Investor Sentiment Stock Research Articles

How Do Structural Oil Price Shocks Affect China's Investor Sentiment? The Critical Role of OPEC Oil Supply Shocks*

AbstractThis paper applies a modified structural vector autoregressive (SVAR) model to explore whether explicit structural oil price shocks affect investor sentiment in China's stock market. The results indicate that China's investor sentiment responds significantly positively to OPEC supply shocks, while it responds significantly negatively to oil‐specific demand shocks. However, China's stock investor sentiment does not respond to aggregate demand shocks and non‐OPEC supply shocks. In addition, OPEC supply shocks and oil‐specific demand shocks have greater explanatory power for variations in stock investor sentiment through variance decomposition.

The term structure effects of individual stock investor sentiment on excess returns

AbstractIn this paper, we construct the individual stock sentiment indexes at daily, weekly and monthly frequencies. We empirically demonstrate the different effects of individual stock sentiment of three frequencies on the excess returns. The results show that the effect of individual stock sentiment on excess returns is a monotonous decreasing function of time term in China's stock market, which presents obvious term structure effect. Moreover, we find that sentiment factor can better explain the variation of excess returns than size factor and book‐to‐market factor do at the same frequency, and thus we should pay more attention to the individual effect of investor sentiment in the short‐term decision‐making. Our results shed new light on the short‐sighted behaviour of irrational investors and the micro‐mechanism of sentiment effect.

Can Stock Investor Sentiment Be Contagious in China?

This paper explores the impact of investor sentiment on financial markets in China by taking the quantile causality test. We find that government bond markets, gold markets, and foreign exchange markets are affected by stock investor sentiment, except for in the corporate bond market. In extreme situations, such as excessively optimistic or pessimistic sentiment, these markets will become more vulnerable to suffering from drastic fluctuations. On the contrary, the market return in government bonds, corporate bonds, and foreign exchange also has an influence on stock investor sentiment. Moreover, these links show various asymmetry due to the heterogeneity of different financial markets. Our results are consistent with the noise trader model, which shows the impact of investor sentiment on market returns. Hence, the authorities can sustain the stabilization of financial markets by reducing information asymmetry, guiding the rational sentiment of investors, and increasing effective regulations.

Internet finance investor sentiment and return comovement

Abstract Since more and more investors are affected by the Internet finance, this paper focuses on examining whether the systematic trading among investors would lead to stock return comovements beyond the usual risk factors. Internet finance investor sentiment index (IFIS) measures the sentiment related to Internet finance investors' behaviors, which is found to be a systematic factor of stock market returns. To clarify the influence mechanism of IFIS, two groups of portfolios are constructed. First, stocks are sorted into three portfolios according to their degrees of relevance to Internet financial products. IFIS has more significant impact on stocks of firms closely linked to Internet financial products. Second, the role of IFIS on return comovements is further examined using size portfolios. Interestingly, IFIS has significant incremental explanatory power, beyond Fama and French (2015) five factors, on return comovements for stocks with larger market capitalization. This phenomenon is contradictory to the findings by using existing stock investor sentiment in the literature. Our findings have strong implications for research on Internet finance and stock return comovements.

Individual Stock Cash Inflow–Outflow Imbalance, Individual Stock Investor Sentiment and Excess Returns

ABSTRACTBehavioral finance research presents evidence of the importance of “anomaly factors” in the stock market. In this article, we develop an individual stock cash inflow–outflow imbalance index based on individual stock cash inflow and cash outflow and further examine the combined effects of individual stock cash inflow–outflow imbalance and individual stock investor sentiment on excess returns. Our results show that the combined effect of individual stock cash inflow–outflow imbalance and individual stock investor sentiment on excess returns is stronger positive relation. Furthermore, we find that increasing individual stock cash inflow will increase excess returns; on the contrary, increasing individual stock cash outflow will decrease excess returns. Overall, our results highlight the importance of individual stock cash inflow, cash out flow, and cash inflow–outflow imbalance on asset pricing.

A New Investor Sentiment Index Model and Its Application in Stock Price Prediction and Systematic Risk Estimation of Bull and Bear Market

Many studies in recent years have shown that investor sentiment affects investor decision-making, which in turn affects stock market volatility and the direction of stock market prices. Since behavioral finance researchers find that linear combinations of stock turnover and popularity indices can greatly reflect stock investor sentiment, this paper aims to construct a new investor sentiment index that can be reasonably applied to predict stock market risk by selecting rational factors. A new investor sentiment index model is first proposed by combining specific monthly new account ratio (SNIA), monthly turnover rate (TOR), popularity index AR, delayed yield (DY) and using principal component analysis approach. Secondly, the indicator is statistically tested. The results of the correlation analysis show that the investor sentiment index is positively correlated with the monthly rate of return, and the result of causal analysis reveals that the investor sentiment index is the Granger cause of the change in yield. Thirdly, a new method is designed to predict the stock price trend by using the presented investor sentiment index. Finally, based on VaR and CoVaR model the investor sentiment index can be utilized to forecast and estimate of systematic risk in the bull or bear market.

The role of stock price synchronicity on the return-sentiment relation

Abstract Traditional finance leaves no roles for investor sentiment on account of the efficient information and arbitrage. This paper investigates how information adjusts the individual stock investor sentiment effects on stock prices. We find that the return-sentiment relations on stocks with low stock price synchronicity outperform those with high stock price synchronicity. Moreover, the return-sentiment relations remain positive and significant among stock portfolios doubled-sorted by stock price synchronicity and limit-of-arbitrage variables, which implies that limits of arbitrage worsen information environment and weaken the roles of stock price synchronicity on the return-sentiment relation. Finally, this paper decomposes the individual stock investor sentiment and confirms the roles of the components of individual stock investor sentiment on stock prices. Overall, this paper confirms the roles of individual stock investor sentiment on stock prices.

Transmission characteristics of investor sentiment for energy stocks from the perspective of a complex network

Energy stock investor sentiment reflects the investment desires and expectations of investors and plays a significant role in the investment decision-making process and in asset value. There are many ways to measure investor sentiment; for example, the development of the Internet makes it possible to use the online comments of investors to portray their sentiments. Taking a complex network perspective, this paper selected the PetroChina Company Limited as the research object, obtained 96839 investor online comments and analyzed their emotional tendencies and sentiment transmission process. In addition, on this basis, we examined the relationship between investor sentiment and stock price volatility to analyze the transmission characteristics of investor sentiment. The results show that, overall, PetroChina investor sentiment experienced stable fluctuations over the past five years, and stock returns fluctuated within the range of investors’ acceptable volatility. In addition, a weak positive correlation is found between investor sentiment and stock returns. The investor sentiment transmission network has scale-free characteristics and cluster effects. This paper is helpful for understanding the behavior of investors in the stock market, and it provides a new perspective on the relevance of unstructured text and structured data.

Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification

This article verifies whether the hypothesis of heterogeneous agent modelling and the behavioural heterogeneity framework can reproduce recent stylized facts regarding stock markets (e.g. the 1987 crash, internet bubble, and subprime crisis). To this end, we investigate the relationship between investor sentiment and stock market returns for the G7 countries from June 1987 to February 2014. We propose an empirical non-linear panel data specification based on the panel switching transition model to capture the investor sentiment-stock return relationship, while enabling investor sentiment to act asymmetrically, non-linearly, and time varyingly according to the market state and investor attitude towards risk. Our findings are twofold. First, we show that the hypotheses of efficiency, rationality, and representative agent do not hold in reproducing stock market dynamics. Second, investor sentiment affects stock returns significantly and non-linearly, but its effects vary with the market conditions. Indeed, the market appears predominated by fundamental investors in the first regime. In the second regime, investor sentiment effect is positively activated, increasing stock returns; however, when their overconfidence sentiment exceeds some threshold, this effect becomes inverse in the third regime for a high threshold level of market confidence and investor over-optimism.

Individual stock crowded trades, individual stock investor sentiment and excess returns

Abstract Recent behavioral asset pricing models and the popular press suggest that investors may follow similar strategies resulting in crowded equity positions to push prices further away from fundamentals. This paper develops a new approach to measure individual stock crowded trades, and further investigates the joint effects of individual stock crowded trades and individual stock investor sentiment on excess returns. Specifically, our results show that the combined effect of individual stock crowded trades and individual stock investor sentiment on excess returns is positive and significant, which reveals the importance of “anomaly factors” in asset pricing. Furthermore, our results suggest that increasing individual stock buyer-initiated crowded trades will increase excess returns simultaneously; however, increasing individual stock seller-initiated crowded trades will decrease excess returns simultaneously. Collectively, our results highlight the importance of individual stock crowded trades and individual stock investor sentiment on the formation of stock prices.

Stock Return Predictability and Investor Sentiment: A High-Frequency Perspective

We explore the predictive relation between high-frequency investor sentiment and stock market returns. Our results are based on a proprietary dataset of high-frequency investor sentiment, which is computed based on a comprehensive textual analysis of sources from news wires, internet news sources, and social media. We find substantial evidence that intraday S&P 500 index returns are predictable using lagged half-hour investor sentiment. The predictability is evident based on both in-sample and out-of-sample statistical metrics. We document that this sentiment effect is independent of the intraday momentum effect, which is based on lagged half-hour returns. While the intraday momentum effect only exists in the last half hour, the sentiment effect persists in at least the last two hours of a trading day. From an investment perspective, high-frequency investor sentiment also appears to have significant economic value when evaluated with market timing trading strategies.

Stock Return and Investor Sentiment: Evidence for Emerging Market

Stock Return and Investor Sentiment: Evidence for Emerging Market

Selectivity, Style, Sentiment and Skill in Mutual Fund Trades

Fund managers can only exhibit selectivity through purchasing (selling) stocks that appreciate (depreciate) more frequently than expected from random occurrence, if stocks are incorrectly priced. We develop a method that can statistically identify fund managers that exhibit net, buy, and sell selectivity in their trades, as well as distinguish manager skill from fortuitous stock selection. Stock investor sentiment betas are calculated from the recently developed investor sentiment index, and used to indicate stock mispricing. We find that superior stock selection is concentrated in funds that hold high sentiment beta stocks; the major constituent of funds with the aggressive growth objective.

Investor Sentiment and the Performance of Mutual Funds Pursuing Momentum and Contrarian Trading Strategies

The success of mutual funds engaging in momentum and contrarian trading strategies is predicated on the identification of mispriced stocks. Stock investor sentiment betas capture salient characteristics that predispose stocks to mispricing. Funds engage in momentum and contrarian trading in equal proportions, but differ in the sentiment betas of the stocks in their portfolios. Momentum funds hold stocks with higher sentiment betas, and with a wider spread of betas compared to contrarian funds. Fund excess returns are strongly related to Baker and Wurgler’s (2007) change in sentiment index, and the mean and spread of the sentiment betas of their stocks.