Market sentiment: a key factor of investors’ imitative behaviour

The aim of this paper is to explore herding behaviour among investors to determine its rational and emotional component factors and identify relationships among them. We apply causality tests to evaluate the impact of return and market sentiment on herding intensity. The herding intensity is quantified using the measure developed by Patterson and Sharma (2006) . The research was conducted during the period 1997–2003 in the Spanish stock market, where the presence of herding has been confirmed. The results reveal that the herding intensity depends on past returns and sentiment or subjective assessments and confirm the presence of both a rational and an emotional factor.     

The systematic pricing of market sentiment shock

ABSTRACT

We show that market sentiment shocks create demand shocks for risky assets and a systematic risk for assets. We measure a market sentiment shock as the unexpected portion of the University of Michigan Consumer Sentiment Index’s growth. This shock prices stock returns in arbitrage pricing theory framework at 1% after controlling for market, size, value, momentum, and liquidity risk factors. Its premium lowered the implied risk aversion by 97.9% to 11.46 between 1978 and 2009 in our sentiment consumption-based capital-asset-pricing model. Merton’s [1973. “An Intertemporal Capital Asset Pricing Model.” Econometrica 41: 867–887]. intertemporal capital-asset-pricing model reconfirms our finding that this market sentiment shock is a systematic risk factor that provides investment opportunities.     

Market sentiment to COVID-19 and the Chinese stock market

We classify the market sentiment to COVID-19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one-way, whereas there exists a two-way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.     

投资者情绪与中国股票市场过度波动

本文分析中国投资者分类情绪及信心变化与中国股票市场波动的同期及动态影响。实证结果表明:就同期而言,中国投资者对国内经济基本面的信心变化以及中国股票市场波动,将影响投资者对国际经济金融环境的信心;就中长期而言,中国投资者情绪中关于国内经济基本面和国内经济政策的信心变化是影响中国股票市场过度波动的重要原因;中国投资者关于国际经济金融环境的信心深受国内经济基本面的信心变化的影响,中国投资者对A股市场估值的判断,受投资者对A股市场的股票估值信心以及国内经济基本面信心变化影响较大。     

Institutional trading,investor sentiment,and lottery-like stock preferences

This paper explores the time-varying institutional investor preference for lottery-like stocks. On average, institutional investor holdings reflect an aversion to lottery-like stocks. However, I find that an institutions’ aversion to lottery-like stocks is reduced when investor sentiment is low. Moreover, I find that during low sentiment periods, institutional investors have abnormally high trading profits in more positively skewed stocks. These results suggest that institutions reduce their aversion toward lottery-like stocks during low sentiment periods to profitably trade in lottery-like stocks.     

Investor sentiment and management earnings forecast bias

This study investigates whether investor sentiment is associated with behavioral bias in managers’ annual earnings forecasts that are generally issued early in the year when uncertainty is relatively high. I provide evidence that management earnings forecast optimism increases with investor sentiment. Furthermore, I find that managers’ annual earnings forecasts are more pessimistic during low‐sentiment periods than during normal‐sentiment periods. Since managers lack incentives to further deflate stock prices during a low‐sentiment period, this evidence indicates that sentiment‐related management earnings forecast bias is likely to be unintentional. In addition, I find that the relationship between management earnings forecast bias and investor sentiment is stronger for firms with higher uncertainty, consistent with investor sentiment having a greater influence on management earnings forecasts when uncertainty is higher.     

Twitter investor sentiment and corporate earnings announcements

We examine the impact of firm-specific investor sentiment (FSIS) on stock returns for negative and positive earnings surprises. Using a measure constructed from firm-specific tweets, we find that FSIS has a greater impact on stock returns for negative relative to positive earnings surprises. We further show that the impact of FSIS is greater for firms whose valuation is uncertain and difficult to arbitrage. Moreover, we provide evidence of return reversals over post-announcement periods. Our results highlight the importance of FSIS around earnings announcements.     

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。     

The informativeness of domestic and foreign investors’ stock trades: Evidence from the perfectly segmented Chinese market

This paper uses the perfect market segmentation setting in China's stock market to compare the information content of the stock trades of domestic and foreign investors. We study 76 firms that issue both A-shares (for domestic investors) and B-shares (for foreign investors) and compare the price discovery role of the two segmented markets in China. Before Feb 19, 2001, the A-share market led the B-share market in price discovery, as the signed volume and quote revision of the A-share market had strong predictive ability for B-share quote returns, but not vice versa. After Feb 19, 2001, because some domestic investors were allowed to invest in the B-share market, we find evidence for a reverse causality from the B-share to the A-share market. Nevertheless, the [Hasbrouck (1995). One security, many markets: determining the contributions to price discovery, Journal of Finance 50, 1175–1199.] information share analysis reveals that A-shares continue to dominate the price discovery process.     

‘BIG DATA’, THE ‘INTERNET OF THINGS’ AND THE ‘INTERNET OF SIGNS’

This paper examines the relationship between so‐called ‘Big Data’, the ‘Internet of Things’ (the ‘Internet of People and Things,’ and the ‘Internet of Everything’), and the ‘Internet of Signs.’ In particular, we investigate how the ‘things’ in the ‘Internet of Things’ generate ‘Big Data’, and how both are used to generate semiotic ‘signs’. In addition, we analyse the importance of context in and the relationships between ‘Big Data’, the ‘Internet of Things’, and the ‘Internet of Signs’. Copyright © 2013 John Wiley & Sons, Ltd.     

Investor sentiment and the underperformance of technology firms initial public offerings

This research examines the effect of individual and institutional investor sentiment toward the overall market at the time of Initial Public Offering (IPO) on the aftermarket performance of technology IPO shares. The study which is based on 1346 U.S. technology IPOs completed between 1992 and 2009 shows that the irrational component of individual investor sentiment negatively affects shares’ aftermarket performance: the more optimistic individual investors are at the time of IPO, the lower the shares’ aftermarket return. On the other hand, the rational component of institutional investor sentiment does not affect the shares’ short-run performance, yet positively affects their long-run performance. In contrast with prior theoretical models this paper shows that investor overconfidence positively affects technology IPO shares’ aftermarket performance. The paper extends the behavioral finance literature by providing evidence on the negative role played by noise trading in affecting technology and biotechnology IPO shares performance.     

投资者情绪对股价联动的影响--基于中国证券市场的实证研究

分别从个股层面以及市场层面探讨投资者情绪对中国证券市场股价联动现象的影响。实证揭示：（1）中国证券市场存在显著的股价联动效应。（2）投资者情绪对股价联动现象存在显著的负向影响。（3）个股层面的投资者情绪变量对股价联动的影响大于市场层面的综合情绪变量。（4）投资者情绪对不同行业的股价联动的影响存在差异。     

Investor Sentiment and Stock Returns: Evidence from Turkey

This paper investigates the relation between investor sentiment and stock returns on the Istanbul Stock Exchange, employing vector autoregressive (VAR) analysis and Granger causality tests. The sample period extends from July 1997 to June 2005. In the VAR models, stock portfolio returns and investor sentiment proxies are used as endogenous variables. Two dummy variables accounting for natural and economic crises are used as exogenous variables. The analysis results suggest that, excepting shares of equity issues in aggregate issues, stock portfolio returns seem to affect all investor sentiment proxies, namely closed-end fund discount, mutual fund flows, odd-lot sales-to-purchases ratio, and repo holdings of mutual funds. Investor sentiment does not appear to forecast future stock returns; only the turnover ratio of the stock market seems to have forecasting potential.     

What Can “Nine‐Eleven” Tell Us about Closed‐end Fund Discounts and Investor Sentiment?

We use the horrific events of September 11, 2001 (“nine‐eleven”) as a natural test of the hypothesis that closed‐end mutual fund discounts from fund net asset values reflect small investor sentiment. Because nine‐eleven was a sudden, unforeseen, and significantly negative and exogenous shock to the world, the capital markets, and investor sentiment, our test avoids many of the problems of extant studies. Discounts worsened dramatically following the event, and then recovered alongside the broader market. This finding is consistent with the hypothesis that discounts reflect the sentiment of small investors, who took their cues from the broader market's overall movement.     

Target price forecasts: The roles of the 52-week high price and recent investor sentiment

This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts’ target price formation. Analysts’ forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables for target prices; equally, the 52-week high price and recent investor sentiment are also shown to explain target price levels and especially target price biases. Our analysis additionally reveals that analysts place greater weight on these two non-fundamental factors in settings with greater task complexity and to some extent in those with greater resource constraints. Conversely, on balance, the results suggest that this increased reliance does not translate into an increased impact per unit of each non-fundamental factor on forecast bias. Finally, our results show that target prices are useful in predicting future stock returns beyond earnings forecasts and commonly used risk proxies. However, in an internally consistent fashion, the informativeness of target prices for future returns is significantly reduced when greater weight is placed on either the 52-week high or recent investor sentiment in the target price formation process.     

Positive Feedback Trading and Investor Sentiment

This article examines how investor sentiment affects positive feedback trading behavior. By analyzing the daily closing total return of CSI 300 index and its individual returns of stocks, we find that relatively high or low sentiment induces active positive feedback trading. With a specific indicator of sentiment, we explain the microstructure setting of the relationship between positive feedback trading and sentiment. We adopt the classical feedback model from Sentana and Wadhwani (1992) to measure positive feedback trading behavior. By adding sentiment factor to the model, we successfully explain how sentiment influences the behavior of both feedback traders and rational investors. The empirical findings suggest that positive feedback traders are more likely to trade when the prices of most securities move forward together. When the sentiment of feedback traders is at an intermediate level, the feedback trading behavior is insignificant.     

Investor Trading Behavior and Sentiment in Futures Markets

This study investigates the effects of investor trading behavior and investor sentiment on futures market return. We find that the spot investor trading behavior, futures investor trading behavior, spot market sentiment, and futures market sentiment all have positive effects on daily futures returns in Chinese financial market. More importantly, we show that the effect of (spot) futures investor trading behavior has better explanatory power than (spot) futures market sentiment on futures returns. Further supporting our results, high investor trading behavior and high investor sentiment strengthen the positive relation between sentiment-returns and behavior-returns.     

Tehran stock exchange prediction using sentiment analysis of online textual opinions

We investigate the impact of social media data in predicting the Tehran Stock Exchange variables for the first time. We consider the closing price and daily return of three different stocks for this investigation. We collected our social media data from Sahamyab.com/stocktwits for about 3 months. To extract information from online comments, we propose a hybrid sentiment analysis approach that combines lexicon‐based and learning‐based methods. Since lexicons that are available for the Persian language are not practical for sentiment analysis in the stock market domain, we built a particular sentiment lexicon for this domain. After designing and calculating daily sentiment indices using the sentiment of the comments, we examine their impact on the baseline models that only use historical market data and propose new predictor models using multi‐regression analysis. In addition to the sentiments, we also examine the comments volume and the users' reliabilities. We conclude that the predictability of various stocks in the Tehran Stock Exchange is different depending on their attributes. Moreover, we indicate that only comments volume could be useful for predicting the closing price, and both the volume and the sentiment of the comments could be useful for predicting the daily return. We demonstrate that users' trust coefficients have different behaviours toward the three stocks.     

Exchange-traded fund ownership and underlying stock mispricing

In response to the increasing proliferation of exchange-traded funds (ETFs), and a warning from the Wall Street hero Michael Burry that passive investing has put the stock market into ‘bubble’ territory, we examine the relation between stock ownership by ETFs and mispricing from 2002 to 2018. We find that increased ETF ownership induces overpricing in underlying stocks. We then identify three mechanisms for this relationship: the overpricing of stocks attributable to increased ETF ownership is stronger for stocks that experience an increase in passive ETF ownership; during periods characterised by high investor sentiment; and for illiquid stocks. Our results are robust to a battery of tests including alternative measures for all key variables and are not confounded by the global financial crisis. Additional analyses show that mispricing caused by ETF ownership change is not driven by firm fundamentals and does not exacerbate stocks' information environment around earnings announcement.     

Investor Sentiment Influence on the Risk-Reward Relation in the Taiwan Stock Market

We examine the influence of investor sentiment on the risk-reward relationship in the Taiwan stock market. Regression results show that the risk-reward relationship is weakly positive (significantly negative) under low (high) levels of investor sentiment. Granger causality tests indicate unidirectional, not bidirectional, causal relationships. Moreover, the negative return-variance relationship is more strongly characteristic of the over-the-counter index than of the Taiwan Stock Exchange weighted index, indicating that an unreasonable risk-reward trade-off may be more prevalent in emerging markets than in mature markets. Finally, the Wald test demonstrates that industry effects on the risk-reward relationship may be negligible.