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This paper studies the relationship between corporate social responsibility (CSR) and stock price volatility based on data of Chinese A-share listed companies from 2010 to 2018, and further analyses the path and underlying mechanism of CSR that affects stock price volatility. With China's gradual transition to a sustainable development model, both public and the government are paying increasing attention to CSR performance. At the same time, the Chinese government takes a more serious attitude towards systemic financial risks, emphasising the importance of controlling systemic risks such as an abnormal stock price on many public occasions. In this context, CSR and stock price volatility have received unprecedented attention, and it's of great value for both industry and the government to explore the impact of CSR on stock price volatility. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of investor investment sentiment on individual stock returns in China. We find that investment sentiment is positively associated with stock performance contemporaneously. The Granger Causality test shows that investor sentiment is a driving force of stock price movement but not the other way around. Our constructed VAR model further suggests that the change in investor sentiment in the lagged period does not significantly affect the current stock return. In addition, both the Impulse Response and the Variance Decomposition analysis provide evidence that the stock price will increase right after a positive sentiment shock, and then follow a price drop until an intrinsic value comes up. Overall, the investor sentiment factor has a strong explanatory power to explain the variation in stock return. [ABSTRACT FROM AUTHOR]

This paper discusses whether investor sentiment contains useful information to predict volatility by constructing investor pessimism index based on Baidu, which is the largest search engine in China. We discover that the investor pessimism index is significantly negatively correlated with contemporaneous returns but predicts following days' returns reversals. Furthermore, the heterogeneous autoregressive model of realized volatility (HAR‐RV) with investor pessimism index performs better than other HAR‐RV‐type benchmark models. We perform a series of robustness tests, which include alternative construction of investor pessimism index, crisis subsample, alternative predictive model, alternative measures of volatility, and considering the role of institutional investor. Our results remain robust. Taken together, investor pessimism index constructed in this paper seem to be a suitable proxy to measure investor sentiment in China and can enhance the accuracy of volatility forecasting in the Chinese stock market. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to expand the investor sentiment’s effect on investment efficiency to the layer of “credit financing,” studying whether investor sentiment can affect credit financing level and the inner mechanism of the effect. Design/methodology/approach – The authors obtain firm-level data from the Shanghai and Shenzhen stock markets and using panel estimation techniques examine whether investor sentiment can affect credit financing level and the inner mechanism of the effect. Findings – This paper finds that credit financing plays the role of partial media in the process of investor sentiment affecting investment efficiency. Based on the funds increasing effect, with the high-investor sentiment and increasing credit financing, corporations alleviate the financing constraints, but also provide a convenient for the abuse of corporate funds. So, investor sentiment positively associates with enterprises’ overinvestment, while investor sentiment negatively associates with enterprises’ underinvestment. Relying on the particular system background and property right environment in China, this paper finds that investor sentiment has an effect on the overinvestment of state-owned enterprises and the underinvestment of private enterprises through credit financing channel, while it does not function in the overinvestment of private enterprises. The reason of the difference is that under the soft budget constraint in the country, the credit preference of state-owned enterprises and the creditor’s rights management of banks are partially absent. Research limitations/implications – By fusing the special financial environment and institutional background, this thesis further includes in the analysis frame the difference in governance effect by credit financing between state-owned and privately owned listed companies, and further analyzes the difference in impact on investment efficiency in enterprises of different natures after investor sentiment has affected enterprise credit financing. Practical implications – This paper has verified the constraint assumption and deepened the research work on bank credit supply and answered practical questions such as whether the banks in the country exercise supervision function over the listed companies and on which kind of listed companies the supervision function plays a more effective role. Social implications – As an unofficial substitution mechanism, bank-enterprise relationship can elevate the investment efficiency by private owned enterprises. Based on the timely research results on credit financing, reference is provided for private listed companies to utilize investor sentiment to improve its investment efficiency. Originality/value – This paper has proved the specific path which creates the dual effects on resources allocation by investor sentiment, that is, the intermediary transmission in credit financing, clarifying the mechanism of action by which investor sentiment affects the efficiency of enterprise investment and making incremental contribution to the research of how investor sentiment affects the efficiency of enterprise investment. [ABSTRACT FROM AUTHOR]

Purpose: While the classic futures pricing tool works well for capital markets that are less affected by sentiment, it needs further modification in China's case as retail investors constitute a large portion of the Chinese stock market participants. Their expectations of the rate of return are prone to emotional swings. This paper, therefore, explores the role of investor sentiment in explaining futures basis changes via the channel of implied discount rates. Design/methodology/approach: Using Chinese equity market data from 2010 to 2019, the authors augment the cost-of-carry model for pricing stock index futures by incorporating the investor sentiment factor. This design allows us to estimate the basis in a better way that reflects the relationship between the underlying index price and its futures price. Findings: The authors find strong evidence that the measure of Chinese investor sentiment drives the abnormal fluctuations in the basis of China's stock index futures. Moreover, this driving force turns out to be much less prominent for large-cap stocks, liquid contracting frequencies, regulatory loosening periods and mature markets, further verifying the sentiment argument for basis mispricing. Originality/value: This study contributes to the literature by relying on investor sentiment measures to explain the persistent discount anomaly of index futures basis in China. This finding is of great importance for Chinese investors with the intention to implement arbitrage, hedging and speculation strategies. [ABSTRACT FROM AUTHOR]

This paper introduces a weather-related sentiment (mood) index (WSI) for the Chinese stock market based on precipitation and temperature data with the PLS method. We find that the WSI is negatively correlated with the equity market and has strong predictive power that is far greater than that of other market and macroeconomic variables. The predictability also holds under the characteristic-mimicking portfolios. The driving force of the WSI's predictive power appears to stem from its ability to predict future cash flow, which reflects investor preference. [ABSTRACT FROM AUTHOR]

This paper studies the effect of structural oil price shocks on China's investor sentiment using the Bayesian inference structural vector autoregression (VAR) model by Baumeister and Hamilton (2019). We find that oil supply shocks followed by consumption demand shocks have positive and persistent effects on China's investor sentiment, whereas aggregate and inventory demand shocks have only temporary effects. The effects of these shocks are transmitted mainly by affecting investor's confidence in domestic economic fundamentals and the international economic environment. Furthermore, oil price shocks also induce different trading motivations in the stock market. [ABSTRACT FROM AUTHOR]

The People's Republic of China has increasingly become an attractive location for foreign capital. The flow of foreign capital into mainland China includes the so-called northbound cash flow which is a colorful term that is often used to describe capital flowing into the mainland from Hong Kong. Two markets that have become an attractive destination for northbound cash flow is the Shanghai stock exchange and the Shenzhen stock exchange. This paper investigates the impact, if any, of northbound cash flows on investor sentiment for investors residing in mainland China. In other words, the paper attempts to ascertain whether the extent of northbound cash flows influences the extent to which mainland investors feel either bullish or bearish about the market. The research objective is addressed using quantitative models and focuses on the Shanghai and Shenzhen stock exchange. Research results indicate that northbound cash flows from Hong Kong significantly impacts investor sentiment in mainland China. [ABSTRACT FROM AUTHOR]

Purpose: The focus of the current research is to examine whether mixed-frequency investor sentiment affects stock volatility in the China A-shares stock market. Design/methodology/approach: Mixed-frequency sampling models are employed to find the relationship between stock market volatility and mixed-frequency investor sentiment. Principal analysis and MIDAS-GARCH model are used to calibrate the impact of investor sentiment on the large-horizon components of volatility of Shanghai composite stocks. Findings: The results show that the volatility in Chinese stock market is positively influenced by B–W investor sentiment index, when the sentiment index encompasses weighted mixed frequencies with different horizons. In particular, the impact of mixed-frequency investor sentiment is most significantly on the large-horizon components of volatility. Moreover, it is demonstrated that mixed-frequency sampling model has better explanatory powers than exogenous regression models when accounting for the relationship between investor sentiment and stock volatility. Practical implications: Given the various unique features of Chinese stock market and its importance as the major representative of world emerging markets, the findings of the current paper are of particularly scholarly and practical significance by shedding lights to the applicableness GARCH-MIDAS in the focused frontiers. Originality/value: A more accurate and insightful understanding of volatility has always been one of the core scholarly pursuits since the influential structural time series modeling of Engle (1982) and the seminal work of Engle and Rangel (2008) attempting to accommodate macroeconomic factors into volatility models. However, the studies in this regard are so far relatively scarce with mixed conclusions. The current study fills such gaps with improved MIDAS-GARCH approach and new evidence from Shanghai A-share market. [ABSTRACT FROM AUTHOR]

This paper analyzes the predictive ability of aggregate and disaggregate proxies of investor sentiment, over and above standard macroeconomic predictors, in forecasting housing returns in China, using an array of machine learning models. We find that our new aligned investor sentiment index has greater predictive power for housing returns than the principal component analysis (PCA)‐based sentiment index, used earlier in the literature. Moreover, shrinkage models utilizing the disaggregate sentiment proxies do not result in forecast improvement indicating that aligned sentiment index optimally exploits information in the disaggregate proxies of investor sentiment. Furthermore, when we let the machine learning models to choose from all key control variables and the aligned sentiment index, the forecasting accuracy is improved at all forecasting horizons, rather than just the short‐run as witnessed under standard predictive regressions. This result suggests that machine learning methods are flexible enough to capture both structural change and time‐varying information in a set of predictors simultaneously to forecast housing returns of China in a precise manner. Given the role of the real estate market in China's economic growth, our result of accurate forecasting of housing returns has important implications for both investors and policymakers. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to study the influence of investor sentiment on the supply of trade credit, and further explores the difference of the effect of investor sentiment on the supply of trade credit in the environment of strong market competition and weak market competition. Design/methodology/approach: The authors use panel estimation techniques to examine the impact of investor sentiment in the Chinese securities market on the supply of corporate trade credit. Findings: This paper finds that investor sentiment has positive impact on trade credit through three channels of motivation, willingness and ability. At the same time, this paper finds that investor sentiment has stronger impact on enterprises in strong market competition than enterprises in weak market competition. Research limitations/implications: This paper expands the research on the influence of virtual economy on the real economy, analyzes the difference of the influence of investor sentiment on the supply of trade credit under different market competition conditions. Practical implications: The paper perfects the mechanism of trade credit decision-making at this stage, and provides more evidence for the virtual economy to act on the real economy. Social implications: This paper provides a theoretical basis for the government functional departments to use the investor sentiment to play a positive role in trade credit to improve the market competition and guide the development of China's capital market in the direction of rationalization and health. Originality/value: In combination with market competition environment and industry characteristics, this paper investigates external irrational factors and studies how investor sentiment affects trade credit supply. [ABSTRACT FROM AUTHOR]

This paper aims to examine the impact of regulatory policies on cryptocurrency market volatility in the context of the COVID-19 pandemic. We find that price volatility, liquidity volatility, and return volatility in the cryptocurrency market increased significantly following regulatory announcements by Chinese policymakers targeting the cryptocurrency industry, and this effect was more pronounced during the COVID-19 pandemic. It indicates that investors are paying a great deal of attention to such events. Yet further findings suggest that as the risk of pandemic transmission increases and stock market returns decline, investor response to regulation decreases. Our findings also suggest that while regulation typically brings market volatility in cryptocurrencies, the release of regulatory policies can instead be beneficial to the stability of the cryptocurrency market when investors are in an highly greedy mood. • Regulatory policies cause market volatility in cryptocurrencies. • COVID-19 transmission risk affects investors' negative reaction to regulation. • Cryptocurrencies are potential safe havens during COVID-19. • Regulatory policies reduce cryptocurrency investor greed. [ABSTRACT FROM AUTHOR]

This paper investigates the multiscale dynamic relations between China Central Television News (CCTV News) and investor sentiment in China by employing the wavelet method. We document significant positive correlations between CCTV News's economic focus/economic tone and investor sentiment at the raw and high-frequency levels using the wavelet DCC-GARCH model. Wavelet Granger causality tests and wavelet coherence analysis confirm that the economic focus/economic tone of CCTV News is dominant and leads investor sentiment for short-term investors. At the same time, investor sentiment can conversely affect CCTV News's economic focus/economic tone for medium-term investors. There is a long-term interdependence between CCTV News's economic focus/tone and investor sentiment. Furthermore, the interaction between CCTV News and investor sentiment increases in turbulent periods compared with relatively calm periods. Finally, we find that CCTV News's economic focus and tone positively affect the stock market returns. The influence seems to be an overreaction in the short term and an underreaction in the long term. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the MSCI China A-shares index (MCASI) and analyze MCASI's properties. From the perspective of index investment, we found that MCASI's investor sentiments, both overnight sentiment and BW sentiment, provide significant predictability for future MCASI returns, supported by the in-sample and out-of-sample results. From the perspective of sector investment, we show that the sector portfolio of "information transfer, software and information technology services" performs the best among the 10 sector portfolios. In addition, seven approaches of the optimal portfolio in ten sectors are examined, and the results suggest that the classic Markowitz portfolio approach is recommended. Our empirical analysis is helpful for domestic and foreign investors seeking to form investment strategies for MSCI China A-shares. [ABSTRACT FROM AUTHOR]

This paper describes a novel approach to measure individual investor sentiment using text-based analysis of millions of posts extracted from Chinese financial online forums. We describe how we built a database of more than 200 million stock posts from online financial forums, created GubaLex, a sentiment dictionary consisting of 48,878 words to allow sentiment analysis, and how we developed GubaSenti, an individual investor sentiment index for the stock market in China. This allowed (1) the first systemic measurement of individual investor sentiment in China; (2) an approach to text-based analysis that reflects investor sentiment about millions of posts about stocks listed in Guba; (3) a way to flexibly measure investor sentiment of a single stock, a sector or an industry and the whole market; and (4) made this possible for daily, weekly, monthly, quarterly, and yearly time periods. We also examine the relationship of the sentiment proxy and stock returns and compare it with two typical BW metrics in China. Empirical results show that GubaSenti correlates better with market performance than BW metrics in China and can be used to predict market changes in the short term. [ABSTRACT FROM AUTHOR]

This paper aims to explore the dynamic relationships between the crude oil price (shocks) and investor sentiment. Specifically, this paper utilizes web crawler to construct Chinese investor sentiment index. The structural vector autoregression (SVAR) model is then used to decompose the crude oil price shocks into three types of oil price shocks. Finally, the wavelet coherence analysis (WTC) is employed to study the dynamic correlation between crude oil price (shocks) and investor sentiment in the time and frequency domain, and their asymmetric dynamic correlation under different trends of crude oil price. Using data from February 2013 to June 2021, our empirical results suggest the heterogeneous dynamic correlations and lead-lag relationships exist between crude oil price (shocks) and investor sentiment over different time and frequency domains. In addition, there are asymmetric dynamic correlations and lead–lag relationships between crude oil price (shocks) and investor sentiment under different trends of crude oil price. [ABSTRACT FROM AUTHOR]

This study employs a fixed-effects model to investigate the holiday effect in the cryptocurrency market, using trading data for the top 100 cryptocurrencies by market capitalization on Coinmarketcap.com from January 1, 2017 to July 1, 2022. The results indicate that returns on cryptocurrencies increase significantly during Chinese holiday periods. Additionally, we use textual analysis to construct an investor sentiment indicator and find that positive investor sentiment boosts cryptocurrency market returns. However, when positive investor sentiment prevails in the cryptocurrency market, the holiday effect weakens, implying that positive investor sentiment attenuates the holiday effect. Robustness tests based on the Bitcoin market generate consistent results. Moreover, this study explores the mechanisms underlying the cryptocurrency holiday effect and examines the impact of epidemic transmission risk and heterogeneity characteristics on this phenomenon. These findings offer novel insights into the impact of Chinese statutory holidays on the cryptocurrency market and illuminate the role of investor sentiment in this market. [ABSTRACT FROM AUTHOR]

Using a database of the trading data in the Chinese stock market over January 2005 to June 2012, this paper studies the stock market crisis based on the perspective of behavioural finance. Investor sentiment is based on B‐W method, and the possibility of the Shanghai stock market crisis was predicted by the logit model. The empirical results show that investor sentiment, which is more significant than the macroeconomic variables, has a significant positive impact on stock market crisis after controlling for the economic variables. Moreover, our results offer an empirical explanation for the financial anomaly of mean reversion. Both in‐sample and out‐sample data tests show that the logit model with investor sentiment is able to predict stock crises. [ABSTRACT FROM AUTHOR]

Purpose The purpose of the paper is to examine the impact of investor sentiment on managers’ decisions to provide CSR disclosures. The core issue focuses on whether, why and how managers adjust their approach to CSR disclosure to cater to the investor sentiment.Design/methodology/approach On the basis of 13,488 observations of A-share listed companies, the authors examine the impacts of investor sentiment on CSR disclosure, which is measured separately by the propensity to issue a standalone CSR report and the quality of CSR reports. Furthermore, the authors examine the moderating role of institutional factors in China.Findings The authors find that during low-sentiment periods, managers are more likely to issue a standalone CSR report and the quality of CSR reports is higher, and vice versa. Additionally, the authors find that the negative correlations between CSR disclosure and investor sentiment are stronger in state-owned enterprises.Research limitations/implications First, the measurement of investor sentiment reflects only a part of characteristics of investor sentiment. Second, the authors pay less attention to the specific items of a CSR report.Originality/value The study contributes to the literature on CSR disclosure and investor sentiment by combining the two fields together. Furthermore, the study deepens the understanding of the institutional context in China and contributes to research on the predictors of CSR disclosure. [ABSTRACT FROM AUTHOR]

Based on five original sentiment indicators in Hong Kong stock market, including the closed-end fund discount rate, the average first-day returns of initial public offering (IPO), the number of IPO, the market trading volume and turnover, this paper uses the principal component analysis method to calculate a comprehensive investor sentiment index. After excluding the trend and seasonal factors from the comprehensive investor sentiment index and Hong Kong Hang Seng Index by autoregressive moving average-generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) family models, this paper makes correlation analysis and Granger causality test on the residuals of ARMA-GARCH model. The study shows that ARMA-GARCH models can effectively process the autocorrelation and heteroscedasticity of investor sentiment index and Hong Kong Hang Seng Index. Also, it indicates that the Hang Seng index return is the Granger cause of investor sentiment in short terms while not in long terms. That is to say investor sentiment would be more optimistic in short terms when the Hong Kong stock market goes up, and vice versa. [ABSTRACT FROM AUTHOR]

In this study, we used data on China's initial public offerings (IPOs), market volatility and macro environment before and after two stock crashes during 2006–2016 to investigate how different investor sentiment affects IPO first-day flipping. The empirical results show that the expected returns of allocated investors are affected by sentiment, with allocated investors having higher psychological expectations of future returns during an optimistic bull market and their optimism discouraging first-day flipping, while higher risk-free interest rate levels and rising broad market indices also discourage first-day flipping and tend to sell in the future. The pessimistic bear market during which allocated investors have lower psychological expectations of future returns, their pessimism will promote first-day flipping, and the increase in the risk-free rate level will also promote first-day flipping, which is the opposite of the optimistic bull market, indicating that their risk aversion has increased and they tend to sell on the same day. We also found an anomaly that the greater the decline in the broad market index during a pessimistic bear market, the more inclined the allocated investors are to sell in the future when the broad market index rises in an attempt to gain higher returns. These findings help explain and understand the impact of market and macro index fluctuations on investor behavior under different investor sentiments. [ABSTRACT FROM AUTHOR]

This paper studies the impact of investor sentiment on corporate investment efficiency from perspective of controlling shareholders’ catering. Using a sample comprises of the listed Chinese manufacturing companies from 2004-2013, the paper concludes that the controlling shareholders in highly share-concentrated companies not only have the ability and motivation to garb interests from the minority shareholders for PBC, but also can moderate the investor sentiment’s impact on corporate investment efficiency. Besides, different share-holding ratio of controlling shareholders, separation of control rights and cash flow rights, controlling shareholders’ nature were found to have different moderating effect. [ABSTRACT FROM AUTHOR]

This study analyzes air quality as a factor affecting Chinese stock market liquidity through the transmission mechanism of investor sentiment. Monthly time-series data from 2014 to 2018 are selected to analyze the air quality index, investor sentiment index, and turnover rate. The static and dynamic relationships among air quality, investor sentiment, and stock market liquidity are investigated using a multiple linear regression model. The inverse effect of stock market liquidity on air quality is analyzed based on the results of impulse response functions, variance decomposition, and the environmental Kuznets curve theory. We find that air pollution can negatively affect investors. Therefore, when facing negative emotion, investors choose to react passively, which reduces stock market liquidity. Furthermore, we find that stock market liquidity and air quality have an inverted U-shaped relationship. Pursuing higher liquidity comes at the expense of the environment, which exacerbates air pollution, thereby causing obviously abnormal behavior and threatening economic development. Based on these findings, this study proposes regulations and economic methods to improve air quality. Other policy recommendations include strengthened investor financial literacy and information disclosure to deter feelings of negativity about air pollution, which would ultimately promote stock market liquidity and economic development. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper uses an agent-based model to study the sentiment contagion of interacting investors in China. We use text mining techniques to identify investor sentiment in stock forum, and then estimate the parameters of the sentiment contagion model to analyze sentiment formation from individual perspective. The empirical results suggest that the intensities of sentiment contagion in the periods of rising and falling are higher than that of the storming period. Intensities of sentiment contagion in emerging industries are higher than basic industries. A favorable macroeconomic environment will promote investors' optimism of the stock market, and high degree of investors' attention and discussions will accelerate contagion of such optimism. Once the stock market tends to be overheated, it may cause investors to worry about the market bubble, which will restrain further rise of investor sentiment. • Sentiment contagion intensity in rise or down stage is higher than storming stage. • The industries not directly linked to entity economy has higher contagion intensity. • The industries with lower sentiment contagion intensity are more basic. • Good macroeconomy and high investor attention will promote optimism sentiment. • The overheated stock market will restrain further rise of investor sentiment. [ABSTRACT FROM AUTHOR]

By using the relationship between high sentiment and momentum, the main purpose of this paper is to investigate if psychological biases of investors have an influence on behavioral biases. We find that in the China stock market, high sentiment of loser groups is correlated with contributors of momentum profits, while high sentiment of winner groups is correlated with contributors of contrarian returns. Further analysis indicates that, the higher the investor psychological bias is, the greater the momentum return will become. Winners/losers that are most sensitive to sentiment and having the longest duration of being kept under the situation will result in higher returns. [ABSTRACT FROM AUTHOR]

This study investigates the influence of earnings-related social media discussion on stock returns surrounding the earnings announcement. By using deep learning approach to develop a new measure of market-wide earnings expectations based on Chinese Sina Weibo, we find that the constructed Weibo optimism index is positively related to the upcoming earnings announcement returns within a short window. This positive effect is more pronounced for firms with lower-quality earnings and firms with no traditional media coverage. Additionally, we also find that an increase in our Weibo optimism index indicates stronger post-announcement return reversals over a longer window. These results imply that earnings-related social media discussion is largely driven by sentiments, leading investors to overreact to earnings announcements. Our evidence supports the view that social media impedes stock price efficiency in financial markets. [ABSTRACT FROM AUTHOR]

This study examines the heterogeneous effects of the COVID‐19 outbreak on stock prices in China. We confirm what is already known, that the pandemic has had a significant negative impact on stock market returns. Additionally, we find, this effect is heterogeneous across industries. Second, fear sentiment can directly cause stock prices to fall and panic exacerbates the negative impact of the pandemic on stock returns. Third, and most importantly, we demonstrate the underlying mechanisms of four firm characteristics and find that those with high asset intensity, low labor intensity, high inventory‐to‐revenue ratio, and small market value are more negatively affected than others. For labor‐intensive state‐owned firms, in particular, stock performance worsened because of higher idle labor costs. Finally, we created an index to measure the relative position of an industry in the supply chain, which shows that downstream companies were more vulnerable to the effects of the pandemic. [ABSTRACT FROM AUTHOR]

This study builds an agent-based computational finance platform that can reproduce the basic characteristics of China's initial public offering (IPO) market and explain its anomalies. The results of our computational experiments show that along with the increasing proportion of sentiment strategy investors (i.e., those with an information advantage) entering the market, the IPO underpricing rate also rises correspondingly. Sentiment investors usually suffer losses because of their irrational investment decisions, while sentiment strategy investors profit by preying on sentiment investors. [ABSTRACT FROM AUTHOR]

With the development of the social network, the interaction between investors in stock market became more fast and convenient. Thus, investor sentiment which can influence their investment decisions may be quickly spread and magnified through the network, and to a certain extent the stock market can be affected. This paper collected the user comments data from a popular professional social networking site of China stock market called Xueqiu, then the investor sentiment data can be obtained through semantic analysis. The dynamic analysis on relationship between investor sentiment and stock market is proposed based on Thermal Optimal Path (TOP) method. The results show that the sentiment data was not always leading over stock market price, and it can be used to predict the stock price only when the stock has high investor attention. [ABSTRACT FROM AUTHOR]

This study examines the relationship between fund‐level investor sentiment and return volatility of exchange‐traded funds (ETFs). We use the first principle component to form a composite fund‐level investor sentiment index that is based on the common variation in four underlying proxies for individual fund sentiment for each ETF: relative strengthen index, psychological line index, Bull and Bear Index and trading volume. And we employ the GARCH model and the EGARCH model to estimate daily ETFs' return volatility, respectively. In our tests, the panel data regressive analysis reveals that investor sentiment reliably predicts ETFs' return volatility in different periods of sentiment state. Specifically, return volatility increases with investor sentiment in the periods of high‐sentiment state, and decreases with investor sentiment in the periods of low‐sentiment state. Furthermore, the panel quantile regression results exhibit nonlinear patterns across the quantiles obviously: weaker effects for lower quantiles and stronger effects for higher quantiles in general. More importantly, the empirical results are stable across different conditional variance models. [ABSTRACT FROM AUTHOR]

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In recent years, how to increase the property income of Chinese households has aroused widespread attention. Our study focuses on the impact and impact mechanism of digital finance on household investment portfolio efficiency in China. Our study reveals that digital finance in China can promote household investment portfolio efficiency. Digital finance development mainly affects household investment efficiency by influencing financial literacy and investor sentiment. Further, we found that household wealth had an inverted U-shaped effect on the impact of digital finance on household investment efficiency. And the enhancement of households' preference for overconsumption inhibited the impact of digital finance on household investment portfolio efficiency. [ABSTRACT FROM AUTHOR]

Using the Hubei province in China as the COVID‐19 pandemic epicenter and January 23, 2020 as the event date (the date the Chinese government announced the lockdown of Wuhan, the provincial capital), we document that while Chinese firms generally exhibited negative cumulative abnormal returns (CARs) around the event date, firms located far from the Hubei province experienced relatively less adverse impact by way of negative CARs than firms located close to and in the province. Moreover, firms that engaged strongly in corporate social responsibility (CSR) activities in terms of corporate donations prior to the event date experienced less of an adverse impact than those with no or weak CSR activities, suggesting that CSR serves an insurance‐like function that alleviates the adverse impact on stock returns precipitated by the negative investor sentiment stemming from COVID‐19. [ABSTRACT FROM AUTHOR]

At present, integrating investor sentiment into the prediction of stock market crisis has attracted more and more attention. However, the existing researches only considered the impact of the market indicators and the micro investor sentiment on stock market, while ignored the impact of the macro one. Therefore, in this paper, we develop an early warning system for predicting stock market crisis via market indicators and mixed frequency investor sentiments. The proposed early warning system consists of five components, which includes the construction of mixed frequency investor sentiments that consider both macro and micro investor sentiments, the identification of stock market crisis, the determination of the forecast horizon using Ensemble Empirical Mode Decomposition (EEMD), the definition of the early warning signal, and the building of prediction model using artificial neural network (ANN). Lastly, we apply the developed warning system to China's stock markets. Experimental results show that mixed frequency investor sentiments can improve the early warning ability in predicting the stock market crisis, and the ANN model has better performance than other methods including Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), K-Nearest Neighbor (KNN), and Logistic Regression (LR). • Combine investor sentiment to predict stock market crisis. • Construct the mixed frequency investor sentiments. • Extensive experimental results verify the effectiveness of constructed sentiments. [ABSTRACT FROM AUTHOR]

We study the cross-sectional effects of investor sentiment on stock price crash risk from the perspective of investor behavioural biases. We develop a firm-specific investor sentiment measure, and find that stocks with stronger investor sentiment are more prone to a future price crash. The positive relation is more pronounced for stocks eligible for margin trading, as higher investor sentiment induces greater margin buy/cover by optimistic investors. Short interest moderates the impact of optimistic sentiment on crash risk. The positive relation is also particularly prominent for stocks with a more speculative appeal, especially for those with lower institutional ownership. [ABSTRACT FROM AUTHOR]

Applying the market tail risk measure proposed by Kelly and Jiang in the China's A‐shares market, we find that the monthly market tail risk significantly and negatively predicts the monthly industrial output growth rate up to 1 year. In addition, from July 2007 to June 2019, we find that stocks with a higher tail risk outperform stocks with a lower tail risk by 0.62% (0.30% after risk adjustment) per month. Using the institutional holding weight within an industry and correlations in return on assets as proxies for the connectedness among stocks associated with firm fundamentals, and treating the sentiment risk and correlations in the three factor risk‐adjusted residuals as proxies for the connectedness among stocks associated with investor sentiment, we further show that the connectedness among stocks significantly affects individual stocks' tail risk and tail risk premium. Moreover, our findings show that the connectedness components of tail risk associated both with firm fundamentals and with investor sentiment can significantly and positively predict stock returns. Our finding suggests that the connectedness among stocks provides an important channel through which firm fundamentals and investor sentiment influence the tail risk premium in the China's A‐shares market. [ABSTRACT FROM AUTHOR]

Abstract: Using the Chinese stock market data as sample, this paper investigates the impact of investor sentiment on the assets valuation. In order to classify stocks objectively, our sample stocks are sorted by double indicators (B/M and PE). In the portfolio, we find stocks with low B/M and high PE are sensitive to investor sentiment, which are considered to be costly to arbitrage. Investor sentiment has incremental power to explain stock return co-movements, which indicates that these stocks would perform higher (lower) excess returns when investors are bullish (bearish).Our findings support a role for investor sentiment in the formation of return and the change of investor sentiment should be taken as an important systemic risk in asset pricing and portfolio management. [Copyright &y& Elsevier]

In a DID model, this study examines the impact of the coronavirus disease 2019 (COVID-19) pandemic on the investor sentiment in the financial market of China using monthly panel data on newly listed Chinese companies between October 2019 and June 2020. The outbreak of the pandemic is shown to exert a significant negative impact on investor sentiment. A future industry heterogeneity analysis shows that the pandemic has driven up investor sentiment in the pharmaceutical sector while having a significantly negative impact on non-pharmaceutical sectors. The pandemic is shown to have a negative impact on the private sector and foreign-invested sector in China while a significantly positive impact on the state-owned sector. This study contributes to the existing literature on the investigation of how significant the impact of public health emergencies on investor sentiment is. [ABSTRACT FROM AUTHOR]

Using the Chinese equity market as the testing venue, this study explores how investor sentiment affects the immediate reaction of stock prices to earnings news in high‐ and low‐sentiment periods. Our key finding is that the sentiment‐driven pricing of earnings will differ between the two periods. Specifically, during high‐sentiment (low‐sentiment) periods, the stock price sensitivity to good (bad) earnings news increases (decreases) with investor sentiment, whereas the stock price sensitivity to bad (good) earnings news is unrelated to investor sentiment. Additionally, we find that the effect of sentiment is more pronounced for young, high volatility, growth and distressed stocks. However, contrary to the U.S. evidence, our results show that small stocks are not always more exposed to sentiment. Further analysis of the role of short‐sales constraints in the sensitivity of stock prices to bad earnings news implies that short sales can enhance informational efficiency. [ABSTRACT FROM AUTHOR]

As the Chinese financial market has recently opened to the world, the high initial public offering (IPO) underpricing rate in the stock market has generated significant concern. This study investigates the impact of investor sentiment and issuing cost on the IPO underpricing rate after listing in various periods. We use the Shanghai Stock Exchange (SSE) A-shares data from 2014 to 2018 and the ordinary least squares (OLS) method to conduct the analysis. The results indicate that, in the first phases, investor sentiment is positively correlated, while the issuance cost is negatively correlated to the IPO underpricing rate. After the company's listing, investor sentiment gradually becomes the main factor affecting the IPO underpricing rate, and its positive impact increases, while the negative impact of the issuance cost weakens slightly. [ABSTRACT FROM AUTHOR]

We take a fresh look at the interaction between crude oil prices and investor sentiment from the novel perspective of both the time and the frequency domains. By using principal component analysis, we first construct an investor sentiment indicator. Then, crude oil prices are decomposed into three oil price shocks through an SVAR model. Lastly, the dynamic relationship between investor sentiment and oil price shocks is comprehensively studied from both the time and the frequency domains via wavelet coherence analysis. Our results show the leading position of crude oil prices in the co-movement relationship with investor sentiment. Further, we distinguish the different effects of oil price shocks on investor sentiment at different times and frequencies. We also find that the patterns of the co-movement between oil prices (oil price shocks) and investor sentiment change not only with time but also with frequency. [ABSTRACT FROM AUTHOR]

Existing theoretical investment literature shows that Tobin's q is a crucial factor of investment, while empirical studies find that cash flow exhibits a more significant effect on investment compared with Tobin's q. Using up-to-date empirical data, we distill innovative investment from total investment to investigate this issue using a panel of 335 innovative companies in China. We unveil that innovative investment is more sensitive to growth opportunity (q) than cash flow. Furthermore, we discover that high investor sentiment can facilitate financing activities of privately owned enterprises, which may impel their innovative investments. On the other hand, state-owned enterprises will raise their tangible investments rather than innovative investment during periods of economic expansion. Lastly, we reveal that external financing cost is the channel in the external financing environment that could affect corporate innovative investment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Measuring investor sentiment has become one of the most widely examined areas in behavioral finance. For the purpose of measuring investor sentiment more accurately, we classify the investor sentiment proxy into six market dimensions for the first time, and construct the investor sentiment monitoring index system. By using PCA method and excluding macroeconomic factors, we construct comprehensive investor sentiment index in Chinese stock market. Our results show this index as a good prediction ability to stock market. [ABSTRACT FROM AUTHOR]

Using China's stock market as the testing venue, this study examines how corporate transparency helps explain the sensitivity of stock prices to general investor sentiment. We find that firms with low corporate transparency, measured by a battery of proxies including state ownership, the prevalence of related party transactions, accrual-based earnings management, audit opinions, and the quality of audit firms, are more affected by investor sentiment than are firms with high corporate transparency. Overall, our findings highlight the importance of corporate transparency in mitigating the effects of investor sentiment on stock prices. [ABSTRACT FROM AUTHOR]

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium. [ABSTRACT FROM PUBLISHER]

This article focuses on investor sentiment and its relationships to stock returns and volatility in the Chinese stock market. By using mutual fund flows as a substitute for investor sentiment for different stocks, this study finds that investor sentiment has a tremendous impact on stock returns in the Chinese stock market. However, some of our results are inconsistent with previous research. Since the Chinese stock market is still an emerging capital market, one explanation for the inconsistency is that investor sentiment has comparatively stronger impact on stock returns in China. [ABSTRACT FROM AUTHOR]