投资者日度情绪、订单流不均衡与股票流动性

doi:10.16381/j.cnki.issn1003-207x.2020.1754

中国管理科学 ›› 2023, Vol. 31 ›› Issue (5): 60-70.doi: 10.16381/j.cnki.issn1003-207x.2020.1754

• 论文 • 上一篇

投资者日度情绪、订单流不均衡与股票流动性

尹海员, 吴兴颖

陕西师范大学国际商学院，陕西西安710119

收稿日期:2020-09-11 修回日期:2021-02-01 发布日期:2023-05-23
通讯作者: 尹海员(1979-)，男(汉族)，山东日照人，陕西师范大学国际商学院，教授，博士，研究方向：证券市场微观结构理论，Email: yinhaiyuan@snnu.edu.cn. E-mail:yinhaiyuan@snnu.edu.cn
基金资助:
教育部人文社会科学基金资助项目(22XJA790008)；陕西省自然科学基金资助项目 (2023JCYB622)

Investor Sentiment, Order Flow Imbalance and Stock Liquidity

YIN Hai-yuan, WU Xing-ying

International Business School, Shaanxi Normal University, Xian 710119, China

Received:2020-09-11 Revised:2021-02-01 Published:2023-05-23
Contact: 尹海员 E-mail:yinhaiyuan@snnu.edu.cn

摘要/Abstract

摘要： 本文挖掘东方财富网的股票论坛发帖文本，通过自然语言处理对其进行情感分析，构建了投资者日度情绪指标并探讨其对股票流动性的影响，还分析了订单流不均衡性在其中起到的中介作用。研究发现，投资者情绪对股票流动性具有显著的正向冲击效应，乐观情绪能显著增加股票流动性，而且流动性对投资者情绪的敏感度会随着卖空限制的降低而加强，股票交易订单流的不均衡性在这一冲击过程中起到了部分中介作用。这种影响效应在不同截面特征的股票中存在显著差异，其中高账面市值比和公司规模更大的个股流动性对情绪波动的敏感度较高，而风险溢价较高的个股流动性对情绪的灵敏度较低。研究结论有助于从更高频率视角深入理解投资者情绪对股票流动性的影响机理。

关键词: 投资者情绪；股票流动性；订单流不均衡；中介效应

Abstract: With the development of Web2.0, social media has gradually evolved into an online expression carrier. Different subjects, for their interests, using this channel to create and share content. Individual investors are more willing to express their true feelings through online platforms. This information has significant explanatory power to the stock market, but will not be reflected in the market data. In the process of continuous aggregation and fermentation, it intensifies the sentimental tendency of investors, fundamentally changes the information structure of the stock market.

Key words: investor sentiment; stock liquidity; unbalanced order flow; intermediary effect

中图分类号:

F830.91

尹海员, 吴兴颖. 投资者日度情绪、订单流不均衡与股票流动性[J]. 中国管理科学, 2023, 31(5): 60-70.

YIN Hai-yuan, WU Xing-ying. Investor Sentiment, Order Flow Imbalance and Stock Liquidity[J]. Chinese Journal of Management Science, 2023, 31(5): 60-70.

参考文献

［1］ Mendelson A H. Dealership market: market-making with inventory［J］.Journal of Financial Economics, 1980, 8(1):31-53.
［2］ Kumari J. Investor sentiment and stock market liquidity: evidence from an emerging economy［J］.Journal of Behavioral and Experimental Finance, 2021, 30(6):166-180.
［3］ Antweiler W, Frank M Z. Is all that talk just noise? The information content of internet stock message boards［J］. Journal of Finance, 2004, 59(3):1259-1294.
［4］ Siganos A, Vagenas N E, Verwijmeren P. Face books daily sentiment and international stock markets［J］. Journal of Economic Behavior & Organization, 2014, 107(10):730-743.
［5］ Solomon D H, Soltes E, Sosyura D. Winners in the spotlight: media coverage of fund holdings as a driver of flows［J］. Journal of Financial Economics, 2014, 113(1):53-72.
［6］ Leitch D, Sherif M. Twitter mood, CEO succession announcements and stock returns［J］.Journal of Computational Science, 2017, 21(2):1-10.
［7］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.Yang Jie, Zhan Wenjie, Liu Ruizhi. Media reports, institutional ownership and the no synchronization of stock price fluctuation［J］. Management Review, 2016, 28 (12): 30-40.
［8］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):52-63.Niu Feng, Ye Yong, Chen Xiaodong. Media reports and IPO Pricing—empirical evidence from listed companies on Shenzhen SME Board［J］. Management Review, 2017, 29 (11): 52-63.
［9］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.Jin Xiu, Jiang Shangwei, Yuan Ying. Predictability of investor sentiment and extreme returns based on stock bar information［J］. Management Review, 2018, 30(7): 18-27.
［10］ Avramov D, Cheng S, Hameed A. Time-varying liquidity and momentum profits［J］. Journal of Financial and Quantitative Analysis, 2016, 51(6):1897-1923.
［11］ Chung K H, Chuwonganant C. Market volatility and stock returns: the role of liquidity providers［J］. Journal of Financial Markets, 2018, 37(1):17-37.
［12］刘学文. 中国股市投资者情绪测度指标的优选研究［J］.中国管理科学,2019,27(1):22-33.Liu Xuewen. Research on the optimization of investor sentiment measurement index in Chinese stock market［J］. Chinese Journal of Management Science, 2019, 27(1): 22-33.
［13］ Chiu J, Chung H. The asymmetric sentiment effect on equity liquidity and investor trading behavior in the subprime crisis period: evidence from the ETF market［J］.Journal of Banking&Finance,2012, 36(9):2660-2671.
［14］刘晓星, 张旭, 顾笑贤. 投资者行为如何影响股票市场流动性?—基于投资者情绪、信息认知和卖空约束的分析［J］. 管理科学学报, 2016, 19(10):87-100.Liu Xiaoxing, Zhang Xu, Gu Xiaoxian. How does investor behavior affect stock market liquidity? Analysis based on investor sentiment, information cognition and short selling constraints［J］. Journal of Management Science in China, 2016, 19(10): 87-100.
［15］ Baker M, Stein J C. Market liquidity as a sentiment indicator［J］. Journal of Financial Markets, 2004, 7(3):271-299.
［16］ Asem E, Chung J, Cui X. Liquidity, investor sentiment and price discount of SEOs in Australia［J］. International Journal of Managerial Finance, 2016, 12(1):25-51.
［17］ Bailey W, Cai Jun, Cheung Y. Stock returns, order imbalances, and commonality: evidence on individual, institutional, and proprietary investors in China［J］. Journal of Banking and Finance, 2009, 33(1):1-19.
［18］ Su Yongchern, Huang Hanching, Lin Shiuefang. Dynamic relations between order imbalance, volatility and return of top gainers［J］.Applied Economics,2012, 44(12):1509-1519.
［19］张峥,李怡宗,张玉龙,等.中国股市流动性间接指标的检验-基于买卖价差的实证分析［J］.经济学(季刊),2013,13(1):233-261.Zhang Zheng, Li Yizong, Zhang Yulong, et al. Test of indirect indicators of liquidity in China’s stock market: an empirical analysis based on bid ask spread［J］. China Economic Quarterly, 2013,13 (1): 233-261.
［20］方杰, 温忠麟, 张敏强.基于结构方程模型的多层中介效应分析［J］.心理科学进展, 2014, 22(3):530-539.Fang Jie, Wen Zhonglin, Zhang Minqiang. Multilevel mediating effect analysis based on structural equation model［J］. Advances in Psychological Science, 2014, 22(3): 530-539.
［21］陈其安,雷小燕.货币政策、投资者情绪与中国股票市场波动性:理论与实证［J］.中国管理科学,2017,25(11):1-11.Chen Qian, Lei Xiaoyan. Monetary policy, investor sentiment and volatility of China’s stock market: theory and empirical research［J］. Chinese Journal of Management Science, 2017, 25(11): 1-11.
［22］ Thomas H M, Robert A W. An analysis of intraday patterns in bid/ask spreads for NYSE stocks［J］. The Journal of Finance, 1992, 47(2): 753-764.
［23］ Pagan A R, Sossounov K A. A simple framework for analyzing bull and bear markets［J］. Journal of Applied Econometrics, 2003, 18(1):23-46.

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投资者日度情绪、订单流不均衡与股票流动性

Investor Sentiment, Order Flow Imbalance and Stock Liquidity

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