The momentum and reversal effects of investor sentiment on stock prices

In this paper, we illustrate the real function relationship between the stock returns and change of investor sentiment based on the nonparametric regression model. The empirical results show that when the change of investor sentiment is moderate, the stock return is positively correlated with the change of investor sentiment, presenting an obvious momentum effect. However, the stock return is negatively correlated with the change of investor sentiment if the change of investor sentiment is dramatic, presenting significant reversal effects. Moreover, the degree of reversal effect caused by extremely optimistic sentiment is greater than that driven by extremely pessimistic sentiment, which shows a significant asymmetry. Our findings offer a partial explanation for financial anomalies such as the mean reversion of stock returns, the characteristic of slow rise and steep fall in China's stock market and so on.     

Impact of network investor sentiment and news arrival on jumps

This paper studied the influence of news announcements and network investor sentiment on Chinese stock index and index futures market jumps. A machine learning text analysis algorithm was employed to measure investor forum sentiment. It was found that news arrivals were an important reason for jump occurrences, jumps were significantly associated with network investor sentiment, and while occasionally the news and network investor sentiment resulted in simultaneous market jumps, they appeared to be relatively independent. The network investor sentiment time-lag and asymmetric effects were also tested, from which it was found that network investor sentiment had a significant asymmetric effect on the jumps, but time-lag effects had little influence. News announcements and the top 25% of the extreme network sentiments were found to explain more than 50% of the jumps, with extreme sentiments tending to increase the volatility of the news-related jumps and persistently influencing returns after the news-related jumps.     

Excess co-movement of agricultural futures prices: Perspective from contagious investor sentiment

This study investigates the excess co-movement of agricultural futures prices from a new perspective of contagious investor sentiment. This study shows that contagious investor sentiment is a key determinant of excess co-movement of agricultural futures prices, by using contagious investor sentiment among different agricultural futures. Further, this study decomposes contagious investor sentiment into expected and unexpected contagious investor sentiment. Results show that both of them can positively affect excess co-movement of agricultural futures prices. More interestingly, expected contagious investor sentiment outperforms unexpected contagious investor sentiment in soybean 1 future, soymeal future, and strong wheat future. In general, the results of this study can provide strong support for the significant roles of contagious investor sentiment in asset pricing applications.     

Risk-neutral skewness and market returns: The role of institutional investor sentiment in the futures market

This paper investigates the effect of index risk-neutral skewness on subsequent market returns and explores whether this effect will vary with various types of institutional investor sentiment in the futures market. Using index futures returns as the proxy of market returns, the empirical results show that the index risk-neutral skewness has a significantly negative effect on subsequent index futures returns. Moreover, the effect of institutional investor sentiment on subsequent index futures returns varies with various types of institutional investor sentiment. Finally, the effect of index risk-neutral skewness on subsequent index futures returns relies on various types of institutional investor sentiment.     

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

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.     

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.     

The effect of market sentiment and information asymmetry on option pricing

This work addresses the impact of imperfections, such as information asymmetry and market sentiment, on the performance of option pricing models. More precisely, this work compares the option pricing model of Black and Scholes and the same model in the presence of imperfections. This study is based on S&P 500 options that cover the period between 17/03/2000 and 14/06/2013. The achieved results show that, in general, in the presence of imperfections, the model is more effective than the Black and Scholes model. This research appears to be promising for the incorporation of imperfections into the assessment of options.     

Impact of investor sentiment on mutual fund risk taking and performance: evidence from China

ABSTRACT

This study provides empirical rationale and guidance for incorporating investor sentiment into mutual fund enterprise information systems. It investigates the effect of fund-specific investor sentiment on fund risk taking and performance. Working on a sample of equity funds in China, our panel regressions reveal that fund risk-taking is negatively related to lagged fund-specific investor sentiment. Investor sentiment is negatively linked to subsequent fund performance, which conforms with the dumb money effect. Encouragingly, there is evidence that mutual fund managers in China possess investing expertise. Fund-specific investor sentiment shows asymmetric impacts. The dumb money effect is primarily driven by positive sentiment.     

Time-varying impact of monetary policy shocks on US stock returns: The role of investor sentiment

This paper investigates how monetary policy shock affects the stock market of the United States (US) conditional on states of investor sentiment. In this regard, we use a recently developed estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks, which in turn is achieved by integrating the current short-term rate surprises, which are least affected by an information effect, into a vector autoregressive (VAR) model as an exogenous variable. When allowing for time-varying model parameters, we find that, compared to the low investor sentiment regime, the negative reaction of stock returns to contractionary monetary policy shocks is stronger in the state associated with relatively higher investor sentiment. Our results are robust to alternative sample period (which excludes the zero lower bound) and model specification and also have important implications for academicians, investors, and policymakers.     

The influence and predictive powers of mixed-frequency individual stock sentiment on stock returns

In this article, we construct mixed-frequency individual stock sentiment using MIDAS model. We first investigate the influence power of mixed-frequency individual stock sentiment on excess returns. The results indicate that the higher the frequency of individual stock sentiment is, the better it explains the variation of excess returns, that mixed-frequency individual stock sentiment, especially mixed high-frequency sentiment, exerts greater influence on excess returns than the same frequency one and that the mixed-frequency sentiment has a stronger explanatory power to the variation of excess returns than size factor, book-to-market factor, profitability factor and investment factor do. Then, we study the predictive content of mixed-frequency individual stock sentiment. The results show that the higher the frequency of individual stock sentiment is, the better the forecast performs. Moreover, by comparing the corresponding statistics in influence and predictive power models, we find that the influence power of mixed-frequency individual stock sentiment is more significant than its predictive power.     

The COVID-19 pandemic uncertainty,investor sentiment,and global equity markets: Evidence from the time-frequency co-movements

We use daily data of the Google search engine volume index (GSVI) to capture the pandemic uncertainty and examine its effect on stock market activity (return, volatility, and illiquidity) of major world economies while controlling the effect of the Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index. We use a time–frequency based wavelet approach comprising wavelet coherence and phase difference for our empirical assessment. During the early spread of the COVID-19, our results suggest that pandemic uncertainty, and FEARS sentiment strongly co-move, and increased pandemic uncertainty leads to pessimistic investor sentiment. Furthermore, our partial wavelet analysis results indicate a synchronization relationship between pandemic uncertainty and stock market activities across G7 countries and the world market. Our results are robust to the inclusion of alternative pandemic fear measure in the form of equity market volatility infectious disease tracker. The pandemic uncertainty and associated sentiment implications could be one plausible reason for increased volatility and illiquidity in the market, and hence, policymakers should look upon this issue for the financial market stability perspective.     

Time-frequency transmission mechanism of EPU,investor sentiment and financial assets: A multiscale TVP-VAR connectedness analysis

This article examines the transmission mechanism of economic policy uncertainty (EPU), investor sentiment and Chinese financial assets from time-frequency and static-dynamic perspectives. The multiscale connectedness method based on time-varying parameter vector autoregression (TVP-VAR) is introduced to explore the time–frequency and static-dynamic spillovers. The empirical results are as follows: First, there is an interdependence between EPU and high-risk assets. Additionally, EPU and high-risk assets spillover risk to investor sentiment individually or in chains, ultimately affecting low-risk assets. Second, high-risk assets spill to low-risk assets in the short term but reverse in the long term. Third, EPU spills over to the system the most around 2008, especially in the long term. In addition, high-risk assets are the largest risk spillover and recipient at each frequency over the last decade. Overall, investors and regulators should consider real-time financial monitoring solutions in China based on economic policy uncertainty and investor sentiment factors.     

Spillover and connectedness among G7 real estate investment trusts: The effects of investor sentiment and global factors

This paper examines the dynamic spillover interconnectedness of G7 Real Estate Investment Trusts (REITs) markets. We use the spillover index of Diebold and Yilmaz (2012), the time-varying parameters vector-autoregression (TVP-VAR) model, and the quantile regression approach. The result show that REITs network connectedness is dynamic and experiences an abrupt increase in the first wave of COVID-19 outbreak (2020Q1). We also observe a substantial abrupt decrease in connectedness during the success of vaccination programs (end 2021). The connectedness among assets is much stronger during COVID-19 than before. The REITs of Japan and Italy are net receivers of spillover and those of US and UK are net transmitters of spillovers before and during COVID-19. Conversely, the REIT of Canada and Germany (France) switches from net receivers (contributors) of spillovers before the pandemic to net contributors (receivers) during the COVID-19. Finally, we show that News Sentiment index, Geopolitical Risk index, Economic Policy Uncertainty index, US Treasury yield, and Stock Volatility index influence the spillover magnitude across quantiles.     

投资者结构对于期货市场流动性影响的仿真研究

流动性是体现金融市场的质量与效率的简洁有效的指标之一,文章拟用u-mart平台就投资者结构对期货市场流动性的影响进行仿真研究。指出噪音交易者对于提供市场流动性的作用。其在市场参与者中的比例与市场流动性的关系并不能完全确定,但大约占60%时效果最好。     

Spillovers of currency carry trade returns,market risk sentiment,and U.S. market returns

This paper examines the link between spillovers of currency carry trade returns and U.S. market returns. Following Tse and Zhao (2012), this paper hypothesizes that the magnitude of spillovers of currency carry trade returns is positively correlated with market risk sentiment and, therefore, has an impact on market returns. Using the G10 currencies and S&P 500 index futures, the empirical results present a high magnitude of spillover effects of currency carry trade markets. The empirical findings also show a significantly positive relationship between spillovers of currency carry trade returns and subsequent market returns. Furthermore, the results indicate that this relationship is stronger in bear markets than in bull markets. Finally, our findings show that spillovers of currency carry trade returns significantly affect the subsequent transition probabilities of market returns.     

投资者情绪对封闭式基金折价的影响研究述评

封闭式基金折价问题由来已久,本文对国内外文献进行梳理,从基本面因素、情绪因素等角度分别对封闭式基金折价问题进行剖析,本文的亮点在于追根溯源从心理学角度寻找投资者情绪的特征,从心理学文献中寻找折价的原因,并根据国内外文献,提出封闭式基金折价问题研究的切入点。     

Intraday return predictability in the cryptocurrency markets: Momentum,reversal, or both

This paper reports evidence of intraday return predictability, consisting of both intraday momentum and reversal, in the cryptocurrency market. Using high-frequency price data on Bitcoin from March 3, 2013, to May 31, 2020, it shows that the patterns of intraday return predictability change in the presence of large intraday price jumps, FOMC announcement release, liquidity levels, and the outbreak of the COVID-19. Intraday return predictability is also found in other actively traded cryptocurrencies such as Ethereum, Litecoin, and Ripple. Further analysis shows that the timing strategy based on the intraday predictors produces higher economic value than the benchmark strategy such as the always-long or the buy-and-hold. Evidence of intraday momentum can be explained in light of the theory of late-informed investors, whereas evidence of intraday reversal, which is unique to the cryptocurrency market, can be related to investors’ overreaction to non-fundamental information and overconfidence bias.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

The impact of individual investor trading on information asymmetry in the Korean stock market

This paper examines the impact of individual investor trading on information asymmetry in the market. In particular, we examine the relationship between the trading volume by individual investors and the corresponding bid-ask spread in the Korean stock market, where the majority of the trading activity is driven by individual investors and therefore information asymmetry can be evident. We find that high trading activity by individual investors increases the bid-ask spread in a short investment horizon, suggesting that individual investors, as uninformed and unsophisticated traders, amplify the degree of information asymmetry in the market through trading.     

Evaluation of a Flemish Active Labour Market Policy in the framework of the European Social Fund. Results and challenges

The aim of this paper is to evaluate the “Work Experience for Young Persons” (WIJ) programme, which was implemented in Flanders between 2015 and 2018. The WIJ programme is partially financed through the European Social Fund (ESF) and targets unqualified, young, and unemployed people with the aim of facilitating their entry to the labour market. The programme involves a trajectory of intensive guidance that includes labour market orientation and coaching as first phase, plus competence strengthening activities as second phase. This analysis is based on the Flemish Public Employment Service’s administrative data sources, which allows us to exploit detailed information on previous labour market history. We apply Coarsened Exact Matching to evaluate the WIJ’s impact on young unemployed people specifically in terms of their probability of being employed, unemployed or inactive, and of re-entering into education. Our results suggest that those who have participated in the WIJ programme have lower employment and education probabilities with respect to those who participated in the standard activities proposed by the public employment service. However, we found a positive employment effect if we only consider those who participated in the standard trajectory, i.e. those whose WIJ intervention lasted fewer than 14 months; this means that the negative effects are driven by those young individuals following the extended trajectories.