分析师能降低股价同步性吗——基于研究报告文本分析的实证研究
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摘要
股价同步性是衡量股票市场资源配置效率的重要指标。党的十九大报告提出,要"增强金融服务实体经济能力"。在这一要求下,探索如何降低股价同步性,提升金融市场合理配置资源的能力具有重要意义。本文借助支持向量机的文本分类方法,通过机器学习度量了2009—2015年中国A股上市公司的分析师研究报告中公司特质信息,研究证券分析师报告内容对股价同步性的影响。研究发现,分析师报告中公司特质信息含量越高,所关注公司的股价同步性越低;当公司所面临的信息不对称问题更加严重、分析师报告影响力更大时,这一负向关系更加显著;进一步研究发现,分析师的能力越强,研究报告中公司特质信息含量越丰富,其盈余预测准确性也更高;分析师降低股价同步性的机制是因为公司特质信息含量高的报告更受投资者关注,能引起更强烈的市场反应,使得股价更多地吸收公司特质信息。以上主要发现在控制样本选择偏差、变更主要变量衡量方式、变换实证模型后依然稳健。本文首次在对分析师报告进行信息分类的基础上,研究分析师传递的具体信息对股价同步性的影响,不仅丰富了股价同步性影响因素的研究,同时从公司特质信息的角度丰富了分析师报告信息含量的研究,具有重要的理论与实践意义。
Stock price synchronicity is an important indicator to measure the efficiency of resource allocation in the stock market. The report of the 19 th National Congress of the Communist Party of China proposed to"enhance the ability of financial market to serve the real economy." Under this requirement, it is of great significance to explore how to reduce stock price synchronicity and improve the ability of financial markets to allocate resources rationally. This paper adopts a textual classification method based on machine learning which called Support Vector Mechine to measure the firm-specific information in analyst reports of Chinese A-share listed companies from 2009 to 2015, and to study their impact on the stock price synchronicity. The paper finds that there is a negative correlation between the firm-specific information of analysts' reports and the stock price synchronicity. The negative correlation is more pronounced when information asymmetry is more severe between firms and investors, and when the reports are more influential. This paper further finds that there would be more firm-specific information in the report if the analysts are more skilled. The earning forecast would be more accurate if the report contains more firm-specific information. Finanlly, this paper finds that the mechanism for analysts reducing stock price synchronicity is because investors pay more attention on reports with more firm-specific information, thus they spurred additional market reaction and lead to the integration of information. The results are still pronounced after controlling the sample selection bias, changing the measurments for main variables, and changing the empirical model. For the first time, this paper classifies the information of analyst reports, to study the impact of specific information transmitted by analysts on stock price synchronicity. This paper enriches the research on the factors that affect stock prices and literature on the information content of analyst reports, which has theoretical and practical meanings.
Stock price synchronicity is an important indicator to measure the efficiency of resource allocation in the stock market. The report of the 19 th National Congress of the Communist Party of China proposed to"enhance the ability of financial market to serve the real economy." Under this requirement, it is of great significance to explore how to reduce stock price synchronicity and improve the ability of financial markets to allocate resources rationally. This paper adopts a textual classification method based on machine learning which called Support Vector Mechine to measure the firm-specific information in analyst reports of Chinese A-share listed companies from 2009 to 2015, and to study their impact on the stock price synchronicity. The paper finds that there is a negative correlation between the firm-specific information of analysts' reports and the stock price synchronicity. The negative correlation is more pronounced when information asymmetry is more severe between firms and investors, and when the reports are more influential. This paper further finds that there would be more firm-specific information in the report if the analysts are more skilled. The earning forecast would be more accurate if the report contains more firm-specific information. Finanlly, this paper finds that the mechanism for analysts reducing stock price synchronicity is because investors pay more attention on reports with more firm-specific information, thus they spurred additional market reaction and lead to the integration of information. The results are still pronounced after controlling the sample selection bias, changing the measurments for main variables, and changing the empirical model. For the first time, this paper classifies the information of analyst reports, to study the impact of specific information transmitted by analysts on stock price synchronicity. This paper enriches the research on the factors that affect stock prices and literature on the information content of analyst reports, which has theoretical and practical meanings.
引文
[1]陈霄,叶德珠,邓洁.借款描述的可读性能够提高网络借款成功率吗[J].中国工业经济, 2018,(3):174-192.
[2]陈钦源,马黎珺,伊志宏.分析师跟踪与企业创新绩效——中国的逻辑[J].南开管理评论, 2017,(3):15-27.
[3]侯宇,叶冬艳.机构投资者、知情人交易和市场效率——来自中国资本市场的实证证据[J].金融研究, 2008,(4):131-145.
[4]胡军,王甄.微博、特质性信息披露与股价同步性[J].金融研究, 2015,(11):190-206.
[5]黄俊,郭照蕊.新闻媒体报道与资本市场定价效率——基于股价同步性的分析[J].管理世界, 2014,(5):121-130.
[6]金鑫,雷光勇,王文.国际化经营、机构投资者与股价同步性[J].科学决策, 2011,(8):1-21.
[7]李扬.完善金融的资源配置功能——十八届三中全会中的金融改革议题[J].经济研究, 2014,(1):8-11.
[8]李增泉,叶青,贺卉.企业关联、信息透明度与股价特征[J].会计研究, 2011,(1):44-51.
[9]林乐,谢德仁.分析师荐股更新利用管理层语调吗?——基于业绩说明会的文本分析[J].管理世界, 2017,(11):125-145.
[10]刘星,陈西婵.证监会处罚、分析师跟踪与公司银行债务融资——来自信息披露违规的经验证据[J].会计研究,2018,(1):60-67.
[11]孟庆斌,杨俊华,鲁冰.管理层讨论与分析披露的信息含量与股价崩盘风险——基于文本向量化方法的研究[J].中国工业经济, 2017,(12):132-150.
[12]丘心颖,郑小翠,邓可斌.分析师能有效发挥专业解读信息的作用吗?——基于汉字年报复杂性指标的研究[J].经济学(季刊), 2016,(4):1483-1506.
[13]史永,张龙平. XBRL财务报告实施效果研究——基于股价同步性的视角[J].会计研究, 2014,(3):3-10.
[14]徐巍,陈冬华.自媒体披露的信息作用——来自新浪微博的实证证据[J].金融研究, 2016,(3):157-173.
[15]伊志宏,李颖,江轩宇.女性分析师关注与股价同步性[J].金融研究, 2015,(11):175-189.
[16]张斌,王跃堂.业务复杂度、独立董事行业专长与股价同步性[J].会计研究, 2014,(7):36-42.
[17]朱红军,何贤杰,陶林.中国的证券分析师能够提高资本市场的效率吗——基于股价同步性和股价信息含量的经验证据[J].金融研究, 2007,(2):110-121.
[18]朱晓婷,杨世忠.会计信息披露及时性的信息含量分析——基于2002—2004年中国上市公司年报数据的实证研究[J].会计研究, 2006,(11):16-23.
[19]Abarbanell, J. S. Do Analysts’ Earnings Forecasts Incorporate Information in Prior Stock Price Changes[J].Journal of Accounting and Economics, 1991,14(2):147-165.
[20]Bellstam, G., S. Bhagat, and J. A. Cookson. A Text-based Analysis of Corporate Innovation[R]. University of Colorado at Boulder, 2016.
[21]Bushman R. M., J. D. Piotroski, and A. J. Smith. What Determines Corporate Transparency[J]. Journal of Accounting Research, 2004,42(2):207-252.
[22]Chan, K., and Y. C. Chan. Price Informativeness and Stock Return Synchronicity:Evidence from The Pricing of Seasoned Equity Offerings[J]. Journal of Financial Economics, 2014,114(1):36-53.
[23]Chan, K., and A. Hameed. Stock Price Synchronicity and Analyst Coverage in Emerging Markets[J]. Journal of Financial Economics, 2006,80(1):115-147.
[24]Cheng, Q., F. Du, X. Wang, and Y. Wang. Seeing Is Believing:Analysts’ Corporate Site Visits[J]. Review of Accounting Studies, 2016,21(4):1245-1286.
[25]Choi, H. M., and S. Gupta-Mukherjee. Analysts’ Use of Industry-level and Firm-Specific Information:Implications for Information Production[R]. Loyola University Chicago, 2017.
[26]Clement, M. B. Analyst Forecast Accuracy:Do Ability, Resources, and Portfolio Complexity Matter[J]. Journal of Accounting and Economics, 1999,27(3):285-303.
[27]Crawford, S. S., D. T. Roulstone, and E. C. So. Analyst Initiations of Coverage and Stock Return Synchronicity[J]. Accounting Review, 2012,87(5):1527-1553.
[28]Dhaliwal, D. S., S. Radhakrishnan, A. Tsang, and Y. G. Yang. Nonfinancial Disclosure and Analyst Forecast Accuracy:International Evidence on Corporate Social Responsibility Disclosure[J]. Accounting Review, 2012,87(3):723-759.
[29]Drake, M. S., and L. A. Myers. Analysts’ Accrual-related Over-optimism:Do Analyst Characteristics Play a Role[J]. Review of Accounting Studies, 2011,16(1):59-88.
[30]Durnev, A., R. Morck, and B. Yeung. Value-enhancing Capital Budgeting and Firm-specific Stock Return Variation[J]. Journal of Finance, 2004,59(1):65-105.
[31]Easley D., N. M. Kiefer, M. O'hara, and J. B. Paperman. Liquidity, Information, and Infrequently Traded Stocks[J]. Journal of Finance, 1996,51(4):1405-1436.
[32]Franco, G., O. K. Hope, D. Vyas, and Y. Zhou. Analyst Report Readability[J]. Contemporary Accounting Research, 2015,32(1):76-104.
[33]Green, T. C., R. Jame, S. Markov, and M. Subasi. Access to Management and the Informativeness of Analyst Research[J]. Journal of Financial Economics, 2014,114(2):239-255.
[34]Gul, F. A., J. B. Kim, and A. A. Qiu. Ownership Concentration, Foreign Shareholding, Audit Quality, and Stock Price Synchronicity:Evidence from China[J]. Journal of Financial Economics, 2010,95(3):425-442.
[35]Huang, A. H., R. Lehavy, A. Y. Zang, and R. Zheng. Analyst Information Discovery and Interpretation Roles:A Topic Modeling Approach[R]. Hong Kong University of Science and Technology, 2016.
[36]Huang, A. H., A. Y. Zang, and R. Zheng. Evidence on the Information Content of Text in Analyst Reports[J].Accounting Review, 2014,89(6):2151-2180.
[37]Hutton, A. P., A. J. Marcus, and H. Tehranian. Opaque Financial Reports, R2, and Crash Risk[J]. Journal of Financial Economics, 2009,94(1):67-86.
[38]Jiang, X., N. Xu, Q. Yuan, and K. Chan, Mutual-Fund-Affiliated Analysts and Stock Price Synchronicity:Evidence From China[R]. Central University Of Finance and Economics, 2016.
[39]Jin, L., and S. C. Myers. R2around the World:New Theory and New Tests[J]. Journal of Financial Economics, 2006,79(2):257-292.
[40]Kothari, S. P., E. So, and R. Verdi. Analysts’ Forecasts and Asset Pricing:A Survey[J]. Annual Review of Financial Economics, 2016,(8):197-219.
[41]Krishnaswami S., and V. Subramaniam. Information Asymmetry, Valuation, and the Corporate Spin-off Decision[J]. Journal of Financial Economics, 1999,53(1):73-112.
[42]Liu, M. H. Analysts’ Incentives to Produce Industry-level versus Firm-specific Information[J]. Journal of Financial and Quantitative Analysis, 2011,46(3):757-784.
[43]Loh, R. K., and R. M. Stulz. When Are Analyst Recommendation Changes Influential[J]. Review of Financial Studies, 2011,24(2):593-627.
[44]Loh, R. K., and R. M. Stulz. Is Sell-side Research More Valuable in Bad Times[R]. National Bureau of Economic Research, 2014.
[45]Morck, R., B. Yeung, and W. Yu. The Information Content of Stock Markets:Why Do Emerging Markets Have Synchronous Stock Price Movements[J]. Journal of Financial Economics, 2000,58(1-2):215-260.
[46]Muslu, V., M. Rebello, and Y. Xu. Sell-Side Analyst Research and Stock Comovement[J]. Journal of Accounting Research, 2014,52(4):911-954.
[47]Piotroski, J. D., and D. T. Roulstone. The Influence of Analysts, Institutional Investors, and Insiders on the Incorporation of Market, Industry, and Firm-specific Information into Stock Prices[J]. Accounting Review,2004,79(4):1119-1151.
[48]Roll, R. The Stochastic Dependence of Security Price Changes and Transaction Volumes:Implications for the Mixture-of-Distributions Hypothesis[J]. Journal of Finance, 1988,43(3):541-566.
[49]Tan, H., S. Wang, and M. Welker. Analyst Following and Forecast Accuracy after Mandated IFRS Adoptions[J].Journal of Accounting Research, 2011,49(5):1307-1357.
[50]Xu, N., K.C. Chan, X. Jiang, and Z. Yi. Do Star Analysts Know More Firm-specific Information? Evidence from China[J]. Journal of Banking&Finance, 2013,37(1):89-102.
(1)公司特质信息的文本分类具体过程介绍,详见《中国工业经济》网站(http://www.ciejournal.org)公开附件,下同。公司特质信息的分类中,机器学习最后输出的准确度为83.33%。
(1)分析师报告的负面信息含量同样采用文本分析方法衡量,具体过程详见《中国工业经济》网站(http://www.ciejournal.org)公开附件。
(1)关于本文全部变量更详细的描述,请参见附录,详见《中国工业经济》网站(http://www.ciejournal.org)公开附件。
(1)稳健性检验的具体实证结果请参见中国工业经济网站(http://www.ciejournal.org)公开附件。
[2]陈钦源,马黎珺,伊志宏.分析师跟踪与企业创新绩效——中国的逻辑[J].南开管理评论, 2017,(3):15-27.
[3]侯宇,叶冬艳.机构投资者、知情人交易和市场效率——来自中国资本市场的实证证据[J].金融研究, 2008,(4):131-145.
[4]胡军,王甄.微博、特质性信息披露与股价同步性[J].金融研究, 2015,(11):190-206.
[5]黄俊,郭照蕊.新闻媒体报道与资本市场定价效率——基于股价同步性的分析[J].管理世界, 2014,(5):121-130.
[6]金鑫,雷光勇,王文.国际化经营、机构投资者与股价同步性[J].科学决策, 2011,(8):1-21.
[7]李扬.完善金融的资源配置功能——十八届三中全会中的金融改革议题[J].经济研究, 2014,(1):8-11.
[8]李增泉,叶青,贺卉.企业关联、信息透明度与股价特征[J].会计研究, 2011,(1):44-51.
[9]林乐,谢德仁.分析师荐股更新利用管理层语调吗?——基于业绩说明会的文本分析[J].管理世界, 2017,(11):125-145.
[10]刘星,陈西婵.证监会处罚、分析师跟踪与公司银行债务融资——来自信息披露违规的经验证据[J].会计研究,2018,(1):60-67.
[11]孟庆斌,杨俊华,鲁冰.管理层讨论与分析披露的信息含量与股价崩盘风险——基于文本向量化方法的研究[J].中国工业经济, 2017,(12):132-150.
[12]丘心颖,郑小翠,邓可斌.分析师能有效发挥专业解读信息的作用吗?——基于汉字年报复杂性指标的研究[J].经济学(季刊), 2016,(4):1483-1506.
[13]史永,张龙平. XBRL财务报告实施效果研究——基于股价同步性的视角[J].会计研究, 2014,(3):3-10.
[14]徐巍,陈冬华.自媒体披露的信息作用——来自新浪微博的实证证据[J].金融研究, 2016,(3):157-173.
[15]伊志宏,李颖,江轩宇.女性分析师关注与股价同步性[J].金融研究, 2015,(11):175-189.
[16]张斌,王跃堂.业务复杂度、独立董事行业专长与股价同步性[J].会计研究, 2014,(7):36-42.
[17]朱红军,何贤杰,陶林.中国的证券分析师能够提高资本市场的效率吗——基于股价同步性和股价信息含量的经验证据[J].金融研究, 2007,(2):110-121.
[18]朱晓婷,杨世忠.会计信息披露及时性的信息含量分析——基于2002—2004年中国上市公司年报数据的实证研究[J].会计研究, 2006,(11):16-23.
[19]Abarbanell, J. S. Do Analysts’ Earnings Forecasts Incorporate Information in Prior Stock Price Changes[J].Journal of Accounting and Economics, 1991,14(2):147-165.
[20]Bellstam, G., S. Bhagat, and J. A. Cookson. A Text-based Analysis of Corporate Innovation[R]. University of Colorado at Boulder, 2016.
[21]Bushman R. M., J. D. Piotroski, and A. J. Smith. What Determines Corporate Transparency[J]. Journal of Accounting Research, 2004,42(2):207-252.
[22]Chan, K., and Y. C. Chan. Price Informativeness and Stock Return Synchronicity:Evidence from The Pricing of Seasoned Equity Offerings[J]. Journal of Financial Economics, 2014,114(1):36-53.
[23]Chan, K., and A. Hameed. Stock Price Synchronicity and Analyst Coverage in Emerging Markets[J]. Journal of Financial Economics, 2006,80(1):115-147.
[24]Cheng, Q., F. Du, X. Wang, and Y. Wang. Seeing Is Believing:Analysts’ Corporate Site Visits[J]. Review of Accounting Studies, 2016,21(4):1245-1286.
[25]Choi, H. M., and S. Gupta-Mukherjee. Analysts’ Use of Industry-level and Firm-Specific Information:Implications for Information Production[R]. Loyola University Chicago, 2017.
[26]Clement, M. B. Analyst Forecast Accuracy:Do Ability, Resources, and Portfolio Complexity Matter[J]. Journal of Accounting and Economics, 1999,27(3):285-303.
[27]Crawford, S. S., D. T. Roulstone, and E. C. So. Analyst Initiations of Coverage and Stock Return Synchronicity[J]. Accounting Review, 2012,87(5):1527-1553.
[28]Dhaliwal, D. S., S. Radhakrishnan, A. Tsang, and Y. G. Yang. Nonfinancial Disclosure and Analyst Forecast Accuracy:International Evidence on Corporate Social Responsibility Disclosure[J]. Accounting Review, 2012,87(3):723-759.
[29]Drake, M. S., and L. A. Myers. Analysts’ Accrual-related Over-optimism:Do Analyst Characteristics Play a Role[J]. Review of Accounting Studies, 2011,16(1):59-88.
[30]Durnev, A., R. Morck, and B. Yeung. Value-enhancing Capital Budgeting and Firm-specific Stock Return Variation[J]. Journal of Finance, 2004,59(1):65-105.
[31]Easley D., N. M. Kiefer, M. O'hara, and J. B. Paperman. Liquidity, Information, and Infrequently Traded Stocks[J]. Journal of Finance, 1996,51(4):1405-1436.
[32]Franco, G., O. K. Hope, D. Vyas, and Y. Zhou. Analyst Report Readability[J]. Contemporary Accounting Research, 2015,32(1):76-104.
[33]Green, T. C., R. Jame, S. Markov, and M. Subasi. Access to Management and the Informativeness of Analyst Research[J]. Journal of Financial Economics, 2014,114(2):239-255.
[34]Gul, F. A., J. B. Kim, and A. A. Qiu. Ownership Concentration, Foreign Shareholding, Audit Quality, and Stock Price Synchronicity:Evidence from China[J]. Journal of Financial Economics, 2010,95(3):425-442.
[35]Huang, A. H., R. Lehavy, A. Y. Zang, and R. Zheng. Analyst Information Discovery and Interpretation Roles:A Topic Modeling Approach[R]. Hong Kong University of Science and Technology, 2016.
[36]Huang, A. H., A. Y. Zang, and R. Zheng. Evidence on the Information Content of Text in Analyst Reports[J].Accounting Review, 2014,89(6):2151-2180.
[37]Hutton, A. P., A. J. Marcus, and H. Tehranian. Opaque Financial Reports, R2, and Crash Risk[J]. Journal of Financial Economics, 2009,94(1):67-86.
[38]Jiang, X., N. Xu, Q. Yuan, and K. Chan, Mutual-Fund-Affiliated Analysts and Stock Price Synchronicity:Evidence From China[R]. Central University Of Finance and Economics, 2016.
[39]Jin, L., and S. C. Myers. R2around the World:New Theory and New Tests[J]. Journal of Financial Economics, 2006,79(2):257-292.
[40]Kothari, S. P., E. So, and R. Verdi. Analysts’ Forecasts and Asset Pricing:A Survey[J]. Annual Review of Financial Economics, 2016,(8):197-219.
[41]Krishnaswami S., and V. Subramaniam. Information Asymmetry, Valuation, and the Corporate Spin-off Decision[J]. Journal of Financial Economics, 1999,53(1):73-112.
[42]Liu, M. H. Analysts’ Incentives to Produce Industry-level versus Firm-specific Information[J]. Journal of Financial and Quantitative Analysis, 2011,46(3):757-784.
[43]Loh, R. K., and R. M. Stulz. When Are Analyst Recommendation Changes Influential[J]. Review of Financial Studies, 2011,24(2):593-627.
[44]Loh, R. K., and R. M. Stulz. Is Sell-side Research More Valuable in Bad Times[R]. National Bureau of Economic Research, 2014.
[45]Morck, R., B. Yeung, and W. Yu. The Information Content of Stock Markets:Why Do Emerging Markets Have Synchronous Stock Price Movements[J]. Journal of Financial Economics, 2000,58(1-2):215-260.
[46]Muslu, V., M. Rebello, and Y. Xu. Sell-Side Analyst Research and Stock Comovement[J]. Journal of Accounting Research, 2014,52(4):911-954.
[47]Piotroski, J. D., and D. T. Roulstone. The Influence of Analysts, Institutional Investors, and Insiders on the Incorporation of Market, Industry, and Firm-specific Information into Stock Prices[J]. Accounting Review,2004,79(4):1119-1151.
[48]Roll, R. The Stochastic Dependence of Security Price Changes and Transaction Volumes:Implications for the Mixture-of-Distributions Hypothesis[J]. Journal of Finance, 1988,43(3):541-566.
[49]Tan, H., S. Wang, and M. Welker. Analyst Following and Forecast Accuracy after Mandated IFRS Adoptions[J].Journal of Accounting Research, 2011,49(5):1307-1357.
[50]Xu, N., K.C. Chan, X. Jiang, and Z. Yi. Do Star Analysts Know More Firm-specific Information? Evidence from China[J]. Journal of Banking&Finance, 2013,37(1):89-102.
(1)公司特质信息的文本分类具体过程介绍,详见《中国工业经济》网站(http://www.ciejournal.org)公开附件,下同。公司特质信息的分类中,机器学习最后输出的准确度为83.33%。
(1)分析师报告的负面信息含量同样采用文本分析方法衡量,具体过程详见《中国工业经济》网站(http://www.ciejournal.org)公开附件。
(1)关于本文全部变量更详细的描述,请参见附录,详见《中国工业经济》网站(http://www.ciejournal.org)公开附件。
(1)稳健性检验的具体实证结果请参见中国工业经济网站(http://www.ciejournal.org)公开附件。
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