主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

中国管理科学 ›› 2021, Vol. 29 ›› Issue (5): 55-64.doi: 10.16381/j.cnki.issn1003-207x.2019.0747

• 论文 • 上一篇    下一篇

股票分析师的羊群行为对公司股价同步性的影响分析

张大永1, 刘倩2, 姬强3,4   

  1. 1. 西南财经大学经济与管理研究院, 四川 成都 611130;
    2. 中国邮政储蓄银行, 北京 100033;
    3. 中国科学院科技战略咨询研究院, 北京 100190;
    4. 中国科学院大学公共政策与管理学院, 北京 100049
  • 收稿日期:2019-05-24 修回日期:2020-02-23 出版日期:2021-05-20 发布日期:2021-05-26
  • 通讯作者: 姬强(1982-),男(汉族),山东威海人,中国科学院科技战略咨询研究院,研究员,研究方向:能源金融、预测建模与风险管理,E-mail:jqwxnjq@163.com. E-mail:jqwxnjq@163.com.
  • 基金资助:
    国家自然科学基金资助项目(72022020,71974159,71974181);中国科学院青促会项目(Y7X0231505);引智基地111项目(B16040)

The Impacts of Analyst's Herding Behavior on Stock Price Synchronicity

ZHANG Da-yong1, LIU Qian2, JI Qiang3,4   

  1. 1. Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu 611130, China;
    2. Postal Savings Bank of China, Beijing 100033, China;
    3. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
    4. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-05-24 Revised:2020-02-23 Online:2021-05-20 Published:2021-05-26

摘要: 股价"同涨同跌"是我国股票市场的一种重要现象。多股集体"暴跌"会给公司和投资者造成严重的损失,因而股价同步性的问题受到监管者和学术界的广泛关注。本文以2010-2017年股票分析师对上市公司做出的预测为主要研究对象,验证了股票分析师的羊群行为与公司股价同步性间的关系,讨论了机构投资者和市场情绪的作用机制。实证结果表明我国股票分析师的羊群行为是"非信息驱动"的真羊群行为,这种行为降低了市场上的特质信息含量,从而增加了公司的股价同步性。上述关系在熊市中更为显著,并且分析师与机构投资者之间的利益冲突会加剧其羊群行为对股价同步性的影响。本文的研究对理解如何降低股价崩盘风险、提高我国股票市场的信息传递效率具有十分重要的理论和实践意义。

关键词: 股票分析师, 羊群行为, 股价同步性, 动态羊群指数

Abstract: Price synchronicity has been studied intensively in the literature and it is particularly relevant to the Chinese stock market. Synchronicity means that stock prices tend to move up or down together, which has happened regularly in the past. This price co-movement, especially during market turmoil, can increase systemic risks and cause significant losses to companies and investors. A market with strong price synchronicity is also considered as a less efficient market, and thus damaging the market's further development. Understanding the fundamental causes of stock price synchronicity is therefore important for policymakers and practitioners.
Among all attempts to explain this phenomenon in the existing literature, herding behaviors of analysts are especially interesting aspect to explore. Analysts are very important participants in the stock market in terms of discovering and spreading information in the market. These people often have strong academic and industrial background, and thus able to extract critical information for companies. Their recommendation and research results are frequently used by companies and investors.
In the behavioral finance literature, herding is a typical issue that causes price deviating from fundamentals. It is also found that herding behavior applies to analyst. Given their importance as an information intermediary, herding behavior among analyst can potentially help explain price synchronicity. Extending from the current literature, and to explore how and to what extent herding in analyst drives price co-movement, an empirical investigation on these issues is provided.
To be specific, four testable hypotheses are set. The main hypothesis on whether herding in analyst contributes to the price synchronicity in China is tested. The second to test what the real driving forces for the herding behavior in analyst are, in other words, whether the herding is driven by information or non-information. Following the existing literature, institutional investors, and market sentiment are included into our modelling framework to further explore the role of herding analysts on price synchronicity. It is expected to see, first, the higher institutional investors, the stronger herding impacts; and second, herding role is stronger in bearish market conditions.
Our empirical analysis uses listed A share firms in China from 2010 to 2017. The original data are collected from CSMAR, Wind and RESSET database. Morck et al. (2000) is followed to construct price synchronicity. Analyst's herding index is the key variable of interest. It is constructed according to Gleason and Lee (2003), who use analyst's forecast of future earnings per share (EPS) and whether the analyst make adjustment towards the average value of all analysts.
Through regression analysis and a set of robustness check, the following conclusions are given. First, it is confirmed that herding among analysts can limit their information discovery role, and thus a driving factor of stock price synchronicity. Second, our analysis using a non-star analysts' herding index show that herding among analyst in China is essentially non-information driven. Third, institutional share can reduce synchronicity and potentially dominate the role from analysts. And last, the fourth hypothesis is confirmed that herding analysts have stronger role in pushing price co-movements in bearish market.
While providing interesting addition to the current literature on understanding stock price synchronicity, this paper has also some important policy implications. Regulating analyst and reforming compensation mechanisms of analysts are needed to give stronger incentives for them to provide objective reports. Further reinforce institutional investors' share in certain companies and improving information disclosure can alleviate price synchronicity and avoid negative role played by analysts. Overall, efforts are needed to establish incentive compatible mechanisms for efficient information distribution in the market.

Key words: analyst, herding behavior, stock price synchronicity, dynamic herding index

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