Changes in sentiment on REIT industry excess returns and volatility

REIT characteristics pose unique risks and benefits to investors who seek liquid diversification and hedging vehicles to complement their portfolios. This paper tests for the asymmetric effect of individual and institutional investor sentiment on REIT industry returns and conditional volatility. We simultaneously model the impact of two markedly different groups of investors on the return generating process of the REIT industry. Our findings suggest that noise trading imposes significant systemic risk on the realization of REIT industry returns. Interestingly, corrections in institutional investor expectations have a larger effect on REIT industry returns and volatility than changes in individual investor expectations. More specifically, bearish shifts in institutional investor expectations of future market conditions have a significantly larger impact on returns and volatility than bullish shifts. Results align with the overreaction to negative information and loss aversion hypotheses.     

Excess Volatility and UK Investment Trusts

Abstract:   The issue of whether or not asset prices are more volatile than the underlying fundamentals is an empirical question with implications for market efficiency. Recent research suggests that the volatility of closed end fund returns in the USA is significantly higher than the returns on assets held by the funds. This has been attributed to noise trading as closed‐end fund shares are predominantly held by individual investors. This study demonstrates that UK investment trust returns exhibit similar excess volatility in spite of the prevalence of institutional investors. However, big investment trusts in terms of market capitalisation show greater excess volatility than small trusts. Although most of the excess volatility appears to be idiosyncratic, investor sentiment index is the most important variable associated with residual returns.     

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.     

投资者情绪是导致我国投资者对市场信息出现反应偏差的原因吗：基于贝叶斯分位数回归模型的研究

本文使用贝叶斯分位数回归模型实证分析包含投资者情绪的投资者最优选择模型,结果表明：投资者情绪对于股票收益率存在非线性的正向影响,这是造成投资者对于市场信息出现反应偏差的一个重要原因.同时,市场信息和投资者情绪指标对于我国股票收益率都有着较大的影响作用;当股票出现不同涨跌幅时,市场信息对于股票收益率的影响有着较大的差异性.而考虑了投资者情绪指标之后,投资者对于市场信息的反应偏差明显减小,说明投资者情绪是造成我国投资者对于市场信息出现过度反应和反应不足的重要原因.我国投资者应该树立起良好的投资意识和心态,避免潜在的投资损失.     

Asset pricing with investor sentiment: On the use of investor group behavior to forecast ASEAN markets

A study of investor behavior, using four investor groups (local, foreign, institutional, and dealer's accounts) on the Stock Exchange of Thailand (SET). The daily net purchases of each group are used as leading indicators for sentiment. The sentiments are examined with relation to each other and market returns. Eight proven macroeconomic factors with known cross-sectional relationships and known to forecast with returns are examined as a benchmark for the newly proposed sentiment factor model. Retesting the factors allows for an apples to apples comparison with the proposed sentiment factors. Using a VAR framework this research finds that dealers predominantly sell to institutional accounts, creating a negative correlation between the two groups, in addition to strong institutional herding which is all indicative of potential agency problems on the exchange. Also find that local individual accounts practice negative feedback trading and the other groups practice positive feedback trading. Of the four groups, the only group that influences the SET is the local individual group of investors. The foreign investor is found to be the least significant group on market returns, provide market liquidity to locals, and be the least responsive to daily market changes-following the prudent man rule. Lastly, propose a simple model, using investor behavior to accurately predict the market's direction for the following day 76 percent of the time with market timing ability (66 percent in Malaysia). This can be useful for buying and shorting the market.     

Noise trading and stock market volatility

We investigate the relative effects of fundamental and noise trading on the formation of conditional volatility. We find significant positive (negative) effects of investor sentiments on stock returns (volatilities) for both individual and institutional investors. There are greater positive effects of rational sentiments on stock returns than irrational sentiments. Conversely, there are significant (insignificant) negative effects of irrational (rational) sentiments on volatility. Also, we find asymmetric (symmetric) spillover effects of irrational (rational) bullish and bearish sentiments on the stock market. Evidence in favor of irrational sentiments is consistent with the view that investor error is a significant determinant of stock volatilities.     

Exploring the relationship between investor sentiment and price volatility

By performing Grey relation analysis, this study elucidates the relationship between investor sentiment and price volatility in the Taiwanese stock market. A sequential relationship is identified between investor sentiment and price volatility, and ranked according to order of importance. Analytical results show that short sales volumes may be an individual leading indicator useful in observing the effects of sentiment on price volatility, followed by open interest put/call ratios and trading volumes, and buy/sell orders. Institutional investors are related, to a lesser extent, to price volatility and sentiment. Qualified foreign institutional investors, or more rational investors, are the least influenced by price volatility, followed by securities investment trust companies and dealers. TAIEX options exert the strongest influence on sentiment during the study period, making them a valuable reference for gauging price volatility.     

Does investor sentiment predict bitcoin return and volatility? A quantile regression approach

The study investigates hypotheses relating to the effect of investor sentiment on predicting bitcoin returns and volatility. Using moments quantile regression, we present robust empirical evidence for the period 2017–2021. Our findings demonstrate that investor interest and emotions are significant predictors of bitcoin returns and volatility, while VIX and Bitcointalk.org forum are the most suitable predictors for representing investor emotions and interest, respectively. The findings also indicate a nonlinear relationship between investor sentiment and bitcoin returns and volatility, with predictable power changing based on the market conditions. Thus, the study enriches existing literature by providing empirical evidence to affirm the viability of behavioral finance theories in the bitcoin market and complements investors with more information to seek profits in different market conditions.     

Futures Market Sentiment and Institutional Investor Behavior in the Spot Market: The Emerging Market in Taiwan

This paper investigates whether and how futures market sentiment and stock market returns heterogeneously affect the trading activities of institutional investors in the spot market in Taiwan. Our empirical results suggest that foreign investors are net sellers whenever futures market sentiment is bullish and net buyers when investor sentiment is bearish. The two types of domestic institutional investors have poor sentiment timing abilities and the price-pressure effect may account for the behavioral differences among institutional investors. In addition, all three institutional investors are momentum traders. Nevertheless, the momentum trading of foreigners is consistent with an information-based model and that of two local institutional investors, as behavior-based models suggest. This indicates that the same trading momentum strategy can lead to different outcomes for different investors, and both information- and behavior-based momentum trading can exist contemporaneously in the Taiwanese stock market.     

Transparency in IPO mechanism: Retail investors’ participation,IPO pricing and returns

Using data from the transparent Indian IPO setting, the paper examines retail investors’ participation, their influence on IPO pricing and the returns they make on IPO investment. The transparency in the mechanism, which allows investors to observe prior investors’ participation, leads to demand which is concentrated at either one or two points of the offer price range. Analysis of investors’ demand during the offer period shows that the participation of retail investors is significantly influenced by the participation of institutional investors. We examine IPO pricing and find that favourable demand by retail investors is positively associated with a high IPO price even after controlling for demand by institutional investors. Further, we find that due to aggressive bidding by overconfident investors, retail investors are, on average, unlikely to make positive allocation weighted initial returns even in a setting where they do not have to compete with institutional investors. Retail investors, however, can earn significant positive allocation weighted initial returns if they limit their participation in IPOs with above average institutional investors’ demand.     

Investor sentiment and return predictability of disagreement

This study examines the influence of investor sentiment on the relationship between disagreement among investors and future stock market returns. We find that the relationship between disagreement and future stock market returns time-varies with the degree of investor sentiment. Higher disagreement among investors’ opinions predicts significantly lower future stock market returns during high-sentiment periods, but it has no significant effect on future stock market returns during low-sentiment periods. Our findings imply that investor sentiment is related to several causes of short-sale impediments suggested in the previous literature on investor sentiment, and that the stock return predictability of disagreement is driven by investor sentiment. We demonstrate that investor sentiment has a significant impact on the stock market return predictability of disagreement through in-sample and out-of-sample analyses. In addition, the profitability of our suggested trading strategy exploiting disagreement and investor sentiment level confirms the economic significance of incorporating investor sentiment into the relationship between disagreement among investors and future stock market returns.     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

Returns,volatility and investor sentiment: Evidence from European stock markets

In this study, we show that patterns in returns behave as if investors, influenced by their level of optimism, selected stocks according to their volatility. Our goal is to confirm the contribution of behavioral finance while showing that investor sentiment can be profitably used by practitioners. We incorporate volatility in the relationship between investor sentiment and future returns, this is the main originality of our approach. Our methodology consists in comparing returns, volatility and higher-order moments of portfolios managed with investor sentiment against those obtained either with passive (buy and hold) portfolio management or with a minimum variance portfolio. Portfolios managed with investor sentiment have better returns and involve less risk under certain conditions.     

Information,hedging demand,and institutional investors: Evidence from the Taiwan Futures Exchange

This paper examines the effect of hedging demand by various types of institutional investor on subsequent returns and volatility. Using data from the Taiwan Futures Exchange, empirical results indicate that the hedging demand of foreign investors has a significant negative impact on subsequent returns and volatility. In addition, trading strategies based on the extreme hedging demand of foreigners are positively correlated with trading performance. Furthermore, there is evidence to show that returns (volatility) also affect the subsequent hedging demand of foreign investors, suggesting a feedback relation. Finally, the hedging demand of foreign investors has a greater impact on subsequent returns and volatility after global financial turmoil. Accordingly, this paper concludes that foreign investors are informed hedgers in the Taiwan futures market, especially after global financial turmoil.     

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.     

Trading behaviour and market sentiment: Firm-level evidence from an emerging Islamic market

We provide firm-level evidence from an emerging Islamic market that individual investors' trading behaviour causes weekend sentiment. Using data for 285 companies listed on the Dhaka Stock Exchange (DSE) for the period from 2002 to 2019 and applying appropriate econometric techniques, the paper has found evidence of weekend effect both on return and volatility. The results confirm that individual investors' sentiment drives the weekend effect in DSE. ‘Information content theory’ and ‘information processing hypothesis’ work for investors so that the market return and volatility become significantly different on Sunday. The market sentiment effect is significant for smaller firms and low dividend yield firms where individual investors are prevalent, suggesting that trading behaviour of individual investors determines weekend sentiment. A positive feedback relationship exists between returns on Sunday and the previous Thursday for both institutions and individuals. Our results are robust in various alternative specifications.     

Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets

The present study investigates the degree of market responses through the scope of investors' sentiment during the COVID-19 pandemic across G20 markets by constructing a novel positive search volume index for COVID-19 (COVID19⁺). Our key findings, obtained using a Panel-GARCH model, indicate that an increased COVID19⁺ index suggests that investors decrease their COVID-19 related crisis sentiment by escalating their Google searches for positively associated COVID-19 related keywords. Specifically, we explore the predictive power of the newly constructed index on stock returns and volatility. According to our findings, investor sentiment positively (negatively) predicts the stock return (volatility) during the COVID-19. This is the first study assessing global sentiment by proposing a novel proxy and its impacts on the G20 equity market.     

投资者情绪对我国股市行业收益率的动态影响作用——基于固定效应广义最小二乘法的研究

本文使用2005--2011年我国股市行业收益率数据并构造投资者情绪指标,利用VAR格兰杰因果检验和固定效应广义最小二乘法分析投资者情绪对我国股市的动态影响。实证结果发现,2005--2011年的两次股票市场大幅度涨跌中,我国投资者情绪和股票收益率存在双向因果关系;投资者情绪在3个月内会对股票收益率有正面的影响,此后12个月内其正向影响作用出现了明显的负向反转,其中具有较高账面市值比和占有较高经济地位的交通运输业、信息技术业和制造业等国家基础行业容易受到投资者乐观情绪的影响而出现大幅度涨跌。     

Reversal of Monday returns

This paper elaborates an interesting aspect of the Monday anomaly: Monday returns are relatively more likely to reverse over the subsequent days. We document that, although the Monday low-return anomaly disappeared, the subsequent reversal of Monday returns remains robust to date. The reversals, measured over a five-day horizon, are pervasive across international stock markets, reasonably stable over time, significant following both positive and negative Monday returns, and not confined to extreme Monday returns. Trading strategies designed to exploit these reversals earn economic profits. We examine potential explanations for the reversal of Monday returns using trading flows data of investor types from Korea. All predictions of the Foster and Viswanathan [J. Finance, 1993, 48, 187–211] model are confirmed: volatility is higher, trading volume is lower, market depth is lower and price impact costs are higher on Mondays. The model implies lower price quality on Mondays, but does not specifically predict reversal of Monday returns. We show that the trading intensity of international/institutional investors is lower on Mondays. This appears to make the market relatively more susceptible to individual investors’ trading, which is negatively correlated with international/institutional investors. Thus, Monday returns are relatively more likely to reverse during the subsequent days of the week when institutional investors trade more aggressively.     

Investor and price response to patterns in earnings surprises

As part of their model to explain short-term positive and long-term negative auto-correlation in stock returns, Barberis, Shleifer, and Vishny [1998. A model of investor sentiment. Journal of Finance 49, 307–345] suggest that investors may extrapolate trends in earnings performance. I test this portion of their model by examining investor trading patterns in firms that experience consecutive same-sign earnings surprises. Consistent with their model, after controlling for regularities in trading activity, I find that the net buying of small investors increases with the number of consecutive positive earnings surprises. I further find that purchasing activity of small investors subsequent to consecutive positive surprises is significantly negatively correlated with returns throughout the remainder of the year. These results suggest that such investors are not simply rationally updating after public news announcements. My results are robust to controlling for auto-correlation in earnings surprises.