分析师是否会在IPO首日价位预测上迎合投资者情绪

据国内外专家多年研究,投资者情绪对IPO首日价位有着重要影响,作为职业的金融分析师,在对IPO首日价位进行预测的同时,投资者情绪是其不得不考虑的重要因素,但是,笔者认为在IPO首日价位预测上,将投资者情绪作为重要因素即可,不必过于迎合。文章将从投资者情绪与IPO的相互关系入手,最终证明分析师不会迎合但是必须考虑投资者情绪。     

国内外对证券分析师可信度与胜任能力研究述评

国内外学术界在证券分析师研究领域已经做出了大量贡献,学者们利用证券分析师的预测以及股票评级的数据,对证券分析师的盈利预测与股票推荐、市场反应、分析师的经济动机等多个问题进行实证分析。但是,对于证券分析师的预测是否可靠以及投资者是否通过分析师研究报告获利,一直都是争议的热点。该文将从证券分析师可信度与胜任能力两个新视角,对国内外相关文献进行系统梳理,并进一步展望未来的研究方向。     

分析师跟进的决定因素——来自中国证券市场的证据

证券分析师在中国资本市场上的信息中介作用正日益凸显。本文研究了公司规模、业务复杂度、投资风险、股权结构和投资者关系管理水平等因素对分析师跟进决策的影响。在此基础上,进一步运用计数(Count data)计量方法和结构化方程(SEM)对实证结果进行了稳健性检验。研究发现,分析师倾向于跟进那些规模较大、机构持股比例较高且投资者关系管理水平较好的公司,而规避那些投资风险和业务复杂程度较高且内部人持股比例较大的公司。实证结果支持了分析师在中国市场上主要搬演了信息中介的角色,而不是作为信息提供者与企业的直接披露进行竞争。     

分析师应提升职业操守

股市反弹，被唤起希望的不仅是很多被深套的股民，沉寂了一段时间的证券分析师们也出来说话了，开始预测牛年的股市走势。其实，境内股市经过十几年的发展，投资者已经开始成熟，也不像以前那样相信证券分析师了。毕竟，分析师们是拿着机构的高薪，并不一定能给普通投资者带来实质上的收获。     

上市公司年报审计质量与证券分析师盈余预测的实证分析

上市公司年报是资本市场投资者的重要公开信息来源。证券分析师通过分析公共信息及私有信息,向市场提供价值。而过去的文献没有涉及证券分析师的盈余预测行为与年报审计质量的关系。本文采用2002年至2008年A股上市公司作为研究样本,研究了年报审计质量对证券分析师盈余预测行为的影响,研究结果表明,审计质量的高低对证券分析师盈余预测行为有显著的影响,具体表现在高的审计质量增加了分析师的预测跟进人数,提高了分析师预测准确度,降低了分析师预测分歧度。     

我国证券分析师预测的有效性研究

以国内证券分析师的盈利预测报告为对象,以2007年—2009年间上市公司数据为基础,采用回归等方法对分析师预测市场的有效性进行研究。结果表明：国内分析师队伍整体实力仍然欠缺,而且良莠不齐;分析师的短期预测行为较为有效,而且预测值和实际值之间的相关性较强,但长期预测的准确度则有待考虑;分析师对于预测行为已经进行了大幅度调整,但效果不明显,主要是针对前两次的盈利调整对于提高预测准确度没有很大帮助,预测准确性最高的普遍集中在年内最后一季度对该年度的评价分析。实证结果为我国投资者正确使用分析师预测报告提供了一定的参考依据。     

新闻报道是否会影响证券分析师盈利预测分歧——基于信息“噪声”的视角

文章以上市公司的百度新闻报道条数作为新闻报道指标,选择中国A股市场1776家股票作为研究对象,以2004-2012年为样本区间,实证检验上市公司新闻报道对证券分析师盈利预测分歧的作用及其影响机理,结果发现:上市公司的新闻报道与分析师预测分歧之间呈现显著的正相关关系;研究结论支持新闻报道本身含有大量"噪声"成分的解释,而不支持分析师"过度自信"的心理偏差的解释。     

分析师的现金流预测有用吗——基于信息供给的视角

文章考察了证券分析师现金流预测行为对盈余预测质量的影响。研究发现,相对于没有现金流预测的公司,有预测的公司其盈余预测质量更高;现金流预测的次数越多,盈余预测质量越高;以上关系在盈余波动大、经营活动现金流波动大的公司更加明显。这说明我国分析师提供现金流预测信息的确有用,能够帮助分析师改善其盈余预测质量。文章的发现具有重要的实践价值,能够帮助投资者了解分析师现金流预测对盈余预测的影响,从而更有效地利用证券分析师报告进行决策。     

股票价格波动的信息渠道影响研究——基于媒体报道和分析师预测的视角

文章手工收集、整理了2006-2015年中国A股上市公司的媒体报道倾向数据，实证研究了媒体报道正向倾向与分析师乐观预测偏差对上市公司负收益偏态系数的影响。研究表明，虽然媒体报道正向倾向、分析师乐观预测均分别对上市公司股价负收益偏态系数产生显著的负向影响，但是两者的交互项对股价负收益偏态系数的影响则是显著为正，即当媒体报道正面倾向与分析师乐观预测两者共同作用时，将会触发"信息过度关注偏差"机制，从而降低了上市公司股票收益。文章研究还发现，媒体报道、分析师预测和"信息过度关注偏差"机制的作用强度，在市场化程度高地区要明显大于市场化程度低地区，可能的原因是市场化程度高地区的企业更加容易被媒体报道和分析师关注，进而产生更强的关注效应。     

证券分析师利益冲突行为的“前因”与“后果”——来自上证A股的经验证据

本文选用我国上证A股的证券分析师投资评级和股票收益率相关数据(2010.04.30-2011.04.30),对我国证券分析师利益冲突行为的影响因素以及证券分析师投资评级的绩效进行实证研究。结果表明:承销商分析师相对于非承销商分析师的投资建议更为乐观,且券商的承销和经纪业务对证券分析师利益冲突行为有显著性影响;券商声誉和分析师上年声誉对证券分析师的股票投资评级存在明显的抑制效应;积极性的投资评级和分析师本年的声誉与分析师所荐股票的短期超额收益率呈正相关关系。     

“近水楼台先得月”吗？——来自分析师调研的经验证据

分析师实地调研对其盈余预测会产生很大影响，那么，在调研中，分析师接触到更高管理层，对其盈余预测的影响是正向还是负向呢？我们以2015-2018年深交所被分析师调研的上市公司为例，研究发现，分析师实地调研受到管理层重视的程度越高，分析师盈余预测准确度越低，同时预测乐观度越高。进一步的研究表明，公司的盈余波动程度以及调研获取的私有信息的时效性也会影响管理层重视对分析师预测的作用效果。研究结果说明对于分析师实地调研来说，“近水楼台”反而影响了其“先得月”。文章的研究深化了分析师行为的相关文献，给资本市场的监管制度提供了一些政策建议。     

Investors' Misweighting of Firm-Level Information and the Market's Expectations of Earnings

Prior studies use fundamental earnings forecasts to proxy for the market's expectations of earnings because analyst forecasts are biased and are available for only a subset of firms. We find that as a proxy for market expectations, fundamental forecasts contain systematic measurement errors analogous to those in analysts' biased forecasts. Therefore, these forecasts are not representative of investors' beliefs. The systematic measurement errors from using fundamental forecasts to proxy for market expectations occur because investors misweight the information in many firm-level variables when estimating future earnings, but fundamental forecasts are formed using the historically efficient weights on firm-level variables. Thus, we develop an alternative ex ante proxy for the market's expectations of future earnings (“the implied market forecast”) using the historical (and inefficient) weights, as reflected in stock returns, that the market places on firm-level variables. A trading strategy based on the implied market forecast error, which is measured as the difference between the implied market forecast and the fundamental forecast, generates excess returns of approximately 9 percent per year. These returns cannot be explained by investors' reliance on analysts' biased forecasts. Overall, our results reveal that market expectations differ from both fundamental forecasts and analysts' forecasts.     

投资者情绪与股票收益——来自移动互联网的实证研究

移动互联网的高速发展使得越来越多的投资者通过移动互联网获取信息并做出投资决策。文章利用网络爬虫技术收集来自移动互联网的用户讨论信息，研究来自移动互联网的用户情绪对股票收益的影响，实证结果显示：移动互联网用户情绪存在显著不对称特征，其更倾向于表现积极乐观的情绪，且其正负面情绪差异大于PCs端；同时，移动互联网用户情绪越乐观，下一期股票收益越高。进一步实证结果表明，处于较差信息环境（如散户持股较高，分析师跟踪人数较少）的公司，移动互联网用户情绪对其股票收益的影响更加显著；此外，对于流动性越差的公司，移动互联网用户情绪对其股票收益的影响也越显著。文章研究结论为移动互联网时代的投资者优化投资决策提供了新的视角，也是对行为金融学中传统媒体定价领域的重要补充。     

Valuation Implications of Unconditional Accounting Conservatism: Evidence from Analysts' Target Prices

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross‐sectional analysis suggests that more sophisticated analysts and superior long‐term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts' earnings forecasts are negatively associated with the degree of conservatism; that is, analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings‐based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.     

Horizon‐Dependent Underreaction in Financial Analysts' Earnings Forecasts*

This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings‐surprise and other earnings‐related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon‐dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings‐forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreac‐tion tactics, investors buying (selling) stock on the basis of analysts' positive (negative) earnings‐forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives‐based explanation for underreaction provides an alternative to psychology‐based explanations and suggests avenues for further research.     

An Approach to Adjusting Analysts' Consensus Forecasts for Selection Bias*

Many recent empirical studies have concluded that analysts' earnings forecasts are optimistic on average. In this paper, we attempt to undo the effect of one potential source of optimistic bias in analysts' earnings forecasts. Assuming forecasts come from a truncated normal distribution, we estimate the “true” population mean using maximum likelihood. We find that our estimates of earnings are more accurate and less biased than standard measures of sample mean and median. However, we do not find a closer relationship between excess market returns and forecast errors from our maximum likelihood estimate than from the sample mean. This may suggest that the market does not fully incorporate analysts' incentives in generating expectations about future earnings.     

The reaction of Canadian securities to revisions of earnings forecasts*

Abstract. This first study of Canadian securities' earnings forecasts published by Institutional Brokers Estimate System (IBES) focuses on changes in the mean earnings per share forecasts of 159 to 188 companies from 1985 to 1987. Cumulative average residuals are used to detect the announcement effects of large earnings forecast revisions. The main results of this study are the following. First, an investor with access to changes of earnings per share forecasts at the beginning of the month of publication could realize abnormal excess returns. Second, trading strategies based on earnings forecasts revisions can also yield abnormal returns, but the magnitude of the revision, the sector of the company, and the month in which the revision is realized must be considered. Third, when financial analysts' forecasts are published, the informational content of large revisions in forecasts has already been discounted by the market. This result is similar to findings of U.S.– and U.K.–based studies. Finally, large forecasts revisions coincide with a period of abnormal returns. However, the information content of the announcement of forecasts changes cannot be established. The gains are larger if the trade is undertaken before the diffusion of the forecast revision to the IBES subscribers. These results do not vary with the model chosen to predict company returns. This does not necessarily indicate the existence of a market inefficiency because information acquisition and analysis costs, as well as transaction costs, may diminish considerably these abnormal trading gains.     

投资者情绪、会计应计与超额回报——基于中国上市公司的实证分析

以我国上市公司1999至2007年的数据为样本,从行为金融学中投资者情绪的角度,深刻剖析投资者情绪对基于会计应计投资策略获得超额回报的影响。研究发现:1、持有会计应计比例低公司的股票,在投资者情绪低迷时期获得的超额回报会大于投资者情绪高昂时期;同样的,持有会计应计比例高公司的股票,在投资者情绪高昂时期产生的投资亏损要大于投资者情绪低迷时期;2、机构投资者持股比例小的公司的股价,更容易受投资者情绪的影响,因而,基于会计应计策略的超额回报在不同情绪下的差异要大于机构持股比例大的公司。本文试图从投资者情绪的角度,分析其对"应计异象"的影响,并且进一步证明,机构持股大小会干扰其影响的程度。     

Sentiment,Loss Firms,and Investor Expectations of Future Earnings*

This study investigates the mispricing of market‐wide investor sentiment by exploring the relation between sentiment and investor expectations of future earnings. Prior research argues that sentiment‐driven mispricing should be most pronounced for hard‐to‐value firms, such as those reporting losses (Baker and Wurgler 2006). Using investor expectations of future earnings, we provide empirical results consistent with this behavioral finance theory. We predict and find that investors perceive losses to be more (less) persistent during periods of low (high) sentiment; that (in contrast) investors perceive profit persistence to be lower (higher) during periods of low (high) sentiment; and that the effects appear stronger for loss firms relative to profit firms. We also document predictable cross‐sectional variation within losses (with the mispricing mitigated for losses associated with activities expected to generate future benefits), R&D, growth, large negative special items, and severe financial distress. Overall, our results document a new and important channel—investor expectations of future earnings—to explain sentiment‐driven mispricing.