互联网金融背景下个人投资者的发帖行为对股价的影响

随着互联网金融的不断发展，研究财经平台的发帖行为对股价涨跌的影响效应具有现实意义。本文以东方财富网股吧中的互联网金融上市公司的发帖行为为基础，使用2022年1—5月的股票相关数据研究股评数及股评情绪对股价涨跌的影响。研究发现：个人投资者情绪的高涨会使股价上涨，个人投资者情绪增加一个单位使股价上涨的胜算提高了24.69%;而个人投资者的关注度增加会使股价下跌，个人投资者关注度每增加1个单位使股价上涨的胜算降低了46.74%。发帖行为对股价涨跌的影响研究为个人投资者做出更合理的决策、互联网金融行业的发展及股市的平稳发展提供借鉴。     

投资者关注与股价崩盘风险:抑制还是加剧?

本文以2010—2017年中国A股上市公司为样本,考察了投资者关注影响股价崩盘风险的客观表现和传导路径。研究发现,投资者关注度的提高会显著加剧下一期的股价崩盘风险,存在“关注度的崩盘效应”;分组检验发现,关注度的崩盘效应仅在机构持股比例低的公司和市场处于牛市状态下存在;路径检验发现,投资者关注不存在信息路径,没有改善公司信息透明度,但存在部分的情绪路径,提高了股价同步性和投资者情绪,从而加剧了股价崩盘风险。建议监管部门重视投资者关注对股价带来的冲击,通过进一步提高机构者持股比例,缓解情绪过热导致的定价错误程度,降低股价崩盘风险。     

投资者关注、股市表现与套利策略——来自百度搜索量的经验证据

本文采用百度指数作为衡量投资者关注度的代理变量,以股票收益率、成交量和股价波动率来描述股票市场的表现,考察投资者关注对当期和下一期股市表现的影响。实证研究发现投资者关注的增加对当期股票成交量和股价波动率有显著的正向影响,而这种影响在下一期会明显减弱。对收益率而言,投资者关注对其的影响具有反转性和非对称性。此外,通过买入关注度低增长股票、卖出关注度高增长股票构建零投资套利组合,并运用Carhart四因素模型进行分析,发现零投资套利组合能够获得显著的超额收益。     

PM2.5年均浓度对企业股利政策的影响北大核心CSSCI

本文分析了PM2.5年均浓度对企业股利政策的影响。研究发现,当所处地区的雾霾污染严重时,企业会发放更多的现金股利,并且很可能采取高派现做法,而非送转;这种效应不会因地域特征、企业污染特征以及政策的变化而消失。进一步分析表明,当所处地区的雾霾污染严重时,企业发放现金股利的做法降低了两类代理成本,但这并未迎合所有投资者的利益需求,而仅迎合了机构投资者尤其是独立机构投资者的利益需求。     

互动式信息沟通降低了股价崩盘风险吗? ——基于交易所网络平台的研究

以2016—2019年我国A股上市公司为样本,实证检验了交易所网络平台互动式信息沟通对上市公司股价崩盘风险的影响.研究发现,网络平台上投资者提问次数和上市公司回答次数越多,上市公司与投资者互动交流越频繁,上市公司股价崩盘风险越低;在信息不对称程度高的公司中,两者间的负相关关系更加显著.进一步分析上市公司信息环境发现,机构投资者持股比例较低、分析师关注度较低时,网络平台上的信息交流对股价崩盘的抑制效果更加显著.     

机构投资者退出威胁如何促进金融市场稳定？——基于股价崩盘风险视角

本文以2007—2021年沪深A股上市公司为研究对象，基于股价崩盘风险视角考察了机构投资者退出威胁如何促进金融市场稳定。研究发现，机构投资者退出威胁可以显著抑制股价崩盘风险，控制可能的内生性问题后结论依然成立。机制分析发现，机构投资者退出威胁通过降低代理成本以及降低分析师盈利预测乐观偏差，可以有效抑制股价崩盘风险。进一步分析发现，机构投资者退出威胁对股价崩盘风险的抑制作用在媒体关注度高的上市公司更显著，而在“两职合一”的上市公司中则被显著削弱。本研究揭示了机构投资者退出威胁在抑制股价崩盘风险中发挥的关键作用，对强化金融稳定保障体系有重要的参考价值。     

投资者情绪异质性能影响股价崩盘风险吗?

本文选取1999—2016年沪深A股市场交易数据以及与投资者情绪相关的数据,从市场层面研究了股价崩盘风险与投资者情绪之间的关系。实证研究发现,投资者情绪是股价崩盘风险的单向格兰杰原因,且股价崩盘风险往往要滞后于投资者情绪3期左右。进一步研究表明,投资者情绪对股价崩盘风险具有非对称性影响,即乐观情绪对崩盘风险具有显著影响,而悲观情绪对崩盘风险影响不显著。     

ESG信息披露对股价同步性的影响

本文以2009—2021年沪深A股非金融上市公司为样本，考察了ESG信息披露对股价同步性的影响和作用机制。研究表明，企业ESG信息披露表现越好，股价同步性越高。ESG信息披露从内部通过提高公司的信息透明度，从外部通过抑制投资者情绪波动，进而提高股价同步性。进一步研究发现，在分析师关注度较低、机构投资者持股比例较低的情境下，ESG信息披露对提高股价同步性可以发挥更大的作用。本文研究拓展了我国ESG信息披露的经济后果，为促进我国企业ESG信息披露与完善该制度建设具有借鉴意义。     

并购形成商誉及其减值损失分析——基于创业板与沪深两市对比

本文通过研究并购形成商誉及其减值损失,发现高管的确有动机通过大量并购而提高股价,进而增加自身收益,而忽视了并购带来的长期影响。在当前市场环境下,并购产生的商誉一旦发生减值损失,投资者会下调对公司未来的盈利预期,减少对公司扩张战略的认同度,从而造成股价的下滑。     

是谁影响了股价下行风险:有形信息VS无形信息

股价下行作为资本市场的普遍现象,在极端情况下会对投资者财富和公司声誉造成巨大冲击,因此受到学界、业界和监管层的高度关注。本文选取2007-2016年我国A股上市公司股票为样本,研究了不同信息对股价下行风险的影响,在此基础上考察了过度自信和损失厌恶两种不同的投资者行为是否会影响信息与股价下行风险之间的关系。研究发现:(1)有形信息显著降低了股价下行风险,而无形信息对股价下行风险的影响并不显著;(2)投资者的过度自信水平越高,有形信息与股价下行风险的负向关系越弱;(3)投资者的损失厌恶程度越高,有形信息与股价下行风险的负向关系越强。本文的研究不仅为投资者的投资决策提供了一个良好的风险管理思路,也为监管层的政策制定提供了相关的理论依据。     

投资者关注与市场反应——来自中国证券交易所交易公开信息的自然实验

涨停的股票能否被交易公开信息披露取决于收益率排名中的随机因素,与股票的基本面特征无关。本文利用这一机制设计自然实验检验了投资者关注对股价的影响。实证结果显示交易公开信息披露使股票受到投资者更多的关注,增加了小额资金的净流入,减少了大额资金的净流入和股价的短期收益率,抑制了股价短期波动率,同时降低了股价在长期发生反转的可能性。频繁登上交易公开信息的知名营业部买入的股票受到更多关注,相应的市场反应也更加显著。进一步的研究表明监管性信息披露引发的投资者关注通过降低市场信息不对称抑制了股价反转。     

Twitter activity,investor attention,and the diffusion of information

We examine the impact of Twitter attention on stock prices by examining over 21 million company‐specific tweets over a 5‐year period. Through a quasi‐natural experiment identifying official Twitter outages, we find that Twitter influences stock trading, especially among small, less visible securities primarily traded by retail investors. In addition, we determine that Twitter activity is associated with positive abnormal returns and when tweets occur in conjunction with traditional news events, more information is spread to investors. Finally, we show that retail investor activity drives the Twitter effect as institutional investors less actively trade the affected stocks.     

媒体关注度对新股表现的影响——来自中国股票市场的证据

新闻媒体对证券投资的影响日趋重要,它会通过影响投资者的心理和行为而影响资产价格。首次公开发行的股票（IPOs）由于倍受媒体关注,从而会在上市以后的价格表现上产生一定的影响。本文选取2006年6月至2008年6月上市的246只首次公开发行的股票作为样本,以百度新闻搜索到包含股票名称的新闻数量作为媒体关注度的衡量指标,实证检验了媒体关注度对新股表现的影响。本文得出结论：媒体关注度通过影响投资者情绪,对新股短期累积超额收益产生正的影响,而对长期累积超额收益产生负的影响。同时发现,媒体关注度高的新股,其发行价格也相对较高。     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

信息不对称、过度自信与股价变动

信息传导的非同步和投资者情绪变化是股票市场的两个典型特征,前者会引发投资者之间出现信息不对称问题,后者主要体现为投资者过度自信,两者共同作用影响股票价格变动。本文将信息不对称和投资者过度自信情绪置于同一个分析框架,建立两阶段动态序贯定价理论模型研究现实市场上信息传导过程中股价变动的内在机制。结果表明:(1)面临新信息的进入,投资者对股票收益预期的调整与均衡价格之间具有正相关关系;(2)面临有利消息时,过度自信投资者比例越大,股票的均衡价格越高,投资收益将越低;面临不利消息时则相反;(3)随着过度自信投资者比例以及过度自信程度升高,市场风险溢价将下降;(4)投资者群体在信息传导过程中出现分化,对股价变动形成异质信念,未获取信息和获取信息但未出现过度自信的投资者认为股价被高估,获取信息且出现过度自信的投资者认为价格被低估,促使更多的交易,引发市场成交量和股价变动;(5)过度自信投资者比例与过度自信程度提高均会对市场效率产生正向影响,而对市场深度具有负向效应。最后,基于理论结果对非对称性和持续性等典型的市场波动性特征进行解释。     

Sentiment stocks

To study how investor sentiment at the firm level affects stock returns, we match more than 58 million social media messages in China with listed firms and construct a measure of individual stock sentiment based on the tone of those messages. We document that positive investor sentiment predicts higher stock risk-adjusted returns in the very short term followed by price reversals. This association between stock sentiment and stock returns is not explained by observable stock characteristics, unobservable time-invariant characteristics, market-wide sentiment, overreaction to news, or changing investor attention. Consistent with theories of investor sentiment, we find that the link between sentiment and stock returns is mainly driven by positive sentiment and non-professional investors. Finally, exploiting a unique feature of the Chinese stock market, we are able to isolate the causal effect of sentiment on stock returns from confounding factors.     

Crowd wisdom and internet searches: What happens when investors search for stocks?

Search engines and social media have become popular among investors as tools for finding and sharing information. The investor social media gathers a large amount of investor-generated content (IGC), which reflects the crowd wisdom of investors, while search engines help investors increase their chances of finding them. In this study, we integrate investor search behavior data from the Baidu Index and investor crowd wisdom data from Eastmoney Guba to assemble a unique data set at the daily level. We then describe and quantify crowd wisdom from investor-generated content (IGC) using three dimensions (IGC average sentiment, IGC sentiment volatility, and IGC increased volume) to investigate the impact of crowd wisdom in the relationship between investors' Internet searches and next-day stock returns. In our empirical analysis, we find that IGC average sentiment strengthens the relationship between investors' Internet searches and next-day stock returns, while IGC sentiment volatility and IGC increased volume have negative effects. These moderating effects are also moderated by institutional investor attention, search terminal preference, and content reading volume. These findings help to explain the value and impact of crowd wisdom when investors search for stock information through the Internet.     

When does attention matter? The effect of investor attention on stock market volatility around news releases

We empirically investigate how retail and institutional investor attention is related to the way stock markets process information. With a focus on 360 US stocks in the S&P 500 universe, our results show that higher retail investors’ attention around news releases increases the post-announcement stock return volatility, whereas institutional investor attention has a small but negative impact on volatility on days following news releases on average over the cross-section of companies. These findings are in line with the hypotheses that attention of retail investors slows price-adjustments to new information and attention of institutional investors results in the opposite reaction. We show that these effects are heterogeneous in the type of news and the topic of the information being released. A portfolio allocation application highlights that these results are not only statistically significant but also sizeable in economic terms and can lead to an overperformance as large as dozens of basis points.     

In Search of Attention

We propose a new and direct measure of investor attention using search frequency in Google (Search Volume Index (SVI)). In a sample of Russell 3000 stocks from 2004 to 2008, we find that SVI (1) is correlated with but different from existing proxies of investor attention; (2) captures investor attention in a more timely fashion and (3) likely measures the attention of retail investors. An increase in SVI predicts higher stock prices in the next 2 weeks and an eventual price reversal within the year. It also contributes to the large first‐day return and long‐run underperformance of IPO stocks.     

Individual Investor Trading and Return Patterns around Earnings Announcements

This paper provides evidence of informed trading by individual investors around earnings announcements using a unique data set of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose abnormal returns following the event into information and liquidity provision components, and show that about half of the returns can be attributed to private information. We also find that individuals trade in both return‐contrarian and news‐contrarian manners after earnings announcements. The latter behavior has the potential to slow the adjustment of prices to earnings news.