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.

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.

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.

The effect of affiliated analysts on stock recommendations: Evidence from share pledges in China

We use the share pledge context in China to examine how affiliated analysts whose securities companies are pledgees of share pledge firms issue stock recommendations on these listed firms.We find that their recommendations are more optimistic than those of non-affiliated analysts,and they are more likely to issue Buy and Add recommendations,suggesting that they issue optimistic rating reports for share pledge firms due to their conflicts of interest.We also find a dynamic adjustment in the stock recommendation behavior of these analysts,and their probability after issuing optimistic stock recommendations is significantly reduced before and after the years that the affiliation relationship between them and share pledge firms both began and ended.These affiliated analysts continue to issue optimistic stock recommendations after visiting the share pledge firms if they work in the same location as the firms,or if they are star analysts among New Fortune’s‘‘top five analysts,"and when the information transparency of the share pledge firms is higher.In addition,the optimistic stock recommendation behavior of affiliated analysts is more significant in our sample of firms with high share pledge ratios and downward stock price pressure.The earnings forecast quality of affiliated analysts is also found to be lower,and they are less inclined to downgrade stock recommendations for these share pledge firms.Buy recommendations issued by both nonaffiliated and affiliated analysts can bring cumulative excess returns in the short event window,but those issued by affiliated analysts are significantly negative in the long-term event window,and significantly lower than those issued by non-affiliated analysts.Overall,our study shows that affiliated analysts issue optimistic rating reports on share pledge firms due to conflicts of interest,which leads to decision-making bias in investors and thus decreases the stock price crash risk of the firms.Our findings further reveal the economic consequences of share pledging and extend our understanding of the behavior of analysts in a conflict of interest situation from the share pledge perspective.

Does an abnormal change in deferred tax assets interfere with analysts' earnings forecasts?

In 2007,China adopted the single balance sheet liability method for tax accounting,but its shortcomings have emerged.I sample A-share listed companies from 2007 to 2018 to study whether an abnormal change in deferred tax assets interferes with analysts’earnings forecasts and find that an abnormal change in deferred tax assets increases the error and divergence of these forecasts.Compared with a negative abnormal change in deferred tax assets,a positive abnormal change has a greater impact on earnings forecasts.Additionally,the level of corporate governance,audit quality and analysts’professional ability have moderating effects on the correlation between an abnormal change in deferred tax assets and earnings forecasts.However,an abnormal change in deferred tax liabilities does not have a significant impact on that correlation.

Firm-specific information, analysts' superiority and investment value

Using a sample of Chinese security analysts’recommendations from 2005 to2010,we examine the source of analysts’superiority and the investment value of their recommendations.Using a calendar-time portfolio approach,we find that,on average,analysts’recommendations are valuable and that analysts are better at analyzing and transferring firm-specific information than market-wide or industry-level information.In addition,we show that the investment value of recommendations increases as firm-specific information becomes more important in stock pricing.Our empirical results are useful in guiding investors and helping brokerage houses to evaluate the output of research departments.

The Impact of Competition on Analysts’Forecasts:A Simple Agent-Based Model

This paper builds an agent-based model to study the impact of analyst competition on analyst optimism.Two strategies(a catering strategy and a pressure strategy)are used to model analysts conflicts of interest between listed corporations and institutional clients.The finding suggests that the relationship between competition and analyst optimism is nonlinear.Low-level competition generates more analyst unbiased forecasts.However,the condition of no competition or high-level competition generates more analyst optimistic forecasts.The empirical test also confirms that analysts issue less biased earnings forecasts under the condition of low-level competition.

Stock index adjustments and analysts' forecast optimism:A quasi-natural experiment on the CSI 300 Index

As stock index adjustments comprise a basic system of capital market,their potential influence on analysts’earnings forecasts is worthy of research.Based on a research sample of 23 adjustments to the CSI 300 Index from June 2007 to June 2018 and the backup stocks announced during the same period,this study examines the impact of additions to stock index on analysts’forecast optimism using a staggered difference-in-differences model.The research results show that after stocks are added to the stock index,analysts’earnings forecast optimism about these stocks increases significantly.Cross-sectional analysis indicates that this increase is more significant when the market is bullish,institutional ownership is low,the ratio of listed brokerage firms is low,star analyst coverage is low,firms show seasoned equity offering activity,the ratio of analysts from the top five brokerage firms ranked by commission income is high,and the analysts’brokerage firms are shareholders.However,analystlevel tests find that analysts’ability helps to reduce the impact of additions to stock index on earnings forecast optimism.Furthermore,additions to stock index significantly increase analyst coverage and forecast divergence.Economic consequences tests find additions to stock index significantly increases stock price synchronization,which is partly mediated by analysts’earnings forecast optimism.This study enriches the literature on the impact of basic capital market systems and analyst behavior.The findings suggest that investors should rationally evaluate analysts’earnings forecasts for stocks added to the stock index and obtain further information from various channels to improve asset allocation efficiency.

Analysts Unfazed by Price Jump

Despite consumer inflation figures hitting 5.6% in July - a 1o-year high - few analysts are showing major concerns. Most analysts whom CIB spoke with said that the moderately high rates of bank loans and fixed asset investment are better signals of the overall health of the Chinese economy than the inflation rate, which is largely cyclical.

川西北某拟建高速公路隧道口高位危岩特征及危险性评价

某拟建高速公路隧道口位于川西北岷江河谷地带,区内地形地貌复杂、新构造运动强烈,高位危岩极其发育,严重威胁拟建公路隧道口。本文基于无人机倾斜摄影及现场调查,采用Rockfall Analyst软件模拟落石三维运动特征。结果表明:(1)危岩区坡度较陡,岩性以砂质千枚岩为主,岩体破碎、节理裂隙发育,稳定性较差,变形破坏模式以滑移式、坠落式为主;(2)落石运动过程以自由飞落、碰撞弹跳以及贴坡运动为主,最大速率33 m/s,最大弹跳高度14.5 m,最大能量约3 100 kJ,在运动过程有大部分会落至隧道洞口上方,危险性高-极高;(3)建议清除隧道洞口上方孤石、危岩,设置锚索(杆)框格梁进行处治,隧道进口接长明洞,同时加强监测。本研究成果对川西北地区公路、铁路工程地质选线、勘察设计及防灾减灾具有一定指导和借鉴意义。

基于近红外光谱快速鉴别硫熏山药

为了防虫、延长储存时间,山药常被熏硫,构建硫熏中药材快速鉴别方法具有重要意义。本研究通过模拟市场上山药的熏蒸过程,在实验室制备了一批模拟样品,采集了山药的近红外光谱图,并利用化学计量学方法进行分析。利用TQ Analyst软件分析不同硫熏浓度及时间条件下山药的近红外光谱特征,建立硫熏山药定性分析模型。研究表明,该模型的准确率高达100%。通过近红外光谱和化学计量学模型的组合,能快速识别山药是否被硫熏,此研究为快速鉴别山药硫熏情况提供了新路径。*通讯作者。In order to prevent pests and prolong storage time, Chinese yam is often fumigated with sulfur. In this work, a batch of simulated samples were prepared in the laboratory by simulating the fumigation process of yam on the market. Near-infrared (NIR) spectra of Yam were then recorded and analyzed by Chemometrics methods. Based on the spectral characteristics of Chinese yam under different sulfur-fumigated concentration and time, a qualitative analytical model was established by TQ Analyst software. The research shows that the accuracy of the model is as high as 100%. The combination of NIR spectroscopy and Chemometrics model can rapidly identify whether yam has been to exposed to sulfur. This study provides a new way for rapid identification of sulfur-fumigated yam.

基于ArcView 3D Analyst的土地复垦三维景观模拟

随着GIS技术的发展,其在土地复垦中的应用越来越广泛。利用GIS技术可以进行复垦土地的适宜性评价、规划设计等。在GIS所提供资料的基础上,建立起复垦规划后的具有真实感的三维景观模型,对评价规划方案、展示规划效果、通过三维可视化的形式反映土地复垦前后的景观变化具有重要意义。ArcView3DAnalyst是ArcViewGIS的扩充模块。对ArcView3DAnalyst作了简单介绍,然后阐述了在ArcView3DAnalyst基础上建立土地复垦三维景观模型的方法,最后结合实例建立了1个土地复垦三维景观模型。

基于无人机和Rockfall Analyst的崩塌落石特征分析与运动学模拟--以察雅县崩塌落石为例

崩塌落石是高陡边坡的一种浅表部破坏方式,突发性强且随机性大,是严重的地质灾害之一。分析崩塌落石特征,并对落石进行运动学模拟对于灾害防治具有重大意义。以往的研究对于崩塌落石的运动学模拟大多基于二维模拟软件,人为控制了运动方向,具有一定的干扰性,部分独立的三维模拟软件计算时考虑的参数较多,增加了模拟难度。在调查方式上,无人机技术凭借机动灵活、工作效益高成为一种趋势。因此,文章以昌都市察雅县北西侧斜坡为研究区,结合现场调查和无人机三维倾斜摄影技术,调查分析了斜坡崩塌落石特征,通过三维模型获取了岩体结构面信息,分析了岩体稳定性;基于GIS环境下三维落石模拟软件Rockfall Analyst,根据历史崩塌轨迹采用参数反演的方法获得研究区斜坡下垫面参数,对物源区块石进行了运动轨迹、速度和弹跳高度的数值模拟。结果表明:(1)斜坡上主要存在三处物源区,岩体整体受三组主控结构面控制,不同结构面之间的组合破坏和冻融侵蚀影响下的岩体差异性分化是造成岩体失稳的主要因素;(2)通过模拟的运动轨迹确定了落石的威胁范围,弹跳高度和速度轨迹可为崩塌落石灾害防治的位置和防治措施的选择上提供地质依据。

面向对象影像信息提取软件Feature Analyst和eCognition的分析与比较

介绍了目前最为先进的两种面向对象的影像信息提取软件Feature Analyst和eCognition。通过对两种软件设计思路、工作流程和软件特殊性的对比分析,探讨了影像信息自动提取的发展趋势。

基于DEM和ArcGIS的挖填土方量计算在净水厂设计中的应用

净水厂设计过程中,对原始地表向设计地表转化这一过程进行挖填土方量计算是一项重要的工作。在对国内外各领域现有的挖填土方量计算方法分析研究的基础上,利用DEM和ArcGIS空间分析模块,提出一种可用于净水厂设计中挖填土方量计算的新方法。将其应用于一个净水厂的设计实例,结果表明,利用该方法进行挖填土方量计算是高效和可行的。

基于ArcView 3D Analyst的矿山环境治理恢复的三维景观模拟

利用GIS所提供的三维可视化功能,建立起矿山治理恢复后的具有真实感的三维景观模型,对评价规划方案、展示规划效果、通过三维可视化的形式反映矿山环境治理恢复前后的景观变化具有重要意义。ArcView 3D Analyst是ArcView GIS的扩充模块,在ArcView 3D Analyst基础上建立了采空塌陷区的回填、削坡设计及其治理后矿山绿化等矿山治理恢复设计的三维景观模拟。

新的数据挖掘工具——Poly Analyst

给出了数据挖掘工具评价的主要指标 ,结合指标对PolyAnalyst的功能和特点进行了较为详尽的介绍 ,并对PolyAnalyst的关键算法进行了分析。对从事数据挖掘软件系统开发和数据挖掘算法研究的人员有所借鉴。

基于景观结构的农村居民点整治优化研究

运用Arc GIS的空间分析和统计功能以及Patch Analyst的定量分析方法,分析疏附县农村居民点的空间特征、农村居民点与自然条件和经济社会条件的关系,并运用多因子综合评价法,建立农村居民点空间格局优化。结果表明,疏附县的农村居民点布局受海拔高度、坡度、河流、水浇地、城镇和园区的综合影响。疏附县农村居民点分为优先发展区、保留发展区、限制发展区3种类型。