财经新闻的话题会影响股票收益率吗？——基于行业板块的研究

›› 2019, Vol. 31 ›› Issue (5): 18-27.

财经新闻的话题会影响股票收益率吗？——基于行业板块的研究

龙文^1,2,3, 毛元丰¹, 管利静¹, 崔凌逍²

1. 中国科学院大学经济与管理学院, 北京 100190;
2. 中国科学院虚拟经济与数据科学研究中心, 北京 100190;
3. 中国科学院大数据挖掘与知识管理重点实验室, 北京 100190

收稿日期:2017-12-29 出版日期:2019-05-28 发布日期:2019-05-31
通讯作者: 毛元丰(通讯作者),中国科学院大学经济与管理学院硕士研究生。
作者简介:龙文,中国科学院大学经济与管理学院、中国科学院虚拟经济与数据科学研究中心、中国科学院大数据挖掘与知识管理重点实验室副研究员,硕士生导师,博士;管利静,中国科学院大学经济与管理学院硕士研究生;崔凌逍,中国科学院虚拟经济与数据科学研究中心博士后。
基金资助:
国家自然科学基金项目（71771204）。

Can Topics in Financial News Impact the Return of Stock Market?——A Research Based on Market Segment

Long Wen^1,2,3, Mao Yuanfeng¹, Guan Lijing¹, Cui Lingxiao²

1. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190;
2. Research Center on Fictitious Economy & Data Science, Chinese Academy of Sciences, Beijing 100190;
3. Key Laboratory of Big Data Mining & Knowledge Management, Chinese Academy of Sciences, Beijing 100190

Received:2017-12-29 Online:2019-05-28 Published:2019-05-31

摘要/Abstract

摘要：

研究新闻对股票市场的影响是当前研究的热点之一，本文使用宏观财经新闻的话题来研究财经新闻对股票收益率的影响。本文使用LDA方法对宏观财经新闻的话题进行提取，并研究新闻话题分布对于行业板块股票收益率的影响，实证结果证实了中国股票市场的"媒体效应"。在此基础上，本文探讨了行业收益率和新闻话题之间的关系，并选取了制造业和金融业两个代表性行业，通过财经新闻话题分布的变化来预测两个行业收益率的情况，策略的结果表明通过财经新闻话题分布来构建预测模型可以获得超额的收益率。

关键词: 财经新闻话题, 股票市场, 媒体效应, LDA

Abstract:

The impact of news on the stock market is one of the recent hot research topics. this paper aims to investigate whether latent topics in financial news can impact the return of the stock market. By introducing text mining techniques and Latent Dirichlet Allocation (LDA) classification method, we extract topics' distribution from comprehensive macroeconomics news and research the impact of financial news on the whole market. Then the relationship of financial topics and return in industry level are further discussed. The empirical study confirms that the distribution of financial topics can affect the distribution of sector return. Accordingly an investment strategy of sector allocation based on topics' distribution is constructed and an obviously higher return can be obtained comparing with random strategy.

Key words: financial news topic, stock market, media effect, LDA

龙文, 毛元丰, 管利静, 崔凌逍. 财经新闻的话题会影响股票收益率吗？——基于行业板块的研究[J]. , 2019, 31(5): 18-27.

Long Wen, Mao Yuanfeng, Guan Lijing, Cui Lingxiao. Can Topics in Financial News Impact the Return of Stock Market?——A Research Based on Market Segment[J]. , 2019, 31(5): 18-27.

参考文献

[1] 许柳英,陈启欢. 公众注意力影响买入行为吗?--基于投资者行为的分析[J]. 上海管理科学, 2005,27(4):39-41
[2] Fand L., Peress J. Media Coverage and the Cross-Section of Stock Returns[J]. Journal of Finance, 2009,64(5):2023-2052
[3] Engelberg J. E., Parsons C. A. The Causal Impact of Media in Financial Markets[J]. The Journal of Finance, 2011,66(1):67-97
[4] Wang J., Ye K. Media Coverage and Firm Valuation:Evidence from China[J]. Journal of Business Ethics, 2015,127(3):501-511
[5] 牛枫,叶勇,陈效东. 媒体报道与IPO公司股票发行定价研究--来自深圳中小板上市公司的经验证据[J]. 管理评论, 2017,29(11):50-61
[6] Narayan P. K., Bannigidadmath D. Does Financial News Predict Stock Returns? New Evidence from Islamic and Non-Islamic Stocks[J]. Pacific-Basin Finance Journal, 2017,42:24-45
[7] Seasholesa M. S., Wu G. Predictable Behavior, Profits, and Attention[J]. Journal of Empirical Finance, 2007,14:590-610
[8] Tetlock P. C. All the News That's Fit to Reprint:Do Investors React to Stale Information?[J]. Review of Financial Studies, 2011,24(5):1481-1512
[9] 汪昌云,武佳薇,孙艳梅,等. 公司的媒体信息管理行为与IPO定价效率[J]. 管理世界, 2015,(1):118-128
[10] 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
[11] Forni M., Gambetti L., Lippi M., et al. Noisy News in Business Cycles[J]. American Economic Journal:Macroeconomics, 2017,9(4):122-52
[12] Rogers J. L., Skinner D. J., ZechmanS. L. C., The Role of the Media in Disseminating Insider-trading News[J]. Review of Accounting Studies, 2016,21(3):711-739
[13] Pan Q., Cheng H., Wu D., et al. Stock Risk Mining by News[C]. Proceedings of the Twenty-First Australasian Conference on Database Technologies-Volume 104. Australian Computer Society, Inc, 2010
[14] Ammann M., Frey R., Verhofen M. Do Newspaper Articles Predict Aggregate Stock Returns?[J]. Journal of Behavioral Finance, 2014,15(3):195-213
[15] Wong F., Liu Z., Chiang M. Stock Market Prediction from WSJ:Text Mining via Sparse Matrix Factorization[C]. Data Mining (ICDM), 2014 IEEE International Conference on. IEEE, 2014
[16] Ingle V., Deshmukh S. Hidden Markov Model Implementation for Prediction of Stock Prices with TF-IDF Features[C]. International Conference on Advances in Information Communication Technology & Computing. ACM, 2016
[17] Shynkevich Y., McGinnity T. M., Coleman S., et al. Stock Price Prediction Based on Stock-specific and Sub-industry-specific News Articles[C]. Neural Networks (ijcnn), 2015 International Joint Conference on. IEEE, 2015
[18] 饶育蕾,谢倩倩,王建新. 媒体关联与新闻报道偏差--来自我国上市公司的经验证据[J]. 管理评论, 2016,28(9):194-205
[19] 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,(7):141-152
[20] Li Q., Wang T. J., Li P., et al. The Effect of News and Public Mood on Stock Movements[J]. Information Sciences, 2014,278:826-840
[21] Kim S. H., Kim D. Investor Sentiment from Internet Message Postings and the Predictability of Stock Returns[J]. Journal of Economic Behavior & Organization, 2014,107:708-729
[22] 马俊伟,王铁军,李庆,等. 基于网络信息挖掘的股市影响因素分析[J]. 吉林大学学报(信息科学版), 2014,(3):196-200
[23] Heston S. L., Sinha N. R. News vs. Sentiment:Predicting Stock Returns from News Stories[J]. Financial Analysts Journal, 2017,73(3):67-83
[24] Song Q., Liu A., Yang S. Y. Stock Portfolio Selection Using Learning-to-rank Algorithms with News Sentiment[J]. Neurocomputing, 2017,264:20-28
[25] Li X., Xie H., Wang R., et al. Empirical Analysis:Stock Market Prediction via Extreme Learning Machine[J]. Neural Computing & Applications, 2016,27(1):67-78
[26] Salton G., Buckley C. Term-weighting Approaches in Automatic Text Retrieval[J]. Information Processing &Management, 1988,24(5):513-523
[27] Deerwester S., Dumais S. T., Landauer T. K., et al. Improving Information Retrieval with Latent Semantic Indexing[J]. Information Sciences, 1988,100(1-4):105-137
[28] Hofmann T. Probabilistic Latent Semantic Indexing[C]. International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 1999
[29] Blei D., Andrew N., Jordan M. I. Latent Dirichlet Allocation[J]. The Journal of Machine Learning Research, 2003,3:993-1022
[30] Barber B. M., Odean T. All that Glitters:The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors[J]. Review of Finance Studies, 2008,21(2):785-818