An examination of U.S. institutional and individual investor sentiment effect on the Turkish stock market

This study examines the effect of rational and irrational components of U.S. institutional and individual investor sentiment on Istanbul Stock Market (ISE) return and volatility. The results show that there is a significant spillover effect of U.S. investor sentiment on stock return and volatility of ISE. A breakdown of sentiment by the type of investor shows that the impact of institutional sentiment is greater than that of individual sentiment. A breakdown of sentiment by rationality shows that the effect of rational sentiment on ISE return is faster though not necessarily greater than that of irrational sentiment. The conclusion from these results is that the effect of U.S. investor sentiment is systemic and cannot be diversified away. U.S. investor sentiment, therefore, constitutes a priced risk factor and must be accounted for accordingly in international asset pricing models. The findings also provide some evidence of a negative relationship between U.S. investor sentiment and ISE return volatility.     

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.     

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.     

我国投资者情绪与股票收益实证研究

根据投资者情绪是股票价格形成重要影响因素这一研究观点,围绕投资者情绪是否构成系统性风险及其对不同类型股票的差异化影响,运用我国股市交易数据进行的实证研究结果表明,投资者情绪不构成股市的系统性风险,但对不同市值的股票有着差异化的影响,随着股票的"投机性"增加,投资者情绪对其影响也增大.此外,投资者情绪会削弱股票收益与其波动的正相关性,且对于"投机性"越高的股票,这一影响也越大.     

Investor Sentiment and Return Predictability of the Option to Stock Volume Ratio

We study the effect of investor sentiment on the relation between the option to stock volume ratio (O/S) and future stock returns. Relative option volume has return predictability under short sale constraints. For this reason, we expect and find a stronger O/S‐return relation during high sentiment periods than during low sentiment periods. We find that Baker and Wurgler's Investor Sentiment Index affects the O/S‐return relation after controlling for consumer sentiment indices and economic environment factors. While prior studies have used consumer sentiment indices as alternative measures of investor sentiment, our results suggest these effects are distinct.     

Market Response to Investor Sentiment

This paper reconsiders the effect of investor sentiment on stock prices. Our main contribution is that, in addition to the intermediate term return predictability, we also analyze the immediate price reaction to the publication of survey‐based investor sentiment indicators. We find that the sign of the immediate market response is the same as that of the predictability at intermediate time horizons. This is consistent with underreaction to cash flow news or with investor sentiment being related to mispricing. It is inconsistent with the alternative explanations of a rational response to cash flow news or sentiment indicators providing information about future expected returns.     

Investor sentiment indices based on k-step PLS algorithm: A group of powerful predictors of stock market returns

We construct a group of new investor sentiment indices by applying a new dimension reduction technique called k-step algorithm which adopts partial least squares method recursively. With the purpose of forecasting the aggregate stock market return, the new group of investor sentiment indices performs a greater ability in predicting the market return than existing investor sentiment indices in and out of sample by adequately using the information in residuals and eliminating a common noise component in sentiment proxies. This group of new investor sentiment indices beats five widely used economic variables and still has a strong return predictability after controlling these variables. Moreover, they could also predict cross-sectional stock returns sorted by industry, size, value, and momentum and generate considerable economic value for a mean-variance investor. We find the predictability of this group of investor sentiment indices comes from its forecasting power for discount rates and market illiquidity.     

Information uncertainty,investor sentiment,and analyst reports

This study investigates the relationships among information uncertainty, investor sentiment, analyst reports, and stock returns in a unified framework. The effects of analyst reports on stock returns depend on the degrees of information uncertainty, indicating that recommendation upgrades (downgrades) convey more valuable positive (negative) information under higher information uncertainty. Such stock market reactions are significantly explained by investor sentiment when information uncertainty is high. Our empirical findings are robust to changes in abnormal return measures and information uncertainty proxies.     

Investor Sentiment and the Closed‐end Fund Puzzle: Out‐of‐sample Evidence

In this paper we examine the proposition that small investor sentiment, measured by the change in the discount/premium on closed‐end funds, is an important factor in stock returns. We conduct an out‐of‐sample test of the investor sentiment hypothesis in a market environment that is more likely to be prone to investor sentiment than the USA. We fail to provide supporting evidence for the claim of Lee et al. (1991) that investor sentiment affects the risk of common stocks. Consistent with Elton et al. (1998) , who show that investor sentiment does not enter the return generating process, our tests do not detect investor sentiment in a capital market that is more susceptible to small investor sentiment. Our results provide additional support against the claim that investor sentiment represents an independent and systematic asset pricing risk.     

Institutional investor sentiment and aggregate stock returns

This paper examines the equity market return predictability of institutional investor sentiment, in comparison to individual investor sentiment. Our findings suggest that institutional traders are informed and that their sentiment helps to tilt stock prices towards the intrinsic value. This is because the sentiment of institutions encompasses news regarding expectations on future cash flows of underlying firms that impounds itself into future price expectations. In this study, we add to the large number of studies that investigate the role and implications of investor sentiment, which has long been viewed as a pure behavioural phenomenon, on market efficiency and price discovery.     

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.     

Investor Sentiment and Option Prices

This paper examines whether investor sentiment about the stockmarket affects prices of the S&P 500 options. The findingsreveal that the index option volatility smile is steeper (flatter)and the risk-neutral skewness of monthly index return is more(less) negative when market sentiment becomes more bearish (bullish).These significant relations are robust and become stronger whenthere are more impediments to arbitrage in index options. Theycannot be explained by rational perfect-market-based optionpricing models. Changes in investor sentiment help explain timevariation in the slope of index option smile and risk-neutralskewness beyond factors suggested by the current models.     

Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors

This paper extracts an investor sentiment indicator for the 30 DJIA stocks based on the textual classification of 289,024 online tweets posted on the so-called StockTwits, and examines its contemporaneous and predictability effects on the dispersion of stock returns using the quantile regression technique. We find that both contemporaneous and predictability effects of sentiment are heterogeneous throughout the return distribution. Specifically, sentiment is positively contemporaneously associated with stock returns at higher quantiles. However, it is a strong negative predictor of future returns at lower quantiles. Overall, our findings are broadly consistent with most behavioural theories and show that sentiment mainly affects the valuation of assets in extreme market conditions.     

Investor attention,information acquisition,and value premium: A mispricing perspective

This paper investigates the impact of investor attention on the dynamics of the value premium. We find superior return differences to value-growth strategy conditioned as low degree of investor attention. In contrast, return differences to the value-growth strategy conditioned as high investor attention are indifferent from zero. We show that return differences to low degree of investor attention across value and growth firms are attributed to mispricing explanation using common risk factors, mispricing factors, sentiment analysis, multivariate analysis, and market expectation errors approach. The findings suggest that investor attention contributes to generating superior return differences to standard value-growth strategy. Our finding concludes that long-short investment strategy in value stocks and growth stocks conditioned as low investor attention generate superior value premium.     

Earnings management and IPO anomalies in China

This paper empirically examines the impact of earnings management and investor sentiment on IPO anomalies using a sample of 506 Chinese IPOs issued over the 1998–2003 period. We develop a parsimonious pricing model in which both the offer price and the short-term aftermarket price are influenced by the use of earnings management, and show that the offer price can be below the fair price while the short-term equilibrium price in the aftermarket can be overvalued due to investor sentiment. Consistent with the overreaction hypothesis, the empirical results reveal a positive relation between the initial return and managed accruals and a negative relation between the long-term stock performance and the initial return. Earnings management appears to generate a pattern where the initial price following an IPO tends to be inflated by overreaction in the secondary market but adjusts to its fundamental level in the long run. These findings are robust across a variety of test specifications.     

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.     

Investor sentiment and the risk–return relation: A two-in-one approach

Traditional finance theory posits a positive risk–return relation, but empirical evidence is inconclusive. Retail investor sentiment has long been viewed as a distorting factor, while more recently institutional investor sentiment is thought to play a role. We examine the separate and joint impacts of retail and institutional investor sentiments on the risk-return relation. We find, at both market and firm levels, the risk-return relation is more likely to be distorted by the two investor-type sentiments jointly, rather than separately. We further find a cross-sectional pattern, with the risk-return relation being more sensitive to investor sentiment for stocks with specific characteristics.     

Intraday online investor sentiment and return patterns in the U.S. stock market

We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.     

Sentiment and stock market connectedness: Evidence from the U.S. – China trade war

We assess the impact of monthly and daily investor sentiment on stock market return and volatility connectedness during the U.S.-China trade war period. Our analyses focus on the connectedness between the two economies and their major trading partners. We also investigate the asymmetric impact of sentiment on volatility connectedness by exploring the upside and downside markets separately. We consistently document a negative relationship between investor sentiment and stock market connectedness for both return and volatility. We further confirm that investor sentiment exerts a larger impact on volatility connectedness in the downside market compared to the upside market.     

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.