Low Sentiment Research Articles

Sentiment and attitudes toward offsetting and the biodiversity market in online media articles.

Biodiversity offsetting, a conservation approach to offset loss of habitat and ecosystem services, has been widely accepted and implemented in different legislative frameworks around the globe. I assigned sentiment scores (from -3 [very negative] to +3 [very positive]) to online news articles to examine public sentiment toward offsetting. I identified 86 pertinent articles published from 2013 to 2023 by web scraping online media outlets through keywords. I examined article content based on topics commonly associated in scientific literature with offsetting, such as risks or financial aspects. Most articles were from Australia (44%), 16% were from the United Kingdom, and 5% were from Colombia and Madagascar. Three distinct groups covered finances (n=47), species, and social impacts of offsetting (n = 23) and offsetting frameworks (n=16). Articles covering monetary and finance aspects had a lower predicted sentiment score (-0.72, 95% CI -0.98 to -0.47) than articles that covered new, alternative offsetting forms (-0.15, 95% CI -0.46 to 0.17), such as mitigation banking and credits. In articles focused on charismatic species and loss of livelihood, offsetting risk and social issues were associated with low sentiment scores (<-0.85). Sentiment scores were high for articles on offsetting at a multicountry or global scale (0.47, 95% CI -0.06 to 0.99), and scores were the lowest in Australia (-1.03, 95% CI -1.36 to -0.70). Public sentiment based on media articles was generally negative toward offsetting, and many of the ecological and methodological issues and risks were reflected in the articles, but mitigation measures as a prerequisite to offsetting were mentioned in only 18% of all articles. With the seemingly high public interest in conservation and hence offsetting, it will be imperative to expand the current breadth of information about offsetting that is being communicated or made available to the public.

Factor returns and FOMC announcements: The role of sentiment

We examine the dynamics of long-short factor returns on FOMC announcement days and the role of sentiment. We find that factor returns are negative on FOMC announcement days. Moreover, on these days returns are significantly lower following low sentiment periods. Hence, investor sentiment is a key driver of factor returns on FOMC days and this effect emanates mainly from the short portfolio leg of each factor.

CEO overconfidence and investor sentiment in M&A decisions

This study investigates the interactive impact of CEO overconfidence and investor sentiment on merger behavior in U.S. firms. We find that the influence of CEO overconfidence on merger frequency is stronger during periods of high investor sentiment, diminishing in low sentiment times. It suggests that investor sentiment is a more dominant determinant than CEO overconfidence in shaping merger frequency. Furthermore, a bullish market trend motivates overconfident CEOs to pursue diversifying mergers, while a bearish market trend encourages cash payments. Overall, overconfident CEOs adapt their merger behavior based on the economic environment, with investor sentiment playing a dominant role in decision-making.

Identifying self-disclosed anxiety on Twitter: A natural language processing approach

BackgroundText analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis. MethodsA total of 233.000 tweets made by 605 users (300 reporting anxiety diagnosis and 305 not) over six months were comparatively analysed, considering user behavior, Linguistic Inquiry Word Count (LIWC), and sentiment analysis. Twitter users with a self-disclosed diagnosis of anxiety were classified as ‘anxious’ to facilitate group comparisons. ResultsSupervised machine learning models showed a high prediction accuracy (Naïve Bayes 81.1 %, Random Forests 79.8 %, and LASSO-regression 79.4 %) in identifying Twitter users’ self-disclosed diagnosis of anxiety. Additionally, a Latent Profile Analysis (LPA) identified four profiles characterized by high sentiment (31 % anxious participants), low sentiment (68 % anxious), self-immersed (80 % anxious), and normative behavior (38 % anxious). ConclusionThe digital footprint of self-disclosed anxiety on Twitter posts presented a high frequency of words conveying either negative sentiment, a low frequency of positive sentiment, a reduced frequency of posting, and lengthier texts. These distinct patterns enabled highly accurate prediction of anxiety diagnosis. On this basis, appropriately resourced, awareness raising, online mental health campaigns are advocated.

The Impact of Technology Attention and Investors on Stock Returns: Taking Science and Technology Innovation Board Company as an Example

Since the fourth anniversary of the opening of the Science and Technology Innovation Board, the number of listed companies on the board has reached 546, with a total fundraising amount of 858.242-billion-yuan, accounting for 42% of the total domestic A-share financing during the same period. The stock return on the Science and Technology Innovation Board has become a topic of concern for investors. This article uses indirect indicators from 2021 to 2023, and uses principal component analysis to construct investor attention and investor sentiment indicators. By using panel analysis, it is found that investor attention has a negative impact on stock return, investor sentiment has a positive moderating effect on investor attention-stock return. In order to further explore the impact and effect of differences in investor sentiment and investor attention in the high and low sentimental group, it conducted a heterogeneity test, which found that the relationship between investor attention and stock returns in the low sentiment group is significantly negative, but not in high group. And there is a significant positive correlation between the investor sentiment moderating effect and stock returns in the high sentiment group, but not in the low sentiment group. This result can be beneficial for guiding market regulatory authorities and consumers to supervise and invest rationally in stocks on the Science and Technology Innovation Board.

Investor sentiment and skewness risk premium

ABSTRACT This paper provides new evidence on the pricing of market skewness risk by incorporating investor sentiment in the relation between sensitivity to innovations in implied market skewness and expected stock returns. Using both univariate and multivariate specifications, we conduct an extensive series of asset pricing tests on the cross-section of stocks during high and low sentiment periods separately. We find that market skewness risk carries a negative premium that cannot be explained away by known risk factors when sentiment is low. In contrast, the results are not conducive to a risk explanation when sentiment is high.

Investor sentiment and firm capital structure

We provide novel evidence of the role of investor sentiment in determining firms' capital structure decisions from three perspectives: leverage ratio, debt maturity and leverage target adjustment. We find that when investor sentiment is high, firms increase their leverage ratios, supporting our contention that high investor sentiment increases firms' debt capacity and facilitates the use of an aggressive leverage policy. Debt maturity is shorter in high sentiment periods, implying that firms are confident about future earnings and use shorter debt maturity to signal their financial solvency. Leverage target adjustment is slower in low sentiment periods, indicating higher costs of external finance. Furthermore, the sentiment-leverage relationship sensitivity is greater for financially constrained firms. Our extended analysis determines that leverage-increasing firms generate lower stock returns subsequent to a period of high sentiment, offering practical insights into the economic consequences of increasing leverage in high sentiment periods on corporate value for investors. Our research advances the understanding of the impact of investor sentiment on firms' financing decisions and stock returns.

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.

A Decision Theoretic Foundation for Noise Traders and Correlated Speculation

Noise traders are a central idea in the modern theory of asset markets, yet there is not a standard model of such agents in contrast to the well-established representation of rational agents as expected utility maximizers. We propose the Hurwicz criterion, a classical criterion in decision analysis for choice under uncertainty, as a foundation for noise traders in asset markets. Hurwicz agents trade on optimism and pessimism and do not trade on information. A binary asset market is introduced with asymmetric information and heterogeneity both in rationality and in ambiguity attitudes. In this environment, noise trader behavior is endogenously positively correlated, the market is more efficient in low sentiment periods, and the favorite-longshot bias holds in equilibrium. The analysis demonstrates that aggregate market properties such as positive trading volume and the favorite longshot bias can be derived from the micro behavior of individual agents that have an axiomatic foundation.

The Media Reinforcement Effect in the Chinese Stock Market

This article focuses on the interaction between media and asset prices and explores the potential mechanisms that drive stock market reaction to news media. The authors find that when buying past losers with low sentiment and selling past winners with high sentiment, the return obtained exceeds the standard reversal effect, and media sentiment has the effect of enhancing stock returns; that is, there is a media reinforcement effect. When the returns are opposite to the media sentiment, the return obtained is lower than the standard reversal effect; that is, the media reinforcement effect disappears. Using different types of media, the authors find that the state-controlled media has a media reinforcement effect, while the private media does not have this same effect. At the same time, the authors find that the stronger the heterogeneous beliefs of investors and the more severe the arbitrage restrictions, the more significant the media reinforcement effect. This article helps to clarify the internal mechanism underlying the market’s reaction to the news media.

The effects of drought on stock prices: An industry-specific perspective

In this study, we examine the effect of drought on industry stock prices using a balanced panel of monthly data for 15 industries classified by China Securities Regulatory Commission in 2012. By combining the results of ordinary least squares (OLS) estimation and quantile regression models, we present a comprehensive evaluation of the relationship between drought and industry stock prices. The OLS regression results generally show that drought is negatively correlated with industry stock prices. However, quantile regression reveals that the effect of drought changes from positive to negative from the lowest to the highest stock price quantile. In addition, drought resistance capacity varies by industry. We further use threshold regression to determine the effects of investor sentiment on the relationship between drought and stock prices and identify two different regimes: low sentiment and high sentiment. In the low sentiment regime, drought has a significant negative effect on industry stock prices, while in the high sentiment regime, drought has a significant positive impact on industry stock prices.

Mutual fund flows and seasonalities in stock returns

We propose a flow-based explanation for two long-standing anomalies in empirical finance – Sell in May and the January effect. We find that mutual fund flows exhibit similar seasonal patterns as stock returns. After controlling for fund flows both calendar effects become insignificant. We provide new evidence on what drives this correlation. We show that return seasonality is due to unanticipated fund flow driven by uninformed (flow-motivated) retail investor trading. Active funds indicate flow-induced price pressure with a corresponding reversal of the effect, while passive funds suggest feedback trading instead. These seasonalities are remarkably pervasive, exhibiting little variation across different types of stocks, and are equally strong in periods of either high or low sentiment.

Investor Sentiment and Market-Wide Liquidity Pricing

The recent asset pricing evidence on the return-liquidity risk relationship is mixed and somewhat ambiguous. We reevaluate the importance of market-wide liquidity and liquidity risk for equity pricing by taking the role of investor sentiment into account. Regarding the market-wide liquidity level as a systematic factor, we find that high market sentiment tends to weaken the effect of market-wide illiquidity - both expected and unexpected - on stocks returns. With respect to systematic liquidity exposure as a priced risk factor, the results show that the effect of exposure to shocks in aggregate liquidity on expected returns is significantly positive when sentiment is low, while it is significantly negative when sentiment is high suggesting that “rational” asset pricing is only valid in the low sentiment regime without too much turbulence caused by sentiment traders.

Sentiment Beta and Asset Prices: Evidence from China

ABSTRACT This article examines the relationship between sentiment beta and stock returns in Chinese stock market. Stocks with low (negative) sentiment beta significantly outperform those with high (positive) sentiment beta. When arbitrage is highly restricted or the stocks are difficult to value, the negative relationship between sentiment beta and stock returns is more pronounced. Further investigation shows that the results are mainly driven by periods of crisis and low economic policy uncertainty (EPU). In general, there exists an against minus catering sentiment (AMC) pricing factor in China.

Investor Sentiment and the Time Variation of the Illiquidity Premium

This paper examines the return premium associated with illiquidity through time. Prior research has documented that investors command a return premium for holding the most illiquid stocks. The idea behind the return premium is that investors demand higher returns as compensation for the risk of not being able to liquidate their position in a timely manner (see Amihud and Mendelson (1986)). We find that the illiquidity premium has substantial variation across time. For instance, during the 25 years examined, the illiquidity premium is only significant in 11 of those years. In fact, the standard deviation of the illiquidity return premium is greater than the average return premium in some specifications. In additional tests, we find that during periods of low investor sentiment, the illiquidity premium is the highest, suggesting that sentiment might contribute to the observed time variation in the premium.

ANALYST FORECAST DISPERSION, INVESTOR SENTIMENT, AND THE CROSS-SECTION OF STOCK RETURNS

This paper explores the role investor sentiment plays in the relationship between analyst forecast dispersion and stock returns. With short sale constraints, stock prices are determined by the optimistic investors. There are more optimistic investors during the high sentiment periods when investors suffer more from psychological bias. This is the first paper to document that following the high sentiment periods, stocks with the most analyst forecast dispersion are overpriced, earning significantly negative returns, while those with the least analyst forecast dispersion are not overpriced as the degree of belief dispersion is low. However, following the low sentiment periods, both are not overpriced. A portfolio that longs the least dispersed stocks and shorts the most dispersed stocks yields significantly positive returns only following the high sentiment periods. My findings can potentially reconcile the puzzling risk effect and mispricing effect in the literature. The risk (mispricing) effect suggests a positive (negative) relation between analyst forecast dispersion and future stock returns. Presumably, the magnitude of the mispricing effect depends on the proportion of irrational investors and their bias, which is positively related to investor sentiment. During the high sentiment period, the mispricing effect takes over, and the overall effect is negative. During the low sentiment period, the percentage of irrational investors is mediate, and the mispricing effect and the risk effect counter each other, leading to insignificant relation.

Investor sentiment, style investing, and momentum

Investor sentiment is an important condition for style investing in affecting asset price predictability. We find that style returns have predictive power for future stock returns in high sentiment periods, but not low sentiment periods. The correlation between style returns and stock returns explains the variation in momentum profits in high sentiment periods, but not low sentiment periods. Sentiment has an interaction effect with style returns, but not market returns. While positive style returns predict future stock returns under high sentiment, negative style returns do not. The effect of investor sentiment on style investing is independent of prior market returns.

Psychological factors of Canadian and Mexican tourists and the US tourism sector

This paper investigates the impact of psychological factors of Canadian and Mexican tourists on the US tourism sector. Using the data of 1996–2019, the study uses vector autoregression models and the spillover analysis to perform the investigation. The paper discovers that high insecurity of tourists significantly reduces tourist arrivals, passenger fare receipts, and expenditure of tourists in the US. Also, tourist inflows are highly influenced by insecurity during terrorist attacks, natural disasters, and the financial crisis of the US. It is found that high sentiment of Canadian and Mexican tourists increases their outbound travel to the US, but the impact of sentiment is relatively stronger for the Canadian tourists. Results show that the tourist inflows from Canada and Mexico are influenced by low sentiment during recessionary periods of Canada and Mexico, respectively. The paper finds no robust evidence of mood and nationalism-based retaliation of tourists for traveling to the US.

News sentiment and stock return: Evidence from managers’ news coverages

In this paper, we construct a monthly news-based manager sentiment (SM) based on the tone of managers’ news reports. Statistically, SM has excellent predictability for the subsequent month's return in both in- and out-of-sample periods. we find that SM contains additional information to forecast stock returns compared to popular economic predictors. After analysing the prediction performance at different sentiment levels, it is found that the prediction power of SM is far better in the high sentiment period than in the low sentiment period. In terms of investing, SM also generates considerable economic value for investors who use forecasting information to optimise their stock portfolios.

Does COVID-19 Still Affect Liquidities and Returns in Indonesia?

Most investors need useful information for investment decisions to obtain optimum returns. Based on this assumption, information obtained by investors will influence investment decisions. Information related to the continuation of the COVID-19 pandemic has tended to be a psychological factor affecting investors since 2020. The objective of this study is to analyze whether market liquidity still has an impact on abnormal returns in Indonesia. Logistic regression is used to test the relationship between market liquidity and abnormal returns on 661 firms listed on the Indonesia Stock Exchange over the period of January 1, 2020, to December 31, 2021. By combining systematic and unsystematic risks, illiquidity in 2021 has a positive impact on abnormal returns, although some combinations show insignificant results. This study finds that during 2021, investors tend to have low sentiment, which may be due to the continued threat of the COVID-19 pandemic, especially for stocks of firms that have high abnormal returns but low systematic risk. On the other hand, illiquidity does not have a significant impact on the stock of firms that have high abnormal returns but also high systematic risk from 2020 to 2021. This result indicates that investors in that stock are still optimistic and not influenced by the continuation of the COVID-19 pandemic.