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.

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.

Managerial Ability and Forecast Accuracy

We examine the relation between managerial ability and management forecast accuracy. We base our analysis on S＆P 500 Composite Index constituents for the period of 2006-2012. Data were collected from Thomson Reuteurs, Compustat and Demerjian, Lev, and McVay （2012）. We find that forecast accuracy is positively associated with managerial ability in the case of sales forecasts. Specifically, more able managers are associated with lower magnitude＇s forecast errors in the case of sales forecasts. Additional analysis finds that managerial ability is immaterial to EPS figures＇ forecast accuracy, i.e., EPS forecasts appear not to be affected by manager＇s superiority. Regarding sales forecasts, the results are consistent with the assertion that managers impact the quality of the delivered management forecasts. Regarding EPS forecasts, the results are in alignment with Demerjian, Lev, Lewis, and McVay （2013） who highlighted that managerial ability is an ability score related to the entire management team.

电信制造业销售预测精度(forecast accuracy)的趋势分析方法——基于数据仓库技术解决方案的研究

电信制造企业中销售预测精度是用来衡量销售人员的预测水平.在企业日常生产活动中,预测人员要根据可能发生的销售合同进行提前预测.这就要求预测人员对销售需求进行很好的估计和度量.在实际的合同交货月所记录的真实出货记录在ERP系统中.于是预测精度的要求由此而来.预测精度是根据产品的实际销售数量和预测数量进行对比分析得出前一个月对当前月的预测精度.再根据不同的预测月不同的权重进行加权平均得出的实际精度.这种指标的衡量意义在预测人员可以此作为参照不断提高预测水平.生产部门和仓储部门可以进行精确计划和合理安排库存.提高准时交货率和减少库存成本.使得企业的资源得到精确配置.预测精度的趋势分析方式基于以上的计算方法加上趋势分析,对产品,客户,地区进行历史预测数据进行展现.提供一个直观的变动趋势来满足不同的级别管理层的考核需要.进行日常跟踪从而提出改进需要.达到资源的最优配置.从而给企业带来管理成本的下降.

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。

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。

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。

Analyst Coverage,Forecasting Bias,and Corporate Innovation:Evidence from China

Due to information asymmetry and strategic innovation,firms often encounter challenges related to insufficient driving forces and low-quality innovation outcomes.Analysts always act as information intermediaries who help foster the advancement of corporate innovation activities and the conversion of innovation output.This study examines the impact of analyst coverage and forecasting bias on corporate innovation,employing data from China A-shared listed firms spanning the period 2007 to 2019.We measure corporate innovation from two perspectives:Input and output.Specifically,we use the ratio of research and development(R&D)expenditure to sales as a proxy for the innovation input and the number of patent citations excluding self-citations to measure innovation output.We find that analyst coverage promotes corporate innovation,which is consistent with the“bright”side of analyst coverage.However,the positive effect of analyst coverage hinges on effectively transmitting and disclosing accurate information to investors in the capital market.Based on this,analysts'forecasting bias includes forecasting dispersion and optimism bias.We find evidence that an increase in analysts'forecast dispersion leads to a decrease in corporate innovation quality.Moreover,this paper presents a novel approach by employing the regression discontinuity method to examine the effect of analyst optimistic bias on firm innovation.The empirical findings reveal that overly optimistic forecasts by analysts exacerbate innovation quality.These analyses enrich the research on analyst coverage and corporate innovation,providing an empirical basis for improving the capital market with the help of analysts.

预报风强度对火箭最大气动载荷精度影响及建模分析

针对不同预报风强度的精度以及其对应的最大气动载荷预报值精度的研究文献极少。以某地区实况风为基准,分别对不同预报风强度的精度以及其对应的最大气动载荷预报值精度特征进行了分析,并利用多元线性回归方法建立了订正模型,结果表明在预报日数第1~11天,预报风强度越大,预报风精度及其对应的最大气动载荷预报值精度越高;利用多元线性回归方法可提高最大气动载荷预报值精度,且预报风强度越小,最大气动载荷预报精度提高越明显。这些发现在火箭发射前的飞行保障及安全决策方面具有参考价值。

辽西半干旱区玉米产量预报方法对比研究

基于辽西半干旱区阜蒙县1986-2016年气象要素与玉米产量、发育期数据,使用产量丰歉相似年法、关键气象因子法、作物模型法开展了玉米产量预报研究,分析比较了3种产量预报方法的趋势预报正确率和定量预报准确率,结果表明,产量丰歉相似年法虽然可以实现玉米产量动态预报,但大概率法和加权分析法对玉米产量趋势的预报正确率均较低(33.3%~66.7%),其中加权平均法准确率高于大概率法的,但二者总体预报准确率都不高,且表现不稳定,不能满足业务服务需求。关键气象因子法提高了2014和2015年(生长季降水偏少年)的产量预报准确率,2年的产量预报趋势正确率为100%,产量预报准确率平均为89.5%。作物模型法随着发布预报日期的推迟,产量预报值更接近实际产量,降水正常年份预报效果好于降水偏少年份的预报效果。综上,将关键气象因子法与作物模型法相结合是准确预报半干旱区玉米产量的有效办法。两种方法相结合,对2011-2016年的产量预报准确率平均值达91.6%,能够满足业务服务需求。

集合预报降雨信息在寸滩-三峡区间的精度评价和可利用性评估

降雨数值预报在预防极端天气和其他气象事件方面具有重要作用。通过提供可靠的概率预报,可以更准确地描述预报结果的不确定性,为决策者提供科学依据,从而提高应用价值和经济价值。以寸滩-三峡区间为研究对象,根据TIGGE资料中的ECMWF和NCEP 2种模式,对2020-2022年(5-10月)逐日降水集合预报信息的精度进行评估。首先,采用Talagrand分布和Brier评分来评估不同预见期的集合预报能力;然后,采用贝叶斯模型平均(Bayesian model averaging,BMA)来修正集合预报;最后,对不同预见期的BMA修正值和实际降雨值之间的误差进行分析。结果显示:ECMWF和NCEP 2种模式的预报能力随预见期的增加逐渐下降,在不同预见期下,通过BMA修正后的降雨预报值具有更高的精度。

Can ChatGPT reduce human financial analysts’optimistic biases?

This paper examines the potential of ChatGPT,a large language model,as a financial advisor for listed firm performance forecasts.We focus on the constituent stocks of the China Securities Index 300 and compare ChatGPT’s forecasts for major financial performance measures with human analysts’forecasts and the realised values.Our findings suggest that ChatGPT can correct the optimistic biases of human analysts.This study contributes to the literature by exploring the potential of ChatGPT as a financial advisor and demonstrating its role in reducing human biases in financial decision-making.

基于CEEMD-ITSA-BiLSTM组合模型的短期负荷预测

准确预测电力系统短期负荷有助于灵活规划系统资源、合理安排机组工作调度以及提高系统运行效率。针对负荷预测精度问题,文中提出了一种基于CEEMD-ITSA-BiLSTM(Complete Ensemble Empirical Mode Decomposition-Improved Tunicate Swarm Algorithm-Bidirectional Long Short-Term Memory)的短期负荷预测模型。对时序性负荷数据进行CEEMD分解,得到若干个平稳的IMF(Intrinsic Mode Function),并对每个IMF进行BiLSTM建模预测。为了提高BiLSTM的精度,采用ITSA算法对BiLSTM的隐含层节点数、学习率和训练次数等超参数进行参数寻优,建立CEEMD-ITSA-BiLSTM负荷预测模型。文中以实际负荷数据进行仿真实验,对比了单一BiLSTM和不同算法优化的BiLSTM模型,结果表明CEEMD-ITSA-BiLSTM模型的RMSE(Root Mean Square Error)、MAE(Mean Absolute Error)和MAPE(Mean Absolute Percentage Error)误差指标相比于BiLSTM模型分别提高了48.54%、51.32%和44.78%,显著低于其他对比模型。

基于GM-Markov模型的南宁吴圩国际机场货邮吞吐量预测

为帮助广西南宁吴圩国际机场科学制定货运相关政策并为机场管理部门提供科学的数据支持,以南宁吴圩国际机场2011—2022年货邮吞吐量数据为基础,构建序列累加生成数列,建立预测模型并进行模型误差分析及精确度检验。研究将灰色理论模型的相对误差划分为5个状态区间,分别应用灰色预测模型和灰色马尔科夫(GM-Markov)模型预测南宁吴圩国际机场2011—2022年的货邮吞吐量,并与实际吞吐量进行比较。研究表明:使用灰色理论模型,南宁市吴圩国际机场2011—2022年的货邮吞吐量预测平均误差为0.04;应用GM-Markov的方法,预测平均误差为0.008。显然GM-Markov预测模型要比传统的灰色预测模型的精度高,能大幅降低波动性较大的时间序列的预测误差,尤其适用于中短期的预测。由此根据GM-Markov预测模型,计算得出南宁吴圩国际机场2023—2026年的货邮吞吐量预测值。

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。