Can Abnormal Local Investor Attention Be Used to Predict Stock Market?

Abstract

Abstract: In this paper, we select 187 listed companies in Growth Enterprise Market as samples and extract more than 1 million posters' addresses from Guba Eastmoney to build a local preference index, i.e., abnormal local investor attention. We test how able abnormal local investor attention is to interpretate and predict stock return, volatility and abnormal trading volume respectively. The results show that abnormal local investor attention significantly positively affects stock returns of that very day and next two days, but there is a reversal over time. In addition, we find that abnormal local investor attention has significant positive influence on volatility of that very day and the next two days, and it has some continuity. Besides, we also find that abnormal local investor attention significantly positively affects abnormal trading volume of that very day and the next two days, but it has a short-term effect and will reverse in the future. The results can not only help better understand how local preference can be used to interpretate and predict stock market, but also provide some decision-making basis for investors and regulators.

Key words: local preference, investor attention, return, volatility, trading volume

Fan Xiaoqian, Yuan Ying. Can Abnormal Local Investor Attention Be Used to Predict Stock Market?[J]. Management Review, 2021, 33(10): 70-80.

References

[1] French K. R., Poterba J. M. Investor Diversification and International Equity Markets[J]. American Economic Review, 1991,81(2):222-226
[2] Coval J. D., Moskowitz T. J. Home Bias at Home:Local Equity Preference in Domestic Portfolios[J]. Journal of Finance, 1999,54(6):2045-2073
[3] Morey M. Preferences and the Home Bias in Trade[J]. Journal of Development Economics, 2016,121:24-37
[4] Broer T. The Home Bias of the Poor:Foreign Asset Portfolios across the Wealth Distribution[J]. European Economic Review, 2017,92:74-91
[5] Wu W. L., Gau Y. F. Home Bias in Portfolio Choices:Social Learning among Partially Informed Agents[J]. Review of Quantitative Finance & Accounting, 2017,48(2):1-30
[6] Eun K. S. Media Bias against Foreign Firms as a Veiled Trade Barrier:Evidence from Chinese Newspapers[J]. American Political Science Review, 2018,112(4):954-970
[7] Schumacher D. Home Bias Abroad:Domestic Industries and Foreign Portfolio Choice[J]. Review of Financial Studies, 2018,31(5):1654-1706
[8] 董大勇,肖作平. 证券信息交流家乡偏误及其对股票价格的影响:来自股票论坛的证据[J]. 管理世界, 2011,(1):52-61
[9] 杨晓兰,沈翰彬,祝宇. 本地偏好、投资者情绪与股票收益率:来自网络论坛的经验证据[J]. 金融研究, 2016,(12):143-158
[10] Huang Y., Qiu H., Wu Z. Local Bias in Investor Attention:Evidence from China's Internet Stock Message Boards[J]. Journal of Empirical Finance, 2016,38:338-354
[11] Kumar L. Local Investor Attention and Stock Returns[D]. Master Thesis, Norwegian School of Economics, 2017
[12] Wang B., Choi W., Siraj I. Local Investor Attention and Post-earnings Announcement Drift[J]. Review of Quantitative Finance & Accounting, 2018,51(1):219-252
[13] Coval J. D., Moskowitz T. J. The Geography of Investment:Informed Trading and Asset Prices[J]. Journal of Political Economy, 2001,109(4):811-841
[14] Ivkovi Z., Weisbenner S. Local Does as Local Is:Information Content of the Geography of Individual Investors' Common Stock Investments[J]. Journal of Finance, 2005,60(1):267-306
[15] Huang Y., Li T. Local Information Advantage, Investor Attention, and Stock Returns[C]. AFA San Fransico Meeting Paper, 2016
[16] 赵静梅,吴风云,罗梅. 投资决策中地区偏好与地区规避的实证研究[J]. 投资研究, 2012,31(1):123-141
[17] Wang J. Home Bias, Exchange Rate Disconnect, and Optimal Exchange Rate Policy[J]. Journal of International Money & Finance, 2010,29(1):55-78
[18] Jacobs H., Weber M. The Trading Volume Impact of Local Bias:Evidence from a Natural Experiment[J]. Social Science Electronic Publishing, 2012,16(4):867-901
[19] Chi S., Shanthikumar D. M. Local Bias in Google Search and the Market Reaction around Earnings Announcements[J]. The Accounting Review, 2017,92(4):115-143
[20] Nieuwerburgh S. V., Veldkamp L. Information Immobility and the Home Bias Puzzle[J]. Journal of Finance, 2009,64(3):1187-1215
[21] Nagel S. Short Sales, Institutional Investors and the Cross-section of Stock Returns[J]. Journal of Financial Economics, 2005,78(2):277-309
[22] Diether K. B., Malloy C. J., Scherbina A. Differences of Opinion and the Cross Section of Stock Returns[J]. Social Science Electronic Publishing, 2002,57(5):2113-2141
[23] 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
[24] 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 Financial Studies, 2008,21(2):785-818
[25] Da Z., Engelberg J., Gao P. In Search of Attention[J]. Journal of Finance, 2011,66(5):1461-1499
[26] 俞庆进,张兵. 投资者有限关注与股票收益——以百度指数作为关注度的一项实证研究[J]. 金融研究, 2012,(8):152-165
[27] 张维,翟晓鹏,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
[28] 金秀,姜尚伟,苑莹. 基于股吧信息的投资者情绪与极端收益的可预测性研究[J]. 管理评论, 2018,30(7):18-27
[29] 孙谦,孙书娜. 投资者关注和股市表现——基于雪球关注度的研究[J]. 管理科学学报, 2018,21(6):60-71
[30] 李心丹,王冀宁,傅浩. 中国个体证券投资者交易行为的实证研究[J]. 经济研究, 2002,(11):54-63
[31] 段江娇,刘红忠,曾剑平. 中国股票网络论坛的信息含量分析[J]. 金融研究, 2017,(10):178-192
[32] Garman M. B., Klass M. J. On the Estimation of Security Price Volatilities from Historical Data[J]. Journal of Business, 1980,53(1):67-78
[33] 张谊浩,李元,苏中锋,等. 网络搜索能预测股票市场吗?[J]. 金融研究, 2014,(2):193-206