考虑信息强度的因子定价模型及其实证研究

摘要/Abstract

摘要：

本文首次基于信息数量和信息质量两个维度构建信息强度指数，研究其对股票截面收益的影响。在构建包含信息强度因子的五因子定价模型基础上，对比分析不同信息强度股票组合收益，研究信息强度与收益和风险的关系。研究发现：基于信息数量和信息质量两个维度构建的信息强度指数对股票截面收益具有较强的解释能力，信息强度是影响股票收益的重要风险因子，考虑信息强度因子的五因子定价模型能更好地解释股票收益；信息强度与超额收益呈反向变动关系，信息强度对收益的敏感系数为负，高信息强度组的超额收益最低、敏感系数绝对值最小，低信息强度组的超额收益最高、敏感系数绝对值最大，按信息强度高低构建的股票组合能够满足不同风险偏好投资者的需求。研究结论为投资者投资决策、监管者完善市场建设及学者们更深入研究资产定价问题提供参考。

关键词: 信息强度, 信息质量, 五因子定价模型, 超额收益, 敏感系数

Abstract:

This paper develops an information intensity index based on two dimensions: information quantity and information quality, to study its effect on stock cross section earnings. Based on a pricing model of five factors, including information intensity, this paper analyzes the return of stock portfolio of different information intensity to study the relationships among information intensity, earnings and risk. The results show that the information intensity index based on the two dimensions has advantages in explaining stock return. Further evidence indicates that information is an important risk factor affecting portfolio returns and the five-factor pricing model considering information strength can better explain the portfolio returns. Specifically, information intensity shows a negative relationship with excess returns and information risk that the information intensity is stronger, the excess return is lower, the information risk is lower. Furthermore, stock portfolio considering the information intensity can meet the needs of investors of different risk preferences. The conclusion can provide advice for investors to invest, supervisors to perfect market construction and scholars to study asset pricing problems.

Key words: information intensity, information quality, five factor pricing model, excess return, sensitive coefficient

金秀, 姜尚伟, 苑莹. 考虑信息强度的因子定价模型及其实证研究[J]. , 2020, 32(5): 14-25.

Jin Xiu, Jiang Shangwei, Yuan Ying. Empirical Research of Factor Pricing Model Considering Information Intensity[J]. , 2020, 32(5): 14-25.

参考文献

[1] Cen L., Chan K., Dasgupta S., et al. When the Tail Wags the Dog:Industry Leaders, Limited Attention, and Spurious Cross-Industry Information Diffusion[J]. Management Science, 2013,59(11):2566-2585
[2] 宋献中,胡珺,李四海.社会责任信息披露与股价崩盘风险——基于信息效应与声誉保险效应的路径分析[J].金融研究, 2017,(4):161-175
[3] Larcker D. F., So E. C., Wang C. C. Y. Boardroom Centrality and Firm Performance[J]. Journal of Accounting and Economics, 2013,55(3):225-250
[4] 游家兴,吴静.沉默的螺旋:媒体情绪与资产误定价[J].经济研究, 2012,47(7):141-152
[5] 易志高,潘子成,茅宁,等.策略性媒体披露与财富转移-来自公司高管减持期间的证据[J].经济研究, 2017,52(4):166-180
[6] Solomon D. H., Soltes E. F. Managerial Control of Business Press Coverage[R]. Working Paper, University of Southern California and Harvard Business School, 2012
[7] 宿成建.现金流信息、现金流风险与股票收益定价研究[J].管理科学学报, 2016,19(5):102-103
[8] 李丹,王丹.供应链客户信息对公司信息环境的影响研究——基于股价同步性的分析[J].金融研究, 2016,(12):191-206
[9] 孔翔宇,毕秀春,张曙光.财经新闻与股市预测——基于数据挖掘技术的实证分析[J].数理统计与管理, 2016,35(2):215-224
[10] 黄润鹏,左文明,毕凌燕.基于微博情绪信息的股票市场预测[J].管理工程学报, 2015,29(1):47-52
[11] 张维,翟小鹏,邹高峰,等.市场情绪、投资者关注与IPO破发[J].管理评论, 2015,27(6):160-167
[12] 杨洁,詹文杰,刘睿智.媒体报道、机构持股与股价波动非同步性[J].管理评论, 2016,28(12):30-40
[13] Kim S., Kim D. Investor Sentiment from Internet Message Postings and the Predictability of Stock Returns[J]. Journal of Econmic Behavior&Organization, 2014,107(4):708-729
[14] Zhao X. F. Does Information Intensity Matter for Stock Return?Evidence from Form 8-K Filings[J]. Management Science, 2016,63(5):1-23
[15] 王欢,张静,许萍丽.基于手机媒体的政府信息发布权威性研究[J].情报科学, 2011,29(3):364-368
[16] Porter M. E., Millar V. E. How Information Gives You Competitive Advantage[J]. Harvard Business Review, 1985,63(8):149-162
[17] Glazer R. Marketing in an Information-Intensive Enviroment:Strategic Implications of Knowledge as an Asset[J]. Journal of Marketing, 1991,55(4):1-19
[18] 刘育良,陈志刚,孙大兴,等.磁头-磁盘接触作用力对磁记录层信息强度影响规律的定量研究[J].物理学报, 2015,64(23):290-299
[19] 韩红桂,乔俊飞,薄迎春.基于信息强度的RBF神经网络结构设计研究[J].自动化学报, 2012,38(7):1083-1090
[20] 苗虹,孙金生,葛世伦,等. ERP分步云化的选择方法:信息强度视角[J].系统工程理论与实践, 2016,36(3):750-759
[21] 蔡淑琴,秦志勇,李翠萍,等.面向负面在线评论的情感强度对有用性的影响研究[J].管理评论, 2017,29(2):79-86
[22] Fama E. F., French K. R. Commom Risk Factors in the Returns on Stocks and Bonds[J]. Journal of Financial Economics, 1993,33(1):3-56
[23] Carhart M. M. On Persistence in Mutual Fund Performance[J]. Journal of Finance, 1997,52(1):57-82
[24] Fama E. F., French K. R. A Five-factor Asset Pricing Model[J]. Journal of Financial Economics, 2015,116(1):1-22
[25] 杨炘,陈展辉.中国股市三因子资产定价模型实证研究[J].数量经济技术经济研究, 2003,20(12):137-141
[26] 王宜峰,王燕鸣.投资者情绪在资产定价中的作用研究[J].管理评论, 2014,26(6):42-55
[27] Lasswell H.社会传播的结构与功能[M].北京:中国传媒大学出版社出版, 2012
[28] Fama E. F. Random Walks in Stock Market Prices[J]. Financial Analysts Journal, 1965,21(5):55-59
[29] 翟华云.应计质量影响因素理论分析[J].财会通讯, 2009,(36):76-78
[30] Easley D., OHara M. Information and the Cost of Capital[J]. The Journal of Finance, 2004,59(4):1553-1583
[31] Bertomeu J., Marinovic I. A Theory of Hard and Soft Information[J]. Accounting Review, 2016,91(1):1-20
[32] Fama E. F., MacBeth J. D. Risk, Return, and Equilibrium:Empirical Tests[J]. Journal of Political Economy, 1973,81(3):607-636
[33] Newey W. K., West K. D. A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix[J]. Econometrica, 1987,55(3):703-708
[34] Fang L., Peress J. Media Coverage and the Cross-Section of Stock Returns[J]. The Journal of Finance, 2009,65(4):2023-2052
[35] Fama E. F., French K. R. Dissecting Anomalies[J]. The Journal of Finance, 2008,63(4):1653-1678