铁开通对分析师盈余预测的影响,揭示了高铁在金融市场的信息传导效应。     

“时移势迁”下的分析师盈余预测——基于地方官员变更的经验分析

本文手工收集了2006—2016年我国各地级市市委书记变更数据,实证检验了地方官员变更对分析师盈余预测的影响以及作用机制。研究发现,市委书记变更会显著降低分析师对当地上市公司盈余预测的准确性,而且,相对于本地升迁,外地调任的市委书记对于分析师预测准确性的影响更大。进一步分析显示,地方官员变更对分析师盈余预测准确性的影响对于处在市场化程度较低地区、国有企业和政府管制行业的上市公司更加明显。路径分析表明,官员变更加大了企业的经营不确定性,进而降低了分析师的盈余预测准确性。最后,我们考察发现在官员变更去向为晋升时对分析师盈余预测的影响更显著。     

券商跟踪海外上市公司对国内分析师盈余预测准确性的影响

本文选取分析师对A股上市公司盈余预测数据,在分析师层面研究券商跟踪海外上市公司带来的效应。研究发现,国内券商跟踪海外上市公司后,其国内分析师对同行业A股公司的盈余预测准确性有显著提高,即券商跟踪海外上市公司会给国内分析师带来溢出效应。进一步研究发现,这种溢出效应对于经验丰富的分析师以及跟踪信息环境较差公司的分析师更加显著。本研究对于全面认识券商海外业务的溢出效应及分析师盈余预测准确性的影响因素具有理论和现实意义。     

A Comparative Analysis of Earnings Forecasts in Europe

This study examines the accuracy and bias of financial analysts' EPS forecasts in nine European countries during 1987 to 1995. There are significant differences between the countries which may be due to the differences in earnings behaviour, accounting practices, and the influence of securities markets. An optimistic bias is endemic in European forecasts, consistent with research from the US. Investors who incorporate earnings forecasts in their stock selection procedures may be able to improve returns by explicitly adjusting their models for observed regularities in earnings forecast errors. However, we have shown that these regularities differ in incidence and magnitude across the countries studied, and further research is needed to effectively model these differences.     

CEO stock options and analysts’ forecast accuracy and bias

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.     

Equity premium prediction and the state of the economy

We detect cyclical variation in the predictive information of economic fundamentals, which can be used to substantially improve and simplify out-of-sample equity premium prediction. Economic fundamentals based on stock-specific information (notably the dividend yield) deliver better predictions in expansions. Economic fundamentals based on aggregate information (notably the short rate) deliver better predictions in recessions. Accordingly, a simple forecast combination of one predictor that generates cyclical forecasts and one predictor that generates countercyclical forecasts can deliver statistically significant and economically valuable equity premium predictions in both expansions and recessions. A prominent two-predictor forecast combination that performs well is the dividend yield and the short rate. Strategies designed for ex-ante timing of the business cycle can provide additional economic gains in equity premium prediction.     

Analysts' Rationality and Forecast Bias: Evidence from Sales Forecasts

When optimistic forecasts can improve access to management, rational analysts have incentives to issue optimistically-biased forecasts (Lim, 2001). This paper proposes that the extent of this optimistic forecast bias will depend on the forecast's importance to management. If management attaches less importance to a forecasted measure, analysts should decrease their forecast bias because the expected benefits of issuing optimistic forecasts are less. We examine analysts' earnings and sales forecasts, and predict that analysts' optimistic bias will be greater for earnings than for sales. Results are consistent with our predictions and contribute to the evidence that analysts' forecast bias is rational and intentional.     

分析师预测准确度影响因素的研究

文章以我国2010-2012年深交所数据为样本,基于公司因素的角度对我国分析师预测准确度进行了实证研究。研究发现,分析师所提供的盈余预测偏于乐观,盈余波动性越大以及上市公司信息披露质量越好,则预测准确度越高;而公司规模越大、盈余管理动机越强以及盈余可预测性越差,则伴随着较低的预测准确度。本文的研究结果为提高我国公司财务报告质量、规范分析师行业提供了相应的思路。     

The effect of management earnings forecast characteristics on cost of equity capital

This study uses a framework presented in Hirst, Koonce, and Venkataraman (2008) to assess how differences in management earnings forecast characteristics influence a firm's cost of equity capital. I find that less specific forecasts, pessimistic forecasts, and forecasts that predict a loss for the period are associated with higher cost of equity capital levels and more timely forecasts and forecasts with more information content are associated with lower cost of equity capital levels. Analysis interacting control variables and forecast antecedents with forecast characteristics indicates that the effects forecast characteristics have on cost of equity capital are either enhanced or moderated depending on firm beta, firm size, firm book-to-market ratios, analyst following, prior forecast bias, and earnings quality. The results highlight the importance of interacting key variables when interpreting the market effect of management earnings forecasts.     

Do investor expectations affect sell-side analysts’ forecast bias and forecast accuracy?

We examine the association between investor expectations and its components and sell-side analysts’ short-run quarterly earnings forecast bias and forecast accuracy. To measure investor expectations, we use the Index of Consumer Expectations survey and decompose it into the “fundamental” component related to underlying economic factors (FUND) and the “sentiment” component unrelated to underlying economic factors (SENT). We find that analysts are the most optimistic and the least accurate when SENT is higher. Management long-horizon earnings forecasts attenuate the effects of SENT on forecast optimism and forecast accuracy. Analysts are also the most accurate when FUND is higher. Last, the market places more weight on unexpected earnings when SENT is high. These findings suggest that analysts are affected by investor sentiment and the market reacts more strongly to unexpected earnings when analyst forecasts are the least accurate. The last result potentially explains why prior research (for example, Baker and Wurgler, The Journal of Finance 61:1645–1680, 2006) finds an association between investor sentiment and cross-sectional stock returns.     

Diagnostic Expectations and Stock Returns

We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.     

Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.