Sentimental showdown: News media vs. social media in stock markets

Motivated by the growing convergence between news media and social media as dominant sources of information dissemination, this study examines the connection between textual sentiment and stock returns. Previous studies have examined the effect of sentiment extracted from these two sources on stock returns independently, without modelling how one source can confound the relationship between stock returns and the other source. We investigate this using data from four markets (USA, UK, South Africa and Brazil) and a sample period stretching from January 2016 to April 2023. Employing a suite of methods that encompass both simple parametric techniques and complex models designed to address nonlinearity, chaos and deviations from normality, the analysis uncovers a pronounced impact of social media sentiment on stock returns in the United States. This influence overshadows the effect of news media sentiment across the employed methods. Interestingly, in other markets, news media exhibits a greater effect on stock returns compared to social media sentiment. By emphasising the convergence of news media and social media, the study highlights the important interplay between these sources, offering valuable insights into understanding the complex dynamics of modern financial markets.

Does COVID-19-specific news affect stock market liquidity? Evidence from Japan

This article examines the effect of COVID-19-specific news on stock market liquidity in the Japanese Topix 500-listed firms. Our empirical analyses show that both COVID-19 confirmed cases and COVID-19-specific news induce a negative effect on stock market liquidity. These findings suggest that the effect of COVID-19-specific news on U.S. stock market liquidity [1] is robustly confirmed in Japanese firms. This study also presents recommendations derived from Narayan et al. [2], who constructed a COVID-19-specific news index using data from popular newspapers worldwide. In sum, this study presents the following:•Stock market liquidity is negatively affected by confirmed cases of COVID-19 in Japan.•The impact of COVID-19-specific news on stock market liquidity was analyzed using the OLS regression method.

Do climate policy uncertainty and investor sentiment drive the dynamic spillovers among green finance markets?

Green finance is an essential instrument for improving the environment and addressing climate change. This study investigates the dynamic spillovers among green finance markets using time-varying parameter vector autoregression (TVP-VAR) spillover indices, and further investigates the impact of climate policy uncertainty and investor sentiment on spillovers based on the generalised autoregressive conditional heteroscedasticity mixed data sampling (GARCH-MIDAS) model. The results indicate that: (i) environmental, social and governance (ESG), clean energy and water markets are information transmitters in the green finance system, whereas green building, green transportation, green bond and carbon markets are mainly information receivers; (ii) green stock markets including clean energy, non-energy and ESG markets transmit and receive greater information in the green finance system, while green bond and carbon markets do less; (iii) the green bond market is more interconnected with other green finance markets after the COVID-19 outbreak; (iv) investor sentiment contributes more to the net total directional spillovers of green resource markets (water and clean energy), while climate policy uncertainty contributes more to total spillovers and the net total directional spillovers of other green finance markets. These findings offer invaluable guidance for both policymakers and environmental investors.

Impact of COVID-19 on investor sentiment in China's stock markets

Large-scale public health emergencies may exert significant adverse effects on market sentiment. This study utilizes interrupted time series analysis (ITSA) to explore the shift in Chinese investors' sentiment in response to the uncertainties due to the outbreak of the COVID-19 pandemic. The empirical findings demonstrate that COVID-19 had a notable impact on investor sentiment within China's stock markets. Before the outbreak of COVID-19, investor sentiment had been on an upward trend. However, since the onset of the pandemic, there has been a sustained decline in investor sentiment, aligning with the downward trend observed in China's stock markets. Interestingly, the immediate effect of the COVID-19 intervention was positive, briefly boosting investor sentiment. As of 2023, with the conclusion of the pandemic and the Chinese government's decision to end the zero COVID-19 policy, we anticipate resurgence in investor sentiment within China's stock markets.

How media coverage news and global uncertainties drive forecast of cryptocurrencies returns?

This paper aims to investigate the impact of global financial, economic, and gold price uncertainty indices (VIX, EPU, and GVZ) and investor sentiment based on media coverage news on the returns of Bitcoin and Ethereum during the COVID-19 pandemic. We adopt an asymmetric framework based on the Quantile-on-Quantile approach, which examines the quantiles of the cryptocurrency returns, investor sentiment, and the various uncertainties indicators. The empirical findings suggest that the COVID-19 pandemic has significantly impacted cryptocurrency returns. Specifically, (i) the results demonstrate the predictive power of Economic Policy Uncertainty (EPU) during this period, as evidenced by a strong negative association between EPU and cryptocurrency returns across all quantiles; (ii) the correlation between cryptocurrency returns and the VIX index was negative but weak, across various quantile combinations of Ethereum and Bitcoin returns; (iii) an increase in COVID-19 news negatively affected Bitcoin returns across all quantiles; (iv) Bitcoin and Ethereum cannot be relied upon as effective hedging tools against global financial and economic uncertainty during the COVID-19 pandemic. Studying the behavior of cryptocurrency during uncertainty like pandemics is extremely important because it provides investors with insights on diversifying their portfolios and hedging their risks.

Social informedness and investor sentiment in the GameStop short squeeze

We examine investor behavior on social media platforms related to the GameStop (GME) short squeeze in early 2021. Individual investors stimulated the stock market via Reddit social posts in the presence of institutional investors who bet against GME's success as short sellers. We analyzed r/WallStreetBets subreddit posts related to GME's trading patterns. We performed text-based sentiment analysis and compared the social informedness of posting users for GME trading on two social media platforms. The short squeeze occurred due to coordinated trading by individual investors, who discussed trading strategies on the platforms and drove collective social informedness-based trading behavior. Our findings suggest that the valence and number of submissions influenced GME's intraday transaction volumes and precursors for irrational trading behavior patterns to have emerged. We provide a theoretical interpretation of what occurred and call for tighter monitoring of social news platforms. We also encourage effort to create an in-depth understanding of the observed patterns and the linkages between them and the larger equity markets.

Carbon disclosure and stock price synchronization: from the perspective of analyst tracking

Under the background of peaking carbon neutralization, it is a significant and fresh proposition to investigate the economic benefits of carbon disclosure (CD) in the Chinese market. By taking all listed enterprises as a sample (2009-2020), this paper firstly empirically analyzes the impact of enterprise CD on stock price synchronization and the indispensable role played by analysts in between. The results indicate that (1) enterprise CD is conducive to reduce stock price synchronization, confirming the accuracy of government mandatory CD system and the effectiveness of voluntary enterprise CD project. (2) Analysts play the role of "information scouts" and have a mediating effect between enterprise CD and stock price synchronization. (3) Analysts play the role of "analysis commentators," and analyst rating has a moderating effect between enterprise CD and stock price synchronization. (4) In further analysis, analysts will mobilize investors' positive investment sentiment, but only when the analyst rating upgrades or remains unchanged.

The impact of investor sentiment on firms' green total factor productivity-facilitator or inhibitor?

Investor sentiment does not only have negative impacts. It may also improve green total factor productivity by invigorating funds. This research constructs a new indicator at the firm level to measure the green total factor productivity of firms. We research the effect of investor sentiment on firms' green total factor productivity using a sample of Chinese heavy polluters listed on Shanghai and Shenzhen A-shares between 2015 and 2019. Through a series of tests, the mediating role of agency costs and financial situations is confirmed. It is discovered that the digitization of businesses facilitates the effect of investor sentiment on the green total factor productivity of businesses. And when managerial competence reaches a certain threshold, the impact of investor sentiment on green total factor productivity is amplified. Tests for heterogeneity reveal that high investor sentiment has a larger impact on green total factor productivity in firms with superior supervision.

Forward looking statement, investor sentiment and stock liquidity

Information is a critical element of capital markets, and liquidity is the lifeblood of capital markets. Relative to historical information, forward-looking information is of significant value to investors. Based on textual analysis calculations, we selected Chinese A-share listed companies as a research sample to explore the impact of forward-looking information disclosure level on stock liquidity. It is found that the higher the level of forward-looking information disclosure, the better the stock liquidity. Investor sentiment is the transmission mechanism through which the forward looking statement disclosure level affects stock liquidity. The heterogeneity analysis shows that the level of forward-Looking statement disclosure has a more significant effect on stock liquidity improvement for state-owned enterprises and enterprises in low-market regions than those in regions with high marketization levels. The article expands and enriches the research on forward-looking information disclosure, and also has some reference value for regulators to formulate laws and regulations and regulate forward-looking information disclosure.

The weekly cycle of investor sentiment and the holiday effect-- An empirical study of Chinese stock market based on natural language processing

Investor sentiment is an important factor that affects stock prices, stock market returns, and asset pricing. However, the fluctuation patterns and factors influencing investor sentiment have received less attention from scholars. This study uses text messages from stock investors' social networks and natural language processing techniques to reveal sentiment fluctuation laws of stock market investors. An investor confidence index (ICI) is constructed by quantifying sentiment in investor messages on social networks. By taking this index as a proxy for sentiment, we measure the candidate fluctuation periods of investor sentiment using a Fourier transform. The significance test then determines the significant cycle of investor sentiment within seven days. Based on this, cluster analysis further reveals that investor sentiment in the 7-day cycle has a 5 + 2 cycle of variability. That is, from Monday to Friday, investor sentiment is disturbed by stock market sentiment showing profit-seeking and risk-averse preferences, while during the weekend holiday, stock market disturbance to investor sentiment becomes lower, investor sentiment is substantially higher, and volatility is narrowed, showing a typical holiday effect. The analysis also shows that the recurring cycle of 5-day trading days and 2-day holidays is a direct exogenous factor contributing to the 7-day cycle of investor sentiment. This study provides a new perspective for studying "investor sentiment," "day of the week effect," and "behavioral finance."

In search of COVID-19 and stock market behavior

The aim of this paper is two-fold. First, we investigate the nexus between investor attention to COVID-19 and daily returns in 59 countries. We use Google Search Volume Index to account for investor attention. Our empirical findings suggest that the search volume of the pandemic is negatively associated with daily returns. The effect was strong in the week that the World Health Organization declared it as pandemic and among advanced countries. Second, we explore the relationship between search volume and market volatility. The findings suggest that COVID-19 sentiment generated excess volatility in the market. Our findings remain robust with alternative specifications.

COVID-19 pandemic and capital markets: the role of government responses

This paper analyzes the moderation effect of government responses on the impact of the COVID-19 pandemic, proxied by the daily growth in COVID-19 cases and deaths, on the capital market, i.e., the S&P 500 firm's daily returns. Using the Oxford COVID-19 Government Response Tracker, we monitor 16 daily indicators for government actions across the fields of containment and closure, economic support, and health for 180 countries in the period from January 1, 2020 to March 15, 2021. We find that government responses mitigate the negative stock market impact and that investors' sentiment is sensitive to a firm's country-specific revenue exposure to COVID-19. Our findings indicate that the mitigation effect is stronger for firms that are highly exposed to COVID-19 on the sales side. In more detail, containment and closure policies and economic support mitigate negative stock market impacts, while health system policies support further declines. For firms with high revenue exposure to COVID-19, the mitigation effect is stronger for government economic support and health system initiatives. Containment and closure policies do not mitigate stock price declines due to growing COVID-19 case numbers. Our results hold even after estimating the spread of the pandemic with an epidemiological standard model, namely, the susceptible-infectious-recovered model.

Investor sentiments and stock markets during the COVID-19 pandemic

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions. We proxy for negative and positive investor sentiments using the Google Search Volume Index for terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significant relationships between positive and negative investor sentiments and stock market returns and volatility. Specifically, an increase in positive investor sentiment leads to an increase in stock returns while negative investor sentiment decreases stock returns at lower quantiles. The effect of investor sentiment on volatility is consistent across the distribution: negative sentiment increases volatility, whereas positive sentiment reduces volatility. These results are robust as they are corroborated by Granger causality tests and a PVAR model. The findings may have portfolio implications as they indicate that proxies for positive and negative investor sentiments seem to be good predictors of stock returns and volatility during the pandemic.

Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets

This paper first investigates the relationship between investor sentiment, captured by internet search behaviour, and the unexpected component of stock market volatility during the COVID-19 pandemic. According to data on 12 major stock markets, our research indicates a positive correlation between the Google search volume index on COVID-19 and the unexpected volatility of stock markets. The result suggests that greater COVID-19-related investor sentiment during this pandemic is associated with higher stock market uncertainty. Our study further examines whether country-level governance plays a role in protecting stock markets during this pandemic and reveals that the unexpected conditional volatility is lower when a country's governance is more effective. The impact of investor sentiment and country governance on unexpected volatility after the initial shock of COVID-19 is also investigated. The findings demonstrate the importance of establishing good country-level governance that can effectively reduce stock market uncertainty in the context of this pandemic, and support continual policy development related to investor protection.

Cryptocurrency price discrepancies under uncertainty: Evidence from COVID-19 and lockdown nexus

The past decades have witnessed recurrent price discrepancies in cryptocurrency markets across countries. In addition to prior explanations that generally attribute this phenomenon to domestic capital controls during normal periods, we provide another explanation that investors perceive cryptocurrency as an alternative (hedging) investment, especially under uncertainty. Using the emerging of the COVID-19 pandemic in 2020 and the subsequent lockdown policies implemented by a group of countries as natural experiments, we adopt a difference-in-difference framework to examine how the nexus affects Bitcoin price discrepancies. We find that price discrepancies are larger in countries with confirmed cases of COVID-19 and rigorously implementing lockdown policies. We then verify our "alternative investment" hypothesis on the mechanism by showing that countries with intensified exposure to media hype on COVID-19 topics and with more panic emotion among citizens during the pandemic generally experienced larger Bitcoin price discrepancies than their counterparts. We also find that domestic capital control, sanitary policy stringency, uncertainty aversion, individualistic culture, and governmental power could moderate the general effect.

Economic policy uncertainty, investor sentiment and financial stability-an empirical study based on the time varying parameter-vector autoregression model

This paper applies the time varying parameter-vector autoregression model to explore the dynamic relationship between economic policy uncertainty, investor sentiment and financial stability in China in different periods and at different time points. The empirical results show that economic policy uncertainty has an obvious negative impact on investor sentiment before 2012 and financial stability in the short term, and the influence of economic policy uncertainty on investor sentiment is greater than that of economic policy uncertainty on financial stability. These influences were more significant during the period of the global financial crisis in 2008. Moreover, investor sentiment had a positive and gradually increasing effect on financial stability, while after 2010, the positive impact gradually weakened. Furthermore, economic policy uncertainty is negatively affected by financial stability, and the effect of financial stability on investor sentiment is positive. In terms of mediating effects, economic policy uncertainty has an indirect impact on financial stability through investor sentiment and vice versa. This paper provides a new solution to economic problems explored in behavioral finance research. Additionally, Chinese government agencies can achieve the goal of preventing financial crises and maintaining financial stability by monitoring investor sentiment and implementing targeted economic policies.

How to gauge investor behavior? A comparison of online investor sentiment measures

Given the increasing interest in and the growing number of publicly available methods to estimate investor sentiment from social media platforms, researchers and practitioners alike are facing one crucial question - which is best to gauge investor sentiment? We compare the performance of daily investor sentiment measures estimated from Twitter and StockTwits short messages by publicly available dictionary and machine learning based methods for a large sample of stocks. To determine their relevance for financial applications, these investor sentiment measures are compared by their effects on the cross-section of stocks (i) within a Fama and MacBeth (J Polit Econ 81:607-636, 1973) regression framework applied to a measure of retail investors' order imbalances and (ii) by their ability to forecast abnormal returns in a model-free portfolio sorting exercise. Interestingly, we find that investor sentiment measures based on finance-specific dictionaries do not only have a greater impact on retail investors' order imbalances than measures based on machine learning approaches, but also perform very well compared to the latter in our asset pricing application.

The impact of COVID-19 on the stock market crash risk in China

This study investigates the impact of the COVID-19 pandemic on the stock market crash risk in China. For this purpose, we first estimated the conditional skewness of the return distribution from a GARCH with skewness (GARCH-S) model as the proxy for the equity market crash risk of the Shanghai Stock Exchange. We then constructed a fear index for COVID-19 using data from the Baidu Index. Based on the findings, conditional skewness reacts negatively to daily growth in total confirmed cases, indicating that the pandemic increases stock market crash risk. Moreover, the fear sentiment exacerbates such risk, especially with regard to the impact of COVID-19. In other words, when the fear sentiment is high, the stock market crash risk is more strongly affected by the pandemic. Our evidence is robust for the number of daily deaths and global cases.

Stock price reaction to appointment of a chief health officer during COVID-19

This study examines how appointing a chief health officer (CHO) at the corporate-board level during the COVID-19 outbreak affects the stock returns of US firms. As the COVID-19 progressed, the negative abnormal return (CAR) is -7.5%. In contrast, shares of firms that had appointed a CHO before or during the window surrounding the date of the first reported COVID-19 case (the WHO declaration) exhibited positive CAR of ＋6.29% (＋0.136%). CARs surrounding the exact CHO appointment date once the COVID-19 had already broken out the effect was even stronger, ＋6.91%. Size, leverage, growth, and R&D intensity influence significantly returns during the outbreak.

Feverish sentiment and global equity markets during the COVID-19 pandemic

This paper proposes a new approach to estimating investor sentiments and their implications for the global financial markets. Contextualising the COVID-19 pandemic, we draw on the six behavioural indicators (media coverage, fake news, panic, sentiment, media hype and infodemic) of the 17 largest economies and data from 1 st January 2020 to 3 rd February 2021. Our key findings, obtained using a time-varying parameter-vector auto-regression (TVP-VAR) model, indicate the total and net connectedness for the new index, entitled 'feverish sentiment'. This index provides us insight into economies that send or receive the sentiment shocks. The construction of the network structures indicates that the United Kingdom, China, the United States and Germany became the epicentres of the sentimental shocks that were transmitted to other economies. Furthermore, we also explore the predictive power of the newly constructed index on stock returns and volatility. It turns out that investor sentiment positively (negatively) predicts the stock volatility (return) at the onset of COVID-19. This is the first study of its kind to assess international feverish sentiments by proposing a novel approach and its impacts on the equity market. Based on empirical findings, the study also offers some policy directions to mitigate the fear and panic during the pandemic.

Immune or at-risk? Stock markets and the significance of the COVID-19 pandemic

The closure of borders and traditional commerce due to the COVID-19 pandemic is expected to have a lasting financial impact. We determine whether the growth in COVID-19 affected index prices by examining equity markets in five regional epicentres, along with a 'global' index. We also investigate the impact of COVID-19 after controlling for investor sentiment, credit risk, liquidity risk, safe-haven asset demand and the price of oil. Despite controlling for these traditional market drivers, the daily totals of COVID-19 cases nevertheless explained index price changes in Spain, Italy, the United Kingdom and the United States. Similar results were not observed in China, the origin of the virus, nor in the 'global' index (MSCI World). Our results suggest that early interventions (China) and the spatiotemporal nature of pandemic epicentres (World) should be considered by governments, regulators and relevant stakeholders in the event of future COVID-19 'waves' or further extreme societal disruptions.

Light a lamp and look at the stock market

In this study, we investigate the impact of the light-a-lamp event that occurred in India during the COVID-19 lockdown. This event happened across the country, and millions of people participated in it. We link this event to the stock market through investor sentiment and misattribution bias. We find a 9% hike in the market return on the post-event day. The effect is heterogeneous in terms of beta, downside risk, volatility, and financial distress. We also find an increase (decrease) in long-term bond yields (price), which together suggests that market participants demanded risky assets in the post-event day.

What investors say is what the market says: measuring China's real investor sentiment

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.

The impact of COVID-19 on the Chinese stock market: Sentimental or substantial?

We investigate the impact of COVID-19 on Chinese stock market by an event study and examine the effect of individual investor sentiment on returns. The pandemic has an overall negative effect on stock market during the post-event window, which can't be explained by real losses. Results show a stronger positive correlation between individual investor sentiment and stock returns than usual. The impact on individual investor sentiment on stock returns is more significant for enterprises with high PB, PE and CMV, low net asset, and low institutional shareholding. Only 7 industries related to pharmacy, digitalization, and agriculture are boosted.

Can the Chinese volatility index reflect investor sentiment?

The volatility index is the implied volatility calculated inversely from the option prices. This study investigates whether the official Chinese volatility index, iVX, can represent investor sentiment. In order to describe investor sentiment comprehensively, we build a three-dimensional investor sentiment measurement system composed of macro, meso and micro level, and decompose iVX into three components to obtain short-term, medium-term fluctuations and long-term trend by EEMD method. The relationships between iVX, its components and sentiment indexes at each level have been analyzed separately, and the empirical results reveal all components of iVX can reflect the investor sentiment at the corresponding level but to which extent they can reflect are not the same. Further we introduce the mixed-frequency dynamic factor analysis to extract the common sentiment factor, which shows stronger correlation with contemporaneous iVX, compared with the sentiment indexes at each level. The ADL model in robustness check also demonstrates the results. Our findings confirm iVX can represent the common sentiment and expectations of Chinese investors in different time scales.

Stock prices and geographic proximity of information: Evidence from the Ebola outbreak

Behavioral finance studies reveal that investor sentiment affects investment decisions and may therefore affect stock pricing. This paper examines whether the geographic proximity of information disseminated by the 2014-2016 Ebola outbreak events combined with intense media coverage affected stock prices in the U.S. We find that the Ebola outbreak event effect is the strongest for the stocks of companies with exposure of their operations to the West African countries (WAC) and the U.S. and for the events located in the WAC and the U.S. This result suggests that the information about Ebola outbreak events is more relevant for companies that are geographically closer to both the birthplace of the Ebola outbreak events and the financial markets. The results also show that the effect is more pronounced for small and more volatile stocks, stocks of specific industry, and for the stocks exposed to the intense media coverage. The event effect is also followed by the elevated perceived risk; that is, the implied volatility increases after the Ebola outbreak events.