Customer Information Disclosure and Analyst Forecasts : Empirical Evidence from Analysts' Perspective

Based on the company's disclosure of key customer information,the impact of corporate customer concentration on analyst forecast was studied,and we further studied the impact of detailed customer names on analyst forecasts. It is found that:(i) customer concentration significantly affects the accuracy of analyst forecasts. The higher the customer concentration is,the lower the accuracy of analyst forecasts is;(ii) Voluntary disclosure of customer names can provide incremental information to analysts and mitigate the negative impact of customer concentration on the accuracy of analyst forests;(iii) further research has found that the incremental information brought by the state-owned enterprises' disclosure of the customer names to analysts is more obvious; disclosure of customer names by companies with high environmental uncertainty is more likely to be of concern to analysts; and star analysts have a higher ability to interpret customer names than non-star analysts.

Mandatory CSR disclosure and analyst forecast properties:Evidence from a quasi-natural experiment in China

Based on a quasi-natural experiment that mandates a subset of listed firms to issue standalone corporate social responsibility(CSR)reports,we examine whether mandatory CSR disclosure improves analysts’information environment.We focus on two properties of analysts’earnings forecasts:forecast error and forecast dispersion.We find that the mandatory issuance of standalone CSR reports is related to less forecast error and less dispersed forecasts,and the effect varies with the firm-level information environment and provincelevel marketization.Additional tests show that the improvement in forecast properties is mainly driven by CSR reports that i)are of high quality and ii)contain more long-term-oriented information than other CSR reports.Our findings provide evidence that mandatory CSR disclosure plays an important informational role for financial analysts.

Labor protection,information disclosure and analyst forecasts:Evidence from China's Labor Contract Law

Labor protection increases employees’stability and strengthens their monitoring role,improving firms’information environment and increasing analysts’earnings forecast accuracy.Using the implementation of China’s Labor Contract Law as a quasi-natural experiment,we find that labor protection significantly improves analyst forecasts.This positive impact is stronger when agency problems are weaker,board independence is greater,corporate reputation is better and industry competition is more intense.Enhanced labor protection significantly reduces firms’business risk and accrual-based earnings management,decreases stock price synchronicity and increases market pricing efficiency.Our findings of significant impacts of China’s Labor Contract Law on analysts’forecasting behaviors offer important guidance for promoting the development of the Chinese capital market and policy making in labor protection.

Information environment,market-wide sentiment and IPO initial returns:Evidence from analyst forecasts before listing

Measuring the information environment of firms using analyst(price)forecast bias and forecast dispersion before listing,we empirically examine the interactive influence of the information environment and market-wide sentiment on the initial returns of initial public offerings(IPOs).We find the smaller the analyst forecast bias/dispersion,the lower the effect market-wide sentiment has on IPO initial returns.This finding indicates that information asymmetry is a basic reason for noise trading occurs and demonstrates the positive effect of financial analysts during IPOs.In addition,the effect of analyst forecasts is more pronounced during periods of rising markets and when IPO prices are not regulated.

Theoretical explanations to security analysts＇ forecast bias

As the representative of mature investors, security analysts＇ recommendations are guidance for most investors, However, a great deal of studies nearly draws the consistent conclusion, i.e. they are not as smart as we imagine, or the market doesn＇t trust their recommendations so much. The existence of optimistic bias in their recommendations has been supported by empirical data widely. Hence these make many papers to explore the reasons and try to give theoretical explanations. Based on prior researches, this paper mainly compares two theoretical models both based on mathematical methods.

Earnings disaggregation and analysts＇ forecasts

Accounting concepts dictate that separately disclosed components should contain separate useful information. This paper examines the relations between income statement components and analysts＇ earnings forecasts and forecast errors. Regressions explaining earnings forecasts using earnings components provide a better fit than regression using just aggregate income to explain forecasts. We interpret this as consistent with the hypothesis that analysts use incremental information in components not available in aggregate income. However, additional tests based on predictability of forecast errors indicate that analysts do not incorporate all information available in components into earnings forecasts. In addition, this inefficiency appears to increase at longer forecast horizons.

New European Union＇s Requirements and IFRS Practice Statement ＂Management Commentary＂： Does MD＆A Disclosure Quality Affect Analysts＇ Forecasts？

The Management Discussion and Analysis （MD＆A） is a mandatory document under the European Union＇s （EU） law. In 2003, the EU issued Directive 2003/51/EC, which broadened the information that firms have to provide in their MD＆A, and in 2010 the International Accounting Standards Board （IASB） issued the International Financial Reporting Standards （IFRS） Practice Statement ＂Management Commentary＂, a non-binding guidance for the presentation of this document. The aim of this paper is to examine the relationship between MD＆A disclosure quality and properties of analysts＇ forecasts. In fact, although most studies found that financial analysts mainly refer to financial statement data in forecasting earnings, there are few researches highlighting the importance of MD＆A disclosures for financial analysts. On this basis, Ramnath, Rock, and Shane （2008） called for researches in order to better understand the relationship between the information really used by analysts and their forecasts. To assess the quality of MD＆A disclosures, we developed a multidimensional measure on the basis of the EU requirements and the IFRS Practice Statement, and then we regressed this variable on both forecast accuracy and dispersion. The findings show that our measure of MD＆A disclosure quality is significantly and positively related to forecast accuracy. We conducted other analyses in order to better understand the previous relationship and we found that, if we analyze the different information contained in the MD＆A statement, financial analysts consider useful accounting and financial data in forecasting earnings. These results enhance our understanding of the role of MD＆A disclosures in the wide set of information that firms provide to financial statement users.

直面挑战:审计师数字化专长是否有助于提高审计质量?

借鉴审计师行业专长的度量方法,将数字化客户占比较高的审计师定义为数字化专长审计师,并检验在数字化变革过程中,积极参与数字化审计并取得数字化审计经验的审计师是否能够取得更好的审计结果。结果发现数字化审计专长审计师在数字化市场领域能够带来更优的审计质量,并且他们的特殊技能带来的积极作用能够被资本市场的投资者和分析师识别和认可(股价同步性更低且分析师预测更精准)。该结论为在数字化变革中,审计师如何能动应对大样本档案提供了证据,并为实务中事务所发展数字化审计提供了一些启示。

实体企业脱实向虚与分析师盈余预测质量——雾里看花还是甄别有道?

当前,实体经济“脱实向虚”倾向较为明显,立足于监管部门日益重视分析师研报质量的现实背景,选取2007—2019年间我国非金融企业作为研究样本,探究实体企业脱实向虚是否以及如何影响分析师盈余预测质量。研究表明:实体企业脱实向虚显著降低了分析师盈余预测质量;机制检验发现,企业脱实向虚通过降低企业信息透明度进而降低了分析师盈余预测质量;进一步研究表明,良好的公司治理和高质量的外部独立审计能削弱企业脱实向虚对分析师盈余预测质量的负面影响,而机构投资者持股则会强化其负面效应。研究从资本市场信息中介视角丰富了企业脱实向虚的经济后果,对政府监管部门引导企业回归主业及提高资本市场的信息效率具有一定启示作用。

审计师与客户间地理距离对分析师预测的影响研究

区位作为制约信息传递的基础性因素,天然地影响着外部经济主体的信息获取成本及监督成本。审计与客户间地理距离差异如何影响审计监督效力一直颇受学者关注。本文基于2017-2021年事务所至企业注册地的距离数据,实证检验了审计与客户间地理距离差异对分析师预测准确度的影响。结果表明,审计师与客户地理临近能够通过提升审计质量、降低大股东侵占行为来提升分析师预测准确度。该提升效果在两权分离度越严重的样本中更加明显;在被审计单位和事务所交通便利、审计师具有行业专长的样本中,这种提升效果会被削弱。本文的研究从地理经济学视角丰富了审计与客户信息差异的经济后果研究。

线上销售能否改善资本市场信息环境——基于分析师盈余预测的证据

基于2015—2019年上市公司通过互联网平台进行线上销售的独特数据,本文研究了线上销售对分析师盈余预测的影响。研究发现:(1)上市公司进行线上销售显著降低了分析师盈余预测误差和分歧度,提升了分析师盈余预测质量,且上述结果在仅保留线上销售行业和PSM匹配后的样本、采用Heckman两阶段模型等方式缓解内生性问题后仍然成立;(2)线上销售对分析师盈余预测质量的提升作用在分析师公开获取信息渠道较少、获取信息成本较高时更为显著;(3)机制检验发现,线上销售可以通过降低盈余波动,或者抑制盈余管理以改善公司盈余信息质量,进而降低分析师盈余预测误差和分歧度。研究结果表明,线上销售不仅增加了分析师获取公司特质信息的来源,而且一定程度上改善了盈余信息质量,有助于分析师发挥资本市场信息中介的重要作用,提高资本市场效率。

MD&A纵向文本相似度与分析师盈余预测准确性

注册制下,信息的真实、准确、完整是投资者合理判断证券价值的关键,分析师在信息作用于股价这一过程中扮演着重要的信息中介角色,而年报所披露的信息对分析师盈余预测至关重要。以2012—2021年沪深A股上市公司为样本,探究了管理层讨论与分析(MD&A)纵向文本相似度对分析师盈余预测准确性的影响。研究发现,MD&A纵向文本相似度越高,分析师盈余预测准确性越低,证实了“增量信息”假说。异质性分析表明,这种影响显著存在于规模小、高科技行业、媒体关注度低的公司中,并且公司位于市场化程度低省份时受此影响更大。进一步研究发现,MD&A纵向文本相似度越高,分析师盈余预测的正向偏差越大。此外,分析师盈余预测准确性的下降会进一步降低资本市场的信息效率。因此,上市公司应重视文本信息披露,避免披露内容样板化;分析师和监管部门应加强对上市公司文本信息披露的监督,优化资本市场信息环境。

分析师的疲劳、预测质量与股票收益——来自中国资本市场的证据

分析师的决策疲劳是否导致预测质量下降是业界关注的问题,本文对中国A股市场中分析师疲劳与预测质量关系进行研究,经过对2006—2023年A股市场卖方分析师个股研究报告中的盈余预测进行数据统计和分析,研究发现:分析师的决策疲劳与盈余预测误差呈正向关系,即随着一周内发布预测的增加,分析师对公司盈余预测误差也在增大。分析师在决策疲劳严重时发布的预测会预示着未来个股中长期收益降低,盈余预测误差在这一关系中充当部分中介变量。决策疲劳引起的较低股票收益与市场信息不对称相关。

ESG改善对企业劳动投资效率的提升作用研究

企业ESG表现的改善,能够强化内部控制,优化信息环境,进而可以通过缓解委托代理冲突和加强外部监督来提高劳动投资决策的科学性和有效性,实现劳动投资效率的提升。采用沪深A股上市公司2009—2022年的数据分析发现:ESG表现改善可以显著提升企业的劳动投资效率,该结论在经过缓解内生性、变量处理、排除非劳动投资影响等一系列稳健性检验后依然成立;ESG表现改善主要通过优化企业的雇佣行为来提升劳动投资效率,即以减少雇佣(而非增加解雇)的方式抑制劳动投资过度,以增加雇佣(而非减少解雇)的方式缓解劳动投资不足;ESG表现改善能够通过降低代理成本和提高分析师预测质量两条路径来提高企业劳动投资效率,并对信息披露质量较高的企业和劳动密集度较高的企业具有更为显著的劳动投资效率提升效应。因此,企业应积极增加ESG投资,并通过提高自身的信息披露质量促进分析师预测质量提升,通过降低代理成本减少非效率劳动投资行为,以有效提升劳动投资效率。

地区诚信与分析师盈利预测准确性:来自中国A股上市公司的证据

地区诚信作为我国非正式制度的重要组成部分,能够有效监督和约束上市公司行为。以2007—2018年中国沪深A股上市公司为研究对象,从北大法宝各地级市诈骗案判决文书中获取构造年度地级市层面诚信水平衡量指标的数据,进而探究地区诚信对分析师盈利预测准确性的影响。结果表明:(1)地区诚信水平越高,分析师对该地区上市公司盈利预测的分歧度和平均误差越小,这种作用在国有企业、内部治理水平低和金融发展程度低的地区样本中更明显,表明地区诚信可以部分替代所有制、内部治理水平和金融发展程度对分析师盈利预测准确性的作用。(2)机制检验发现,地区诚信通过提高上市公司信息披露质量来降低分析师盈利预测的分歧度和平均误差。因此,应完善社会诚信体系建设,营造良好的营商环境和氛围,提升地区诚信水平,降低信息不对称程度和减少分析师盈利预测误差,进而推动资本市场高质量发展。

行业特定知识转移与分析师预测质量:来自券商机构并购的证据

当前频发的“研报门”事件使得如何提升分析师预测质量成为学术界的热点话题。并购作为券商获取外部知识资源的有效途径,是分析师提高业务水平的重要手段。为此,借助券商机构并购事件构建多时点DID模型,基于知识转移视角探究了行业特定知识对于分析师预测质量的影响。研究结果表明:券商机构并购能够有效改善分析师预测质量,降低分析师预测偏误和预测分歧;且这一改善效应在吸收合并与控股合并的并购事件中更为明显。进一步研究发现,当客户公司地理距离邻近、分析师知识差距较大以及工作年限较短时,并购后分析师预测质量的改善效果越明显。基于知识转移的视角,明晰了分析师预测质量的影响因素与作用机制,对于监管机构制定和完善有关券商并购重组的政策具有重要参考价值。

投资者付费评级机构跟踪能改善股票市场信息质量吗——来自分析师预测的证据

“投资者付费”模式能够提高债券市场信息效率,本文研究了其对股票市场信息质量的影响。本文利用2010年投资者付费评级机构中债资信成立这一外生冲击,以分析师预测度量股票市场信息效率,发现投资者付费评级机构的跟踪降低了分析师预测偏误、分歧度与乐观偏差。上述结论对一系列替换设定稳健。机制上,投资者付费评级机构跟踪提高了企业的信息披露质量,进而影响分析师预测表现。在控制了信用评级质量改善与投资者付费评级机构自有信息等潜在机制后,信息披露质量改善的机制仍然存在。进一步看,分析师跟踪人数并没有减少,分析师预测的公共信息增多,而投资者付费评级提高分析师预测表现的作用在拥有公共信息少的分析师组中更加显著;这意味着信用评级机构向分析师提供了可以利用的公共信息。本文为债券和股票市场的信息传递提供了直接的证据,同时也为政府监管部门加强债券市场基础设施建设、引入双评级制度及提高投资者付费评级跟踪比例来促进股票资本市场与多层次资本市场发展提供了理论支持。

知识产权自愿性信息披露、分析师预测分歧度与股价崩盘风险

近年来,知识产权自愿性信息披露颇受重视。而知识产权自愿性信息披露对股票市场影响的研究对于企业明确知识产权自愿性信息披露的重要性、维持股票市场的稳定健康发展具有重要意义。本文基于大数据文本挖掘思想测度上市公司的知识产权自愿性文本信息披露水平,并基于此实证检验知识产权自愿性信息披露对股票市场股价崩盘风险的影响。研究发现:知识产权自愿性信息披露能够显著降低上市公司的股价崩盘风险,而这种关系在非国有企业和制造业企业中更为显著。分析师预测分歧度在知识产权自愿性信息披露与股价崩盘风险之间发挥显著的中介作用。进一步研究发现,知识产权优势信息和风险信息的披露对于股价崩盘风险的降低具有显著作用,而知识产权内容信息披露对股价崩盘风险的降低作用并不显著,再次对知识产权优势信息和风险信息的机制检验发现,分析师预测分歧度依旧发挥显著的中介作用。

经济政策不确定性、ESG评级与分析师预测准确度

选用2012—2021年沪深A股非金融上市公司作为研究样本,探讨经济政策不确定性是否会影响分析师预测准确度,以及ESG评级在经济政策存在不确定性时对分析师预测准确度之间的关系中所起的作用。研究结果表明,经济政策不确定性越高,分析师预测准确度越低,且上市公司较优的ESG评级水平会缓冲经济政策不确定性对分析师预测准确度的负向影响。进一步研究发现,分析师预测准确度的下降表现为分析师会做出更加乐观的盈余预测,在影响机制分析中发现,更为良好的内部控制质量和更高的媒体关注度能够缓解经济政策不确定性带给分析师预测准确度的负向影响,最后从政府和监管者、上市公司、证券分析师3个方面提出相应对策建议。