Effect Of Sentiment Research Articles

ESG경영 활동 효과가 조직 커뮤니케이션의 균형성과 기업 준법성에 대한 공중의 인식에 미치는 영향 : 반기업정서의 매개효과를 중심으로

ESG경영 활동 효과가 조직 커뮤니케이션의 균형성과 기업 준법성에 대한 공중의 인식에 미치는 영향 : 반기업정서의 매개효과를 중심으로

The effect of investor sentiment on equity market investments: Evidence from Borsa Istanbul

Bu çalışmanın amacı, 2007:01-2022:06 dönemi için yatırımcı duyarlılığının pay piyasası yatırımlarına etkisinin araştırılmasıdır. Çalışma, Borsa İstanbul Pay Piyasası’na yatırım yapan yabancı ve yerli yatırımcıların toplam portföy değerlerini kapsamaktadır. Yatırımcı duyarlılığı temsilinde çeşitli ölçütler kullanılmaktadır. Bu temsilcilerden biri olan ankete dayalı ölçütler bu çalışmanın değişkenlerini oluşturmaktadır. Dolayısıyla çalışmanın veri setini “yatırımcıların toplam portföy değerleri”, “Tüketici Güven Endeksi”, “Michigan Tüketici Güven Endeksi”, “Ekonomik Güven endeksi” ve “CBOE Volatilite Endeksi” oluşturmaktadır. Çalışmada Toda Yamamoto (1995) nedensellik testi uygulanmıştır. Çalışma sonucunda ilk olarak, ekonomik güven endeksi ile yatırımcılarının portföy değerleri arasında çift yönlü nedensellik ilişkisi tespit edilmiştir. İkinci olarak, Michigan tüketici güven endeksinden yatırımcıların portföy değerlerine doğru nedensellik ilişkisi olduğu bulgulanmıştır. Son olarak ise yatırımcıların portföy değeri ile tüketici güven endeksi arasında tek yönlü nedensellik ilişkisi olduğu saptanmıştır.

Does sentiment affect stock returns? A meta-analysis across survey-based measures

We are the first to meta-analyze the literature on the relationship between sentiment and stock returns, a topic that reacts to the history of systemic events causing asset bubbles in financial markets. We focus on three questions — whether the literature is biased; what is the “true effect” beyond this bias; and what are the key determinants of the variance among the estimates in the literature. To answer those questions we collect 1311 point estimates from 30 primary studies and use state-of-art meta-analytical approaches. Both linear and non-linear tests for publication bias suggest that the “true effect” of an improvement in sentiment is non-negligible and negative. In the majority of specifications, researchers tend to report this effect as being much stronger than it actually is. Next, using Bayesian model averaging we show that the effect of sentiment on future returns is significantly stronger for individual investors than for large institutions, and in US stock markets compared with European ones. The effect also depends on several data and model characteristics.

The Impact of Investor Sentiment on Housing Prices and the Property Stock Index Volatility in South Africa

Abstract While prior studies have examined the predictive effect of macroeconomic and country risk components on property stock index dynamics, limited explanations exist in the literature regarding the time-varying effect of investor sentiment on housing prices. Accordingly, this study assesses the impact of investor sentiment on housing properties’ returns and the effect of investor sentiment on the conditional volatility of housing price indices under different market conditions, using GARCH, GJR-GARCH, E-GARCH and Markov-switching VAR models. We found investor sentiment to significantly impact the risk premium of the property returns, where property returns increased with positive changes in investor sentiment, and conditional volatility of property returns decreased with the same changes in investor sentiment. Investor sentiment exerts positive predictive influences on the prices of small and medium houses, in both bullish and bearish market conditions but does not affect the large housing market segment. This makes the implementation of risk-related diversification across small and medium real estate portfolios more effective than large real estate portfolios. Our findings show that investor sentiment is a plausible driver of mass investor redemption actions under conditions of uncertainty.

SUSTAINABLE DEVELOPMENT GOALS, HERDING, AND RISK-AVERSE BEHAVIOUR IN MUSLIM COUNTRIES

This study examines the impact of Sustainable Development Goals (SDGs) on behavioural biases, namely herding and risk-averse behaviours, in Sharia-compliant stocks. It also explores the mediating effect of investors' sentiments on the relationship between SDGs and behavioural biases. Adopting panel data and quantile regressions, we find that that SDGs 4, 8, 10, 11, and 13 significantly and positively correlate with stock returns in Indonesia, Kuwait, Oman, and Qatar. However, SDG 7 is the only SDG goal that is significant to Saudi and UAE stock returns. The results imply a complete mediation as the SDGs have caused changes in investors' sentiment and subsequently triggered the investors to herd and become risk-averse. The impact of SDGs is more pronounced in the upper and lower quantiles of Indonesia, Saudi, and UAE stock returns, as well as the median quantile of Bahrain, Kuwait, Oman, and Qatar stock returns. The results of this study can benefit policymakers, regulators, and practitioners in identifying the best SDG practices to assist Sharia-compliant stocks in Indonesia and Gulf Cooperation Council (GCC) countries to attain better stock returns and improve investors' sentiments and behaviours. The results can also assist governments in weighing the impact and benefits of adopting SDGs in different Muslim countries.

Investor sentiment and stock price jumps: A network analysis based on China’s carbon–neutral sectors

In this paper, we analyze the interconnectedness between investor sentiment and stock price jumps based on the two-layer network models. We first use the Diebold and Yilmaz (DY) and Baruník and Křehlík (BK) spillover indexes to analyze the interactive effects of investor sentiment and price jumps between different industries in China's carbon–neutral sectors from the time and frequency domains. The results verify strong two-way spillover effects of investor sentiment and jump volatility among green industries. The connectedness in the short-term risk network of stock volatility is significantly higher than that of the Internet sentiment network, and the short-term risk spillover effect of the network plays a leading role in the total risk spillover. Subsequently, we further study the dynamic spillover between investor sentiment and jump volatility using the rolling time window. The dynamic network reveals significant heterogeneity in the spillover of Internet sentiment, and the interaction effect of investor sentiment and jump volatility displays time-varying characteristics. The green industrials and energy industries are systemically important sectors in the two-layer network system. The empirical results show the complex risk contagion mode in the green stock market and provide a reference for investors and market regulators on the risk management of the green stock market.

Like, Comment, and Share on TikTok: Exploring the Effect of Sentiment and Second-Person View on the User Engagement with TikTok News Videos

TikTok—the world’s most downloaded app since 2020, has become a place for more than silly dancing and lip-syncing. TikTok users are increasingly turning to TikTok for news content. Meanwhile, news publishers are embracing TikTok to reach a younger audience. We aim to examine the content strategy adopted by the most-followed news publishers on TikTok and how effective their TikTok strategy is in spurring audience engagement in terms of liking, commenting, and sharing. This study retrieved 101,292 TikTok news videos as of November 22, 2022. With the help of computer vision, natural language processing, and sentiment analysis, we found that TikTok news videos containing negative sentiment and more second-person view shots are associated with significantly higher audience engagement. In addition, this study demonstrated that the TikTok video features and engagement levels differ between the news publishers and other TikTok creators. Moderator analysis shows that both the effect of negative sentiment on engagement and the effect of the second-person view on engagement are moderated by the TikTok account type. The impact of negative sentiment and second-person view on engagement behaviors becomes smaller or even insignificant for news publisher TikTok videos. Theoretical and practical implications are discussed in this study.

Predictive effect of investor sentiment on current and future returns in emerging equity markets.

This study uses Non-linear Predictive Regression Analysis to analyze the effect of investor sentiment on the returns of the selected developing equity markets, including Brazil, South Africa, Indonesia, India, China, Russia, and Pakistan. The Principal Component Analysis is applied to construct an Investor Sentiment Index. In most selected countries, investor sentiment substantially affects contemporaneous market returns, and this effect remains persistent in the short term. However, it becomes less prominent over time. It suggests that stakeholders should give importance to the investors' sentiments while making investment decisions.

Daily online review sentiment and hotel performance

PurposeThis paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).Design/methodology/approachThe authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.FindingsDaily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.Research limitations/implicationsDaily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.Originality/valueThis study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

Effects of oil market sentiment on macroeconomic variables

This paper aims to evaluate the effects of oil price shocks on macroeconomic variables, for the economies of the United States and Brazil. We develop a variable that measures the volatility of oil prices, from a textual sentiment analysis. We evaluate oil price shocks using the Local Projection method. Our results suggest that changes in oil prices cause larger impacts on the US economy, compared to the effects on the Brazilian economy. The responses of the US and Brazilian variables were similar when using the sentiment indicator or the VIX volatility index. Finally, we find that decreasing the frequency of the variables, together with changing the method, does not change the response trajectories of the macroeconomic variables.

Smells like animal spirits: the sensitivity of corporate investment to sentiment

AbstractEconomists have long been interested in the effect of business sentiment on economic activity. Using text analysis, I construct a new company-level indicator of sentiment based on the net balance of positive and negative words in Australian company disclosures. Company-level investment is very sensitive to changes in this corporate sentiment indicator, even controlling for fundamentals, such as Tobin’s Q, as well as controlling for measures of company-level uncertainty.The high sensitivity of investment to sentiment could be due to several mechanisms. It could be because of animal spirits among managers or because of sentiment proxies for private information held by managers about company prospects. Overall, I find mixed evidence of the underlying causal mechanism. The effect of sentiment on investment is relatively persistent, which is consistent with managers having private information about company fundamentals. But the sensitivity of investment to sentiment is not any stronger at opaque companies in which managers are likely to be better informed than investors. Further, investment is sensitive to sentiment even when investors have an information advantage over managers by lagging the sentiment indicator by a year. Overall, the sensitivity of investment to sentiment appears to reflect both animal spirits and fundamentals.Corporate investment has been weak since the global financial crisis (GFC) and demand-side factors, such as lower sales growth, explain more than half of this weakness. Low sentiment and heightened uncertainty weighed on investment during the GFC but have been less important factors since then.

Do TripAdvisor Valences are Trustworthy on South Asian Destinations?

Travellers prefer to rely on peers’ recommendations and review websites to look for reliable and unbiased information. Trustworthy communicators are more influential than the untrustworthy one. Trustworthy content is need of the hour in specific to post COVID19 travel. This research is analysing what propels a traveller towards destinations and empirically verify the valences of trustworthiness on TripAdvisor reviews. Content analysis of TripAdvisor reviews (153799 numbers) on South Asian destinations are captured, modelled, and analysed using Descriptive statistics, Regression Analysis and Structural Equation Modelling. Positive reviews are more trustworthy than the negative reviews and are helpful to potential tourist who seeks ‘real’ or ‘genuine’ reviews. There is no moderating effect of negative sentiments on Trustworthiness. Our research results find that valences of TripAdvisor review are useful to potential tourists for their travel planning and actions. Practitioners should listen to TripAdvisor review valences and keep up with the value chain, make the destinations more tourist friendly and evolve new themes. Tourism ecosystem should use modicum of digital opportunities emanating from sentiments and apply appropriate strategies to develop their destinations. This way, tourists will develop brand equity. This study contributes to the growing body of literature on polarity analysis in TripAdvisor reviews and investigated the relationship between positive and negative valences with trustworthiness.

Emojis and stock returns

PurposeThe authors explore how the sentiment expressed by emojis in comments on stocks is associated with the stocks' subsequent returns.Design/methodology/approachBy applying our own analyzer, the authors find a sentiment effect of emojis on stocks returns separately to the plain text-expressed sentiment in Reddit posts about meme stocks such as Gamestop during the Covid-19 pandemic.FindingsThe authors document that a one-standard deviation change in emoji sentiment magnitude measured as the quantity of positive emoji sentiment posts over the previous hour is associated with an 0.06% (annualized: 109.2%) one-hour abnormal stock return compared to a mean of 0.03% (annualized: 54.6%). If the stock exhibits a higher intra-hour volatility, a proxy for uninformed noise trading, this relation is more pronounced and even stronger compared to stock return's relation to plain text sentiment.Research limitations/implicationsThe authors are not able to show causation that is open to future research. It also remains an open question how emojis impact market price efficiency.Practical implicationsEmojis are positively related to stock returns in addition to plain text-expressed content if they are discussed heavily by retail investors in Internet boards such as Reddit.Social implicationsShared emotions expressed by emojis might have an influence on how disconnected individuals make homogeneous decisions. This argument might explain our found relation of emojis and stock returns.Originality/valueSo, the study findings provide empirical evidence that emojis in Reddit posts convey information on future short-term stocks returns distinct from information expressed in plain text, in the case of volatile stocks, with a higher magnitude.

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.

Idiosyncratic volatility and firm-specific news: evidence from the Chinese stock market

This study investigates the effect of firm-specific news on the pricing of idiosyncratic volatility (IVOL) in China. Using a sample of non-financial A-share listed firms from January 2006 to June 2018, we find that the predictive ability of IVOL is much weaker around firm announcements compared to that without news, suggesting that the limited arbitrage cannot disentangle the IVOL puzzle completely in the emerging market. Additionally, we investigate the effect of news sentiment on the predictive ability of IVOL and find that it is much stronger following bad news compared to good news. Finally, when we include the macroeconomic variables known to predict returns to adjust the systematic risk, we obtain novel findings that the negative premium of IVOL becomes insignificant, suggesting that the negative premium is time-varying with macroeconomy.

Information Vs Investor Sentiment Effect on Stock Market Liquidity During Covid-19 Pandemic

Information Vs Investor Sentiment Effect on Stock Market Liquidity During Covid-19 Pandemic

The Effect of Investor Sentiment throughout the Distribution of Returns in the Chinese Stock Market

This paper adopts the data of xueqiu.com in the first half of 2015 from the Datago database and selects 100 A-shares stocks in CSI100. The number of followers is considered when building the bullishness index. In addition, quantile regression is used to study the contem-poraneous and predictive effects of sentiment on stock returns. The result suggests that sen-timent has negative contemporaneous effects on stock returns, while for the predictive mod-el, the effect is positive. Furthermore, the effects of sentiment are stronger in extreme cir-cumstances and more substantial at lower quantile than at higher quantile. However, the weighted bullishness index does not explain well as the original one. Overall, this paper ver-ifies the difference of effects between extreme and normal conditions, then attempts to use a new method to construct a bullishness index and offer more evidence about the relationship between social network sentiment and stock returns in the Chinese stock market.

A comparative study on effect of news sentiment on stock price prediction with deep learning architecture.

The accelerated progress in artificial intelligence encourages sophisticated deep learning methods in predicting stock prices. In the meantime, easy accessibility of the stock market in the palm of one's hand has made its behavior more fuzzy, volatile, and complex than ever. The world is looking at an accurate and reliable model that uses text and numerical data which better represents the market's highly volatile and non-linear behavior in a broader spectrum. A research gap exists in accurately predicting a target stock's closing price utilizing the combined numerical and text data. This study uses long short-term memory (LSTM) and gated recurrent unit (GRU) to predict the stock price using stock features alone and incorporating financial news data in conjunction with stock features. The comparative study carried out under identical conditions dispassionately evaluates the importance of incorporating financial news in stock price prediction. Our experiment concludes that incorporating financial news data produces better prediction accuracy than using the stock fundamental features alone. The performances of the model architecture are compared using the standard assessment metrics -Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Correlation Coefficient (R). Furthermore, statistical tests are conducted to further verify the models' robustness and reliability.

Information asymmetry, sentiment interactions, and asset price

We develop an asset pricing model with sentiment interactions between institutional and individual investors under the condition of information asymmetry. Our model considers private information and investor sentiment, two imperfections in securities markets, and integrates them into a theoretical model to investigate the role of the interaction between information asymmetry and investor sentiment in asset pricing. We show that the joint effect of private information and investor sentiment deviate the price of risky assets and efficiently explains anomalies in the stock market. Investor sentiment changes the effect of information on the equilibrium price relative to a world where all investors are completely rational. Private information changes the effect of investor sentiment on the equilibrium price in comparison with a scenario with symmetric market information. In addition, the individual investors’ learning and the disclosure of information both allow private information to be better integrated into the price and simultaneously changes the effect of investor sentiment on the equilibrium price.

How does the COVID-19 pandemic shape the relationship between Twitter sentiment and stock liquidity of US firms?

Using a new investor sentiment metric derived from Twitter, this paper examines how the pandemic's death rate influences the impact of investor sentiment on stock liquidity. Recent literature remains inconclusive regarding the effect of COVID-19 information and investor sentiment on financial markets. Using panel smooth transition regression (PSTR) for daily data on 338 listed firms in the S&P500 from January 2, 2020, to May 26, 2021, the findings reveal that the impact of Twitter sentiment on stock liquidity is nonlinear and changes over time and across firms in the function of the pandemic's death rate in the US. The results exhibit a threshold level of 4.32%, above which investor sentiment boosts stock liquidity. The speed of the transition from low to high pandemic death rate regime occurred abruptly rather than smoothly. This translates to severe changes in investor perception and demonstrates that investors are rapidly updating their beliefs during the COVID-19 outbreak.