Impact Of Sentiment Research Articles

The causal relationship between social media sentiment and stock return: Experimental evidence from an online message forum

This paper examines the impact of sentiment in an online message forum on stock returns. Using a novel controlled experiment, we collect a large panel of messages with no fundamental information but strong sentiment and stock return data. We find a significant causal effect of social media sentiment on the same-day stock returns. The sentiment has no significant effects on stock returns on subsequent days. This effect is mainly driven by messages with positive sentiment, which has a strong positive impact on stock returns. Our results establish a causal relationship between social media sentiment and stock returns and highlight the risk of market manipulation via social media.

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.

Investor Sentiment and Paradigm Shifts in Equity Return Forecasting

This study investigates the impact of investor sentiment on excess equity return forecasting. A high (low) investor sentiment may weaken the connection between fundamental economic (behavioral-based nonfundamental) predictors and market returns. We find that although fundamental variables can be strong predictors when sentiment is low, they tend to lose their predictive power when investor sentiment is high. Nonfundamental predictors perform well during high-sentiment periods while their predictive ability deteriorates when investor sentiment is low. These paradigm shifts in equity return forecasting provide a key to understanding and resolving the lack of predictive power for both fundamental and nonfundamental variables debated in recent studies. This paper was accepted by David Simchi-Levi, finance.

Overreaction, Investor Sentiment and Market Sentiment of COVID-19

This study examines the impact of investor sentiment and market sentiment on overreaction in Europe and USA markets before and during COVID-19. The investor sentiment is calculated by the standard deviation, realized volatility, Parkinson’s estimator and Garman and Klass’s estimator. The market sentiment is measured by Business Confidence Index, Consumer Confidence Index, Labour Force Survey, Leading Index and Monetary Aggregates. The results of this study show that investor and market sentiments are correlated to stock return before COVID-19. Nonetheless, realized volatility is the only investor sentiment that is significant with the emergence of COVID-19. It shows that investors rely on the previous day’s stock prices to trade under market uncertainty. Market sentiment is observed to be insignificant in the pandemic. Furthermore, the existence of overreaction is detected in European portfolios but no evidence of overreaction is shown in the USA during pre-COVID-19. Surprisingly, overreaction is observed in Europe and USA markets in the pandemic. The USA market has a higher overreaction tendency than Europe. The results of this study assist academicians, practitioners and investors in understanding and creating awareness of the existence of market overreaction and its determinants before and during COVID-19.

U.S. banks’ lending, financial stability, and text-based sentiment analysis

We examine the impact of investor sentiment on bank credit and financial stability. We also investigate how loan growth may affect bank stability. We use a large panel data set of U.S. commercial banks over the period 1999Q1–2015Q4, using bank-level data. Investor sentiment is proxied by two novel but alternative measures based on textual analysis. First, we employ the sentiment measure constructed by García (2013) based on the fraction of positive and negative words in two columns of financial news from the New York Times. Second, we employ the text-based measure of uncertainty constructed by Manela and Moreira (2017) called News Implied Volatility, which uses front-page articles of the Wall Street Journal. The results show that banks’ lending falls when investor sentiment is low, while this effect is more pronounced when banks hold a higher level of credit risk. These effects are more pronounced during recessions with loan growth also responding negatively to the anxiety of investors throughout recessions. Finally, we show that the Great Financial Crisis had a negative effect on investor sentiment leading to a decline in U.S. lending behavior and an increase in the U.S. banking sector instability.

Are You What You Tweet? The Impact of Sentiment on Digital News Consumption and Social Media Sharing

This study examines the impact of news content sentiment on digital news readership and social media sharing. Using econometric analyses and models estimated with rich clickstream data on online news readership and social media sharing data collected from Twitter, we find a differential effect of sentiment on news readership and sharing behaviors. Specifically, individuals are likely to read news articles with negative headline sentiment on the news website but tend to share articles with positive article sentiment on Twitter. Upon decomposition of news article sentiment, we find a contrasting positive author sentiment effect and a negative news topic valence effect on news readership. Interestingly, we uncover that an increase in a Twitter user’s followers leads to an increase in the Twitter user’s propensity to share positive-sentiment news articles. Overall, our findings affirm the coopetitive but complementary relationship between news websites and social media platforms. Our results also guide publishers to better craft their news content and manage social media presence to improve audience engagement and readership outcomes while preserving the agenda-setting ability of news media. Importantly, given the dichotomy between news reading and sharing behaviors, predicting individual behaviors based on social media opinions may need to be viewed with prudence.

Walking on air or hopping mad? Understanding the impact of emotions, sentiments and reactions on ratings in online customer reviews of mobile apps

Online customer reviews (OCR) are an established source of competitive intelligence. Since OCR reflect perceptions of past users about product features and performance, prospective customers of mobile apps often resort to OCR before they decide to download an app. In addition to the textual content of the OCR, potential users of the app often consult the star ratings provided by the reviewers. In this paper, we determine if the star rating of mobile payment apps suitably captures the appropriate customer perception reflected in the textual content of the OCR for the payment apps. We conduct a three-dimensional analysis of 146,914 reviews from two popular mobile payment apps and uncover the sentiment and emotions captured in the review text, and the reactions in the emojis. Our analysis shows that the consolidated sentiment and the happiness emotion obtained from the OCR of mobile payment apps impacts the star ratings more strongly, than other emotions embedded in the text, and reactions in the emojis. The findings also hold good during the Covid-19 pandemic. We propose a novel perception score that captures the nuances in the OCR more effectively and suggest how mobile app providers can use it to arrange the OCR for better compatibility with content. The results of this research will be useful for mobile app providers that depend on OCR for popularizing their apps and will provide them a novel metric based on content, that can leverage OCR better to influence future downloads.

The conditional impact of investor sentiment in global stock markets: A two-channel examination

While investor sentiment has been shown to have a robust, direct impact on stock returns, we know little about how it impacts returns through an indirect channel from conditional volatility. We conduct a global study of investor sentiment across 40 international stock markets to examine the impact of investor sentiment on stock returns via both direct and indirect channels and how the impact varies across bull and bear market regimes. Using turnover ratio as the sentiment proxy and applying GARCH-type models, we confirm a conditional impact of investor sentiment on stock returns via both channels: In bull regimes, optimistic (pessimistic) shifts in investor sentiment would increase (decrease) stock returns, while in bear regimes, optimistic (pessimistic) shifts would decrease (increase) stock returns.

Impact of sentiment and monetary policy on Mexican tourism stock returns: the domestic and US role

PurposeThis paper focuses on the role of sentiment and monetary policy (both domestic and the United States (US)) in explaining the changes in the Mexican tourism firms' stock returns for the period 1998M03–2019M12.Design/methodology/approachThe authors conducted the ordinary least square regression estimations using various models to investigate the impact of sentiment and monetary policy changes on tourism firms' stock returns. Furthermore, to provide a robust check, the authors run all regression models based on the capital asset pricing model by regressing the excess returns of tourism firms' stocks on all independent variables.FindingsEmpirical findings reveal that the changes in Mexican consumer sentiment have a stronger positive effect on tourism firms' stock returns than Mexican business sentiment changes. However, the US consumer and business sentiment are irrelevant to tourism firms' stock returns. Moreover, this study’s results indicate that changes in the US interest rates positively influence tourism firms' stock returns. This study’s findings show that as the monetary divergence between Mexico and the US (differential real interest rates) widens, the lower is the tourism firms' stock returns.Originality/valueThis study is the first to extend the prior studies by examining the effects of sentiment and monetary policy (both domestic and US role) on Mexican tourism stock return.

Bank Stock Return Reactions to the COVID-19 Pandemic: The Role of Investor Sentiment in MENA Countries

In this study, we investigated the impact of COVID-19 investor sentiment (CS), number of cases (CC), and deaths (CD) on bank stock returns in 16 MENA countries. In addition, we examined the interaction effects of CS with CC and CD on bank stock returns. Lastly, we looked at whether Islamic banks outperformed conventional banks during the pandemic. Based on monthly data from the Middle East and North Africa (MENA) countries from February 2020 to July 2021, we used the clustered standard error fixed effect estimation on Islamic and conventional bank stock market returns. The results suggest that CC and CD have negative impacts on bank stock market returns while CS has no effect, except for the lagged value. The interaction effect of CS with CC and CD on stock returns proved to strengthen the link in the current month and weaken the link in the previous month.

Does investor sentiment affect fund crashes? Evidence from Chinese open-end funds

This paper aims to detect the impact of investor sentiment on the open-end fund crashes, drawing on the open-end stock funds and partial stock funds of China for the 2009–2019 period. The results show that the rise of investor sentiment will significantly increase the risk of the open-end fund crashes, which remains valid after robustness tests. Further researches indicate that the market timing and stock selection abilities of fund managers weaken the positive impact of investor sentiment on the open-end fund crashes, and the market illiquidity promotes the positive impact of investor sentiment on the open-end fund crashes.

Impact of Twitter sentiment on stock price returns

Impact of Twitter sentiment on stock price returns

The Impact of Market Factors and News Sentiments on Silver Futures ETFs

Abstract This study constructs a multi-factor capital asset pricing model (CAPM) to analyze systematic risk and other influential risk factors in the silver futures exchange-traded funds (silver futures ETFs) market and then provides an analysis of precious metals investments as a reference. Specifically, the volatility index (VIX) and the real estate investment trusts (REITs) are used as influences of silver futures on political and economic factors. In addition, we use text mining to capture news events on the network into a Boolean matrix, which transforms unstructured data into structured data. Further, the term frequency (TF) and inverse document frequency (IDF) algorithm are applied to calculate the most important keywords on the market and measure them in the model after a sentimental evaluation. The empirical results show that the silver futures ETFs market is indeed affected by market news, providing investors in this market with a reference. JEL classification numbers: C10, C13, G00, G10. Keywords: Silver futures ETFs, Volatility index; Real estate investment trusts, Text mining, Inverse document frequency.

Asymmetric effect of FEARS Sentiment on Stock Returns: Short-sale constraints, limits to arbitrage, and behavioural biases

ABSTRACT This paper examines the implications of short-sale constraints, limits to arbitrage, and behavioral biases on the FEARS sentiment and stock returns asymmetric relationship. Our results indicate a strong negative relationship between FEARS sentiment and stock return. Our findings show that short-sell and arbitrage constraint attenuates the potential impact of sentiment on return behavior. We find that the FEARS sentiment influences behavioral biases and the trading activity of market participants.

SPATIAL EFFECT OF MARKET SENTIMENT ON HOUSING PRICE: EVIDENCE FROM SOCIAL MEDIA DATA IN CHINA

Market sentiment has become more easily spread between cities through social media. This study investigates the spatial effect of market sentiment on housing price in a social media environment. In order to extract home-buyer sentiment from social media, we use text sentiment analysis techniques and build a novel housing market sentiment index. A spatial econometric model of housing price volatility is subsequently constructed and the housing market sentiment index is included as an independent variable in the model. Using panel data from 30 large and medium-sized cities in China for 20 quarters from 2016 to 2020, the spatial effect of market sentiment on housing price is empirically analyzed by calculating direct and indirect effects. The results show that market sentiment had a significant positive effect on housing prices in the local and neighboring cities over the research period. However, the impact of market sentiment on housing price was heterogeneous in terms of geographical region; the direct effect was stronger in the eastern region than in the central and western regions, and the indirect effect was significant only in the eastern region. These findings can provide references for government to formulate housing market regulation policies and measures based on market sentiment.

The impact of COVID-19 news and investor sentiment in European stock pricing, a regional, country, and economic sector review

In the present paper we extended the Fama-French (FF), three-factor model, by including the U.S. VIX and European VSTOXX implied volatility indexes. Also, the Baker, Bloom Davis, Kost, and Renault Economic policy (WEUI), pandemics (WPUI) news, and social media (TWITUI) uncertainty index were included. We did this in order to test if, the main Eastern, Northern, Southern, and Western European stock markets could be priced with behavioral biases such as investor sentiment. With a balanced panel data of 659 European companies from January 2017 to Jun 2021, we found that the WPUI could be used in a regional perspective, along with the VIX and TWITUI factors. In a country-specific perspective, only the inclusion of the TWITUI factor led to better-fitting results in Finland, Ireland, the Netherlands, Poland, Spain, and Sweden. Our results suggest that other pandemic news sentiment indexes should be developed and used in the main European stock markets and encourage the use of social media investor sentiment proxies in risk and asset-pricing multifactor models.

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

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

Symbolic Games in A Garden of Earthly Delights by Joyce Carol Oates

This article will show that postmodern thoughts play an essential role in Joyce Carol Oates’ Wonderland Quartet. In its opening novel A Garden of Earthly Delights, I will also consider the imagery of Lewis Carroll’s Alice texts that influenced Oates’ Quartet. Oates’ and Carroll’s texts share the depiction of decentralised permissiveness and rejection of all authority that I interpret through the aesthetic conception of postmodern games by Gilles Deleuze. By blurring the lines between fantasy and reality, the aspect of violence is repressed in Carroll’s texts. However, Oates aestheticises violence to maximise the diverse impact of postmodern sentiment on American cultural forms that emerged in the decades of the 1950s and 1960s. In contrast to Carroll’s Alice, who demands order to protect herself from the chaos, Clara in A Garden of Earthly Delights rejects conventions and fabricates chaos to alleviate her unprivileged condition.

Market sentiments and firm-level equity returns: panel evidence of Malaysia

This study focuses on the impact of market sentiment on firm-level equity returns in Malaysia by hypothesising that market sentiment is a relevant risk factor. Understanding how the market sentiment reflects the equity return is crucial to market participants managing their portfolio investment risks. In modelling for firm-level equity return determinants using augmented Fama and French (1992, 1996) three-factor model, this study used data from a sample of 608 publicly listed firms for 2010–2019 and the dynamic panel GMM estimation technique. The findings revealed that market sentiment indices, namely Business Conditions Index (BCI) and Consumer Sentiments Index (CSI), strongly and positively influenced firms equity returns. Excellent market sentiment encouraged a bullish strategy, increasing share prices and, consequently, stock returns. In addition to market sentiment, other related variables, namely domestic market returns, international market returns, small minus big (SMB), high minus low (HML), and firms’ liquidity ratio, are also found to be statistically significant in influencing firms equity returns. The policy implication provides a vital strategy to market participants, particularly fund managers and investors, to accordingly manage their risks and returns on their portfolio investment.

News Sentiment and the Risk of a Stock Price Crash Risk: Based on Financial Dictionary Combined BERT‐DCA

This study combines a financial knowledge dictionary and pretraining method based on BERT (Bidirectional Encoder Representation from Transformers) to construct a deep learning model for identifying stock news sentiments. The study then calculates the sentiment metrics of all stocks and analyzes the impact of news sentiment on the risk of a stock price crash and its heterogeneity. The results show that stocks with more positive sentiment metrics have a higher risk of crash in the following year. We also investigate the information intermediation and investor sentiment channels by which news sentiment affects the risk of a crash. The results show that more net insider sales, lower information transparency, and less analyst coverage amplify the impact of news sentiment on future crash risk, which is consistent with the information intermediation channel. Additionally, more retail investor positions, more active investor sentiment, and divergence between analysts’ opinions and news amplify the impact of news sentiment on the risk of a future stock price crash, which is consistent with the investor sentiment channel.