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We use a random forest model to classify firms' financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment. [ABSTRACT FROM AUTHOR]

This study investigates the role of free cash flows and (cross-sectional and time-series) price momentum in predicting future stock returns. Past returns and free cash flows each positively predict future stock returns after controlling for the other, suggesting that cash flows and momentum both contain valuable and distinctive information about future stock returns. A strategy of buying past winners with high free cash flows and shorting past losers with low free cash flows significantly outperforms the traditional momentum trading strategy. The enhanced performance is not sensitive to investor sentiment, time variations, or transaction costs. Further analysis shows that the incremental cash flow effects are largely attributable to net distributions to equity/debt holders. Overall, our findings shed light on the role of corporate fundamentals in technical trading strategies. [ABSTRACT FROM AUTHOR]

Textual data require an analytical trade-off between breadth and depth. Automated approaches locate patterns across large swaths of data points but sacrifice qualitative insight because they are not well equipped to deal with context-determined ways to express meaning, like figurative language. To strengthen the power of automated text analysis, researchers seek hybrid methodologies that combine computer-augmented analysis with sociocultural researcher insights based on qualitative textual interpretation. This article demonstrates a new method, which the authors term metaphor-enabled marketplace sentiment analysis (MEMSA). Building on existing automated text analysis methodologies linking word lists to sentiments, MEMSA adds metaphors that associate topics with sentiments across domains. Using MEMSA, researchers can leverage the sentiment potential of these located metaphors and scale insights to the level of big textual data by employing a dictionary approach enhanced by a specific and useful linguistic property of metaphors: their predictable structure in text (something is something else). This article shows that metaphors add associative detail to sentiments, revealing the targets and sources of sentiments that underlie the associations. Understanding nuanced market sentiments enables marketers to identify sentiment-based trends embedded in market discourse, so they can better formulate, target, position, and communicate value propositions for products and services. [ABSTRACT FROM AUTHOR]

We examine the evolutionary effects of sentiment words in financial text and their implications for various business outcomes. We propose an algorithm called Word List Vector for Sentiment (WOLVES) that leverages both a human-defined sentiment word list and the word embedding approach to quantify text sentiment over time. We then apply WOLVES to investigate the evolutionary effects of the most popular financial word list, Loughran and McDonald (LM) dictionary, in annual reports, conference calls, and financial news. We find that LM negative words become less negative over time in annual reports compared to conference calls and financial news, while LM positive words remain qualitatively unchanged. This finding reconciles with existing evidence that negative words are more subject to managers' strategic communication. We also provide practical implications of WOLVES by correlating the sentiment evolution of LM negative words in annual reports with market reaction, earnings performance, and accounting fraud. [ABSTRACT FROM AUTHOR]

This study examines investor attention connectedness measures before and after the COVID-19 outbreak. We find that investor attention spillovers persist among global equity markets, and developed markets dominate as shock transmitters. The spillover effect increased significantly amidst the COVID-19 pandemic period due to escalating market turmoil. The empirical results suggest that investor attention interdependencies have important implications for improving our understanding of the shock transmission of global equity markets and co-movement dynamics. Our findings offer additional insights to investors and speculators to design better portfolio strategies by considering the net spillover effects of investor attention between numerous equity markets. [ABSTRACT FROM AUTHOR]

The introduction of regulated CME futures contracts on Bitcoin in 2017 raised an expectation that cryptocurrencies would become part of mainstream financial markets. This also heightened links between traditional markets and Bitcoin, implying that the cryptocurrency would be subject to systematic spillovers. This paper uses high‐frequency data to examine whether Bitcoin basis risk is linked to investor sentiment from established financial markets. Our findings indicate that extreme investor sentiment, as reflected by the tail risk in various volatility indices, including the VIX, consistently correlates with a negative Bitcoin basis, where Bitcoin futures prices are lower than spot prices. Fluctuations significantly influence this relationship in the trading volume of Bitcoin futures and are more pronounced during periods of substantial unexpected inflation and deflation. These results underline the complex dynamics between market sentiment and cryptocurrency pricing, offering insights with substantial implications for investors and policymakers. [ABSTRACT FROM AUTHOR]

This research examines the effects of information disclosure ratings (IDR) on firm-specific stock price crash risk. We present evidence that there is a statistically significant negative relationship between stock price crash risk and IDR. Specifically, effective information disclosure attracts greater investor attention and leads to more liquidity, which mitigates the stock price crash risk. Our findings remain robust after controlling for relevant variables and addressing the issue of endogeneity. This research proves that high IDR mitigates the stock price crash risk by eliciting market reaction, which not only introduces a novel perspective for investors in their analysis of corporate risks but also offers valuable directions for policy formulation to guide the market. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to unravel the relationship between market-driven impacts of climate change and firms' deployment of renewable energy (RE) innovation. The purpose is to understand how market-related forces, influenced by uncertainty, shape firms' behaviour in response to climate change challenges. Design/methodology/approach: Drawing on the behavioural theory of the firm (BTOF), the paper develops a conceptual model to decode the relationship between each category of market-driven impacts and the resulting RE innovation within firms. The model takes into account the role of uncertainty and differentiates between multinational enterprises (MNEs) and domestic firms. Findings: The analysis reveals five key sources of market-driven impacts: investor sentiment, media coverage, competitors' adoption of ISO 14001, customer satisfaction and shareholder activism. These forces influence the adoption of RE innovation differently across firms, depending on the level of uncertainty and the discrepancy between environmental performance and aspiration level. Originality/value: This paper contributes to the literature in four ways. Firstly, it emphasises the importance of uncertainty associated with market-driven impacts, which stimulates different responses from firms. Secondly, it fills a research gap by focusing on the proactivity of firms in adopting RE innovation, rather than just operational strategies to curb emissions. Thirdly, the paper extends the BTOF by incorporating the concept of uncertainty in explaining firm behaviour. Finally, it provides insights into the green strategies of MNEs in the face of climate change, offering a comprehensive model that differentiates MNEs from domestic firms. [ABSTRACT FROM AUTHOR]

Purpose: With the rise of mandating climate-related disclosures (CRD), this paper aims to investigate how energy and agriculture markets are exposed to climate disclosure risk. Design/methodology/approach: Using the multivariable simultaneous quantile regression and data from 1 January 2017 to 29 February 2024, the authors examine daily and monthly responses of energy and agriculture markets to climate disclosure risk, energy risk, market sentiment, geopolitical risk and economic policy risk. The sample covers the global market, Australia, Canada, European Union (EU), Hong Kong, Japan, New Zealand, Singapore, the UK and the USA. Findings: The results show that climate disclosure risk creates both positive and negative shocks in the energy and agriculture markets, and the impacts are asymmetric across quantiles in different economies. The higher the climate disclosure risk, the greater impact of crude oil future on the energy sector in North America (Canada and the USA) and Europe (EU and the UK), but no greater effects in Asia Pacific (Australia, New Zealand and Singapore). The agriculture sector can hedge against economic policy and geopolitical risks, but it is highly exposed to climate disclosure and energy risks. Originality/value: This study timely contributes to the modest literature on the asymmetric effects of climate disclosure risk on the energy and agriculture markets at the global and national levels. The findings offer practical implications for policymakers and investment practitioners in understanding financial effects of mandating CRD to diversify risks depending upon market conditions and policy uncertainty. [ABSTRACT FROM AUTHOR]

We explore the impact of investor attention on idiosyncratic risk in the cryptocurrency markets. Taking the Google Trends Index as the measure of investor attention, we find that investor attention can significantly reduce cryptocurrencies' idiosyncratic risks by increasing the liquidity. We further study possible cross-sectional variations of the effect of investor attention on idiosyncratic risk. Evidence shows that the investor attention effect is more pronounced for smaller-cap and younger cryptocurrencies. Moreover, a relatively stable external market environment and rising market state are conducive to the further play of the attention effect. [ABSTRACT FROM AUTHOR]

Do behavioral factors mediate the relationship between industry returns and Bitcoin returns? We use four industry indices in technology, energy, clean energy, and banking, and the Sentiment index from Thomson Reuters Marketpsych Indices as a behavioral factor to investigate this question. We show that the sensitivities of technology and clean energy industry indices to Sentiment, positively and significantly, strengthen the relationship between sentiment and Bitcoin returns. By showing that behavioral factors mediate the association between the returns of industry indices and Bitcoin returns, we provide evidence that investors' Sentiment captures the association between Bitcoin and sectors related to cryptocurrencies. Our results, however, do not support prior studies' findings of a direct relationship between the industry indices and Bitcoin returns. [ABSTRACT FROM AUTHOR]

In this paper, we show that industry volatility concentration is a strong predictor for aggregate stock market returns. Our monthly industry volatility concentration (IVC) index displays significant predictive ability, with in‐sample and out‐of‐sample R2 statistics of 0.686% and 0.712%, respectively, which outperforms a host of prevailing return predictors. Moreover, the IVC index can generate high utility gains of 143.8 basis points above the historical average benchmark for mean–variance investors. We find that the IVC index is countercyclical. Furthermore, the predictive source of the IVC index not only stems from the cash flow and discount rate channels but is also explained by the channels of investor attention and sentiment. The predictive ability of our IVC index also remains significant under a broad range of robustness tests. [ABSTRACT FROM AUTHOR]

This paper developed a mediating effect model of retail opinion divergence, investor sentiment, and stock liquidity to investigate how investor comments and bullish-bearish-polling activities on social media affect investors’ attitudes and behaviours, thus, the stock market. The paper first used the Python programming language to scrape the bullish-bearish-polling outcomes for each stock and developed an investor opinion divergence index. Next, the study collected online investor comments, from which an online investor sentiment index was developed through machine-learning-based ways. The analysis results show that both investor sentiment and retail opinion divergence significantly impact stock liquidity, and investor sentiment plays a mediating role in it. [ABSTRACT FROM AUTHOR]

In this paper, we propose utilizing machine learning methods to determine the expected aggregated stock market risk premium based on online investor sentiment and employing the multifold forward-validation method to select the relevant hyperparameters. Our empirical studies provide strong evidence that some machine learning methods, such as extreme gradient boosting or random forest, show significant predictive ability in terms of their out-of-sample performances with high-dimensional investor sentiment proxies. They also outperform the traditional linear models, which shows a possible unobserved nonlinear relationship between online investor sentiment and risk premium. Moreover, this predictability based on online investor sentiment has a better economic value, so it improves portfolio performance for investors who need to decide the optimal asset allocation in terms of the certainty equivalent return gain and the Sharpe ratio. [ABSTRACT FROM AUTHOR]

This study uses large stock dividends (LSDs) of Chinese listed firms from 1999 to 2018 to study the purpose of their issuance. We find that turnover rate and stock liquidity do not increase significantly after LSDs are disbursed. Stocks respond positively to LSD announcements, whereas firms' buy-and-hold abnormal returns and operating performance deteriorate. Furthermore, managers first cater to investor sentiment by paying LSDs and then cash out their stockholdings for personal profit at the expense of shareholder wealth. The regulators in China and other emerging markets should protect investors' interests by preventing the potential abuse of LSDs. [ABSTRACT FROM AUTHOR]

We investigate the extent of investors' awareness of the bubble risk of assets' fundamental value by examining Chinese listed companies' goodwill bubbles. We find that firms with larger goodwill have a higher possibility of goodwill impairment recognition in the future, indicating a higher bubble risk of companies' assets fundamental. Next, we find that firms with more goodwill experience lower stock returns in subsequent 1–3 years, which means investors do not demand corresponding risk compensation and underestimate the goodwill bubble risk for these firms. Furthermore, we investigate five behavioral biases driving investors to underestimate the bubble risk. The results show that investors' gambling preference for bubble assets is the key driver, while investors limited attention, extrapolation, opinion divergence, and earnings expectation are not applicable in our setting. Our study suggests that investors' gambling preference is a channel through which the risk of companies' assets fundamental bubble transmits to the stock market. [ABSTRACT FROM AUTHOR]

The extreme weather and climate occur frequently attracted high attention from society, which brings high uncertainty risks to enterprises. This study uses a fixed effects model to investigate the impact of corporate climate-related risk perceptions on their behavior. We found that increased climate-related risk perception catalyzes corporate green and low-carbon transitions (GLCT). From the perspectives of internal governance and external supervision, it is found that executive risk aversion, government environmental regulation, and investor attention can all contribute to the positive impact of climate-related risk perception on GLCT. Additionally, corporate climate-related risk perceptions can contribute to transition outcomes and lead to favorable capital market responses by improving GLCT actions, and that the contribution of climate-related risk perceptions to GLCT is stronger among non-state-owned enterprises and high-polluting industries. This study provides strategic insights for organizations to effectively manage climate risk. [ABSTRACT FROM AUTHOR]

This study constructs a monthly index of skilled analysts (ISA) regarding the coverage by such analysts and explores their predictive ability on the future excess returns of Chinese A-share market. The empirical results reveal that ISA significantly and positively predicts excess stock market returns, with R2s of 4.39% and 4.13% in- and out-of-sample respectively, which surpasses the predictive ability of most commonly used economic variables. High ISA precedes a higher investor sentiment index (ISI) and lower idiosyncratic volatility (IVOL) at firm level. The conclusion remains valid after controlling for a series of other predictor variables and performing robustness tests. [ABSTRACT FROM AUTHOR]

This study develops a theoretical model to capture volatility-managed portfolios' risk-adjusted returns affected by investor sentiment, and uses Chinese A-share market data to analyze the volatility-managed effect based on the small-minus-big (SMB) factor and explain the abnormal returns of volatility-managed portfolios from the investor sentiment perspective. Our results show that the Sharpe ratio of the SMB factor significantly increases after volatility management, especially in low-sentiment periods. Moreover, the mechanism analysis shows that in low-sentiment periods, small-cap stock investors overreact to volatility compared to large-cap stock investors, making the SMB factor significantly positively correlated with lagged volatility. Additional analyses show that volatility-managed portfolios constructed through stocks with gambling characteristics can achieve higher abnormal returns, and the abnormal returns of volatility-managed portfolios cannot be corrected by arbitrage traders as arbitrage is ineffective, reflecting the immaturity of China's emerging capital market. [ABSTRACT FROM AUTHOR]

This research aims to examine the changes in abnormal returns (AR) and trading volume activity (TVA) before and after the announcement of MUI Fatwa Number 83 of 2023, which targets companies for boycott due to their alleged affiliation with Israel. This study employed an event study approach, using a 5-day event window, 10-day event window, 20-day event window and 30-day event window before and after the Fatwa's announcement to measure abnormal returns and trading volume activity. The analysis began by examining the normality of the data to determine whether it was normally distributed. For normally distributed data, a Paired Sample T-test was used, while the Wilcoxon Signed Rank test was applied to non-normally distributed data. The analysis reveals a significant difference in AR during the initial 5-day window, indicating a strong short-term market reaction driven by investor sentiment and uncertainty. However, for longer windows (10, 20, and 30 days), no significant differences in AR were found, suggesting that the market stabilized as new information was absorbed, consistent with the Efficient Market Hypothesis (EMH) by Eugene Fama (1970). Conversely, TVA showed significant increases across all event windows, indicating sustained investor interest and heightened trading activity. This suggests that while the impact on stock prices was short-lived, the boycott had a lasting influence on trading volume, reflecting continued portfolio adjustments. [ABSTRACT FROM AUTHOR]

This study conducts a detailed investigation into the interplay between major sporting events, specifically the ICC Cricket World Cups and FIFA Football World Cups, and their potential impact on the relationship between dividend announcements and stock market returns. Beyond the customary exploration of investor sentiment and its connection to stock market returns, our research thoroughly examines the effects of these significant sports events on the stock market's reaction to dividend announcements. Drawing on extensive FTSE 350 index data spanning January 1990 to December 2021, we employ event study methodology as the primary analytical framework. To bolster the reliability of our findings, we apply the Generalized Method of Moments (GMM) estimation method, addressing potential endogeneity concerns. Our results uncover a distinct pattern—the stock market exhibits a less favourable response to dividend increases announced following England's victories in major sporting events, such as the FIFA Football World Cup and ICC Cricket World Cup, compared to instances where they faced defeat. Additionally, we observe a more negative market response to dividend decreases announced following England's losses in these pivotal sporting events, as opposed to England emerging victorious in these key contests. This research contributes valuable insights into the intricate relationship between sports passion and market dynamics, offering implications for both scholarly discourse and investment strategy formulation. [ABSTRACT FROM AUTHOR]

We test the role of dividends and investor sentiment in the relation between idiosyncratic risk and expected returns because Pastor and Veronesi (J Financ 58:1749–1789, 2003) find evidence that dividends reduce firm-specific uncertainty by sending information to the market participants through dividends. Also, Baker and Wurgler (J Financ 61:1645–1680, 2006) document that the negative relation between idiosyncratic risk and expected return only exists under the optimistic sentiment. We first document that the negative relation between idiosyncratic risk and expected return is more concentrated for stocks without dividends than stocks with dividends. We further find that the role of dividends in the relation between idiosyncratic risk and expected return is not affected by investor sentiment. These findings are robust to weighing schemes of returns and firm characteristics such as beta, size, book-to-market ratio, momentum, and liquidity. [ABSTRACT FROM AUTHOR]

Prior research finds mixed evidence that firms strategically manage their earnings announcement timing to either highlight or obscure financial information. While most prior studies focus on the specific timing and the nature of individual earnings announcements, we instead focus on the variability of firms' annual earnings announcement dates (hereafter referred to as EADs) over a span of time. Using archival data collected from I/B/E/S and Compustat, we find that firms with fewer resources, weaker internal monitoring systems, and greater financial uncertainty are much more likely to exhibit increased EAD variability. Furthermore, we provide substantial evidence that the capital market's response to earnings is noticeably weaker when a firm's EAD variability is higher. Additional in-depth analysis reveals that firms exhibiting higher EAD variability tend to report significantly lower future performance in both the short- and long-term horizons. Consequently, while managers might intentionally alter an earnings announcement date to exploit variations in investor attention, this comprehensive study provides significant evidence that they should also consider how the market perceives and interprets the overall EAD variability. This understanding is crucial to improve strategic financial communication and maintain investor trust. [ABSTRACT FROM AUTHOR]

Popular methods to value Bitcoin include the stock-to-flow model, Metcalfe's Law, technical analysis, and sentiment-related measures. Within this paper, I test whether such models and variables are predictive of Bitcoin's returns. I find that the stock-to-flow model predictions and Metcalfe's Law help to explain Bitcoin's returns in-sample but have limited to no ability to predict Bitcoin's returns out-of-sample. In contrast, Bitcoin market sentiment and technical analysis measures are generally unrelated to Bitcoin's returns in-sample and are poor predictors of Bitcoin's returns out-of-sample. Despite the poor performance of Bitcoin return predictors within out-of-sample regressions, I demonstrate that a very successful out-of-sample Bitcoin tactical allocation or "market timing" strategy is formed via blending out-of-sample univariate model predictions. This OOS-blended model trading strategy, which algorithmically allocates between Bitcoin and cash (USD), significantly outperforms buying-and-holding or "HODL"ing Bitcoin, boosting CAPM alpha by almost 1300 basis points while also increasing portfolio Sharpe Ratio and Sortino Ratio and dramatically reducing portfolio maximum drawdown relative to buying-and-holding Bitcoin. [ABSTRACT FROM AUTHOR]

As the green bond market in China develops and its institutional structure improves, the green bond has emerged as a pivotal element within the broader framework of the green financial system. We focus on bond issuers in China's A-shares from the years 2010 to 2021 and explore green bond issuance and the spillover effect of green technology innovation under the market attention perspective. Findings are that: (1) Green bond issuance can produce the spillover effect in the industry and significantly enhance peer enterprises' green technology innovation. (2) From the viewpoint of market attention, analyst attention can significantly enhance the spillover effect of green bond issuance within the industry. The same is true for media attention and investor attention. (3) Further research shows that within the same industry, the spillover effect is more pronounced for state-owned enterprises, large-scale enterprises, and enterprises in regions with higher levels of green financial development. For the booming development of China's green bond market and the sustainable development of enterprises, this paper provides theoretical and practical foundations. [ABSTRACT FROM AUTHOR]

The objective of this research is to empirically explore the impact of forward looking statements on the stock liquidity with investor sentiment as mediation variables. The independent variable is the forward looking statement and the dependent variable is stock liquidity and investor sentiment as mediation variables. The analysis technique used is a linear multivariate regression analysis technique. Data span from 2017 to 2022 and covers manufacturing firms listed on the Tehran Stock Exchange. The findings of the research show that the forward looking statement has a significant positive effect on stock liquidity. Forward looking statements have a significant positive effect on investor sentiment. Investor sentiment has a significant positive effect on stock liquidity. Investor sentiment mediates the effect of forward-looking information on stock liquidity. The empirical findings suggest that investor sentiment can play a role as a mediating factor between the disclosure of forward-looking statements and stock liquidity. Therefore, companies should pay special attention to the management of investors' emotions and gain investors' trust by providing clear and accurate information so that they can improve the liquidity of their shares. This article expands and enriches research on forward-looking information disclosure, as well as and is a reference for regulators to develop rules and regulations and regulate forward-looking information disclosure. The association between the extent of disclosure and stock liquidity is still ambiguous. To the best of the authors' knowledge, this study is the first to investigate the impact of forward looking statement on stock liquidity with investor sentiment as meditation. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to identify and rank the financial, nonfinancial, and behavioral components affecting companies' ERC. Methodology: Using data from 153 companies listed on the Tehran Stock Exchange over the period 2013 to 2022, and employing data mining techniques and two methods: stepwise forward regression and regression decision tree, the influential components on ERC were identified and ranked. Findings: The results of the stepwise forward regression method indicated that the components of auditor's opinion type, earnings per share (EPS), stock liquidity, growth opportunities, earnings stability, inflation rate, sales growth, operating profit ratio, relative strength index per share, and market index return respectively influence ERC. The regression decision tree method results also showed that the components of earnings stability, stock liquidity, EPS, stock price synchronicity, stock trading imbalance, adjusted trading volume, psychological line index, relative strength index per share, earnings conservatism, and financial statement restatements respectively influence ERC. The Wilcoxon test results also showed that the ranking of components influencing ERC is not the same in the two methods. Additionally, comparing the mean absolute error of the two methods indicated that the regression decision tree method identifies and ranks the influential components on ERC more accurately. Conclusion: The results of both methods confirm the high impact of EPS, stock liquidity, earnings stability, and relative strength index per share on the ERC of companies. [ABSTRACT FROM AUTHOR]

Literature on investor sentiment has predominantly been conducted at the market level. Recent studies employing firm‐level sentiment have increasingly turned to textual analysis; however, the suitability of this type of proxy is still unverified. We utilize the Chinese stock market data from 2015 to 2023, aiming to discern whether the jump component of realized volatility possesses characteristics of investor sentiment. Our analysis reveals a pronounced short‐term persistence in jump volatility, particularly, among stocks that are hard to value and those with minimal institutional ownership. Further, we find that stocks exhibiting high monthly jump volatility consistently exhibit underperformance over extended periods, corroborating the hypothesis of sentiment‐induced temporary mispricing phenomena. Significantly, our findings advocate for the adoption of the jump component of realized volatility as a proxy for firm‐specific investor sentiment, offering a novel perspective in the sentiment analysis literature. [ABSTRACT FROM AUTHOR]

This study examines the effect of manager sentiment on conditional conservatism. Manager sentiment refers to widely held beliefs of financial managers about their firms' future economic prospects that are not justified by available economic fundamentals. Manager sentiment is likely to affect conditional conservative reporting because the decision to recognize unrealized economic losses in a timely manner flows from financial managers' beliefs about their firms' future cash flow prospects. We predict and find that manager sentiment is negatively associated with conditional conservatism, indicating that firms report less conservatively during periods of high manager sentiment (over‐optimism) and more conservatively during periods of low manager sentiment (over‐pessimism). Moreover, the effects of manager sentiment on conditional conservatism remain strongly negative after controlling for manager overconfidence. We further find that asset write‐offs are lower during high sentiment periods but higher in subsequent periods. Importantly, the manager sentiment effect on conservatism is incremental, and the opposite in sign, to the effect of investor sentiment, which has not been demonstrated in prior literature. [ABSTRACT FROM AUTHOR]

This paper investigates the role of credit market sentiment and investor beliefs in credit cycle dynamics and their transmission to businesscycle fluctuations. Using U.S. data from 1968 to 2014, we find that credit market sentiment is indeed able to detect asymmetries in a small‐scale macroeconomic model. An unexpected credit market sentiment shock has different impacts in an optimistic and pessimistic credit market environment. While an unexpected movement in the optimistic regime leads to a rather muted impact on output and credit, we find a significant negative impact on these variables in the pessimistic regime. The findings highlight the relevance of expectation formation mechanisms as a source of macroeconomic instability. [ABSTRACT FROM AUTHOR]

The excess levels of investor participation coupled with irrational behaviour in the South African bond market causes excess volatility, which in turn exposes investors to losses. Consequently, the study aims to examine the effect of market-wide investor sentiment on government bond index returns of varying maturities under changing market conditions. This study constructs a new market-wide investor sentiment index for South Africa and uses the two-state Markov regime-switching model for the sample period 2007/03 to 2024/01. The findings illustrate that the effect investor sentiment has on government bond indices returns of varying maturities is regime-specific and time-varying. For instance, the 1–3-year government index return and the over-12-year government bond index were negatively affected by investor sentiment in a bull market condition and not in a bear market condition. Moreover, the bullish market condition prevailed among the returns of selected government bond indices of varying maturities. The findings suggest that the government bond market is adaptive, as proposed by AMH, and contains alternating efficiencies. The study contributes to the emerging market literature, which is limited. That being said, it uses market-wide investor sentiment as a tool to make pronunciations on asset selection, portfolio formulation, and portfolio diversification, which assists in limiting investor losses. Moreover, the findings of the study contribute to settling the debate surrounding the efficiency of bond markets and the effect between market-wide sentiment and bond index returns in South Africa. That being said, it is nonlinear, which is a better modelled using nonlinear models and alternates with market conditions, making the government bond market adaptive. [ABSTRACT FROM AUTHOR]

Using proprietary individual-level trading data around a natural experiment—the release of a smartphone trading app by a large investment advisor—this study investigates how smartphone trading technology affects retail investor behavior and mutual fund performance. App adoption by retail investors leads to an increase in investor attention and trading volume. App adopters' flows become more sensitive to short-term fund returns and market sentiment, resulting in higher aggregate flow volume among adopters. The funds more exposed to the shock experience a greater decline in abnormal returns, likely attributable to higher fund flow volume and liquidity costs. As a result, both adopters and nonadopters experience a decline in their mutual fund investment returns. This paper was accepted by Lin William Cong, finance. Funding: The W. Edwards Deming Center and the Eugene Lang Entrepreneurship Center at Columbia University provided funding to support this research. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2021.02099. [ABSTRACT FROM AUTHOR]

This study uses a quantile-on-quantile regression framework to establish a link between investor sentiment proxied by market turnover and stock returns in G7 countries. The QQ analysis results reveal that the impact of investor sentiment on future stock returns is asymmetric and varies across quantiles of stock returns and sentiment. Overall, a significantly negative relationship is observed for all G7 countries. Interestingly, when the market is very bullish, and investors are pessimistic, investor sentiment positively influences future returns, except for Japan. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of financial availability on illegal fundraising activities in China. By collecting 14,481 judgement documents from 2013 to 2019 in China Judgements Online and extracting data, we find that financial availability effectively reduces the amount of money invested, the actual loss and the number of related court cases. This effect remains robust under various robustness specifications. In addition, we find that the attention of investors can increase the negative impact of financial availability on illegal fundraising. [ABSTRACT FROM AUTHOR]

Non-fungible tokens (NFTs) have experienced wild market fluctuation during the past years, which leads to the high volatility of NFT's daily price. This paper examines two potential volatility drivers of NFTs: macroeconomic fundamentals and investor attention. We employ the global and local economic policy uncertainty (EPU) indices as the economic fundamentals' proxies. The investor attention is represented by the Google search volumes (GSV) or NFTs attention index. Based on the empirical results of a modified generalized autoregressive conditional heteroskedasticity –mixed-data sampling (G-M) model, we find that either economic fundamentals or investor attention can increase the volatility of NFTs significantly. The monthly global EPU index adjusted by the current GDP and weekly GSV contain complementary information. Macroeconomic fundamentals and investor attention can jointly model the volatility of NFTs better than considering only one explanatory variable, as suggested by the G-M model with two explanatory variables. The results remain robust to alternative Twitter-based EPU indices and the ongoing COVID-19 pandemic period. [ABSTRACT FROM AUTHOR]

We construct an extreme climate concern indicator (ECC) on the basis of the coverage of the extreme climate news reports. First, ECC significantly negatively forecasts stock market returns in subsequent months. The predictability of ECC returns outperforms alternative confidence indicators and economic predictors over both in-sample and out-of-sample periods. Second, relative to before the Paris Agreement entered into force, extreme climate concerns prominently enhanced the forecasting capabilities after the signing of the Paris Agreement. Third, the return prediction accuracy of ECC in periods of low climate concern is significantly greater than that in periods of high climate concern, which is also consistent with the limited attention of investors. Finally, ECC substantially brings appreciable economic gains to investors, and the relevant empirical results pass a series of robustness tests. [ABSTRACT FROM AUTHOR]

Today, with a growing emphasis on sustainable economic development, corporate environmental, social and governance (ESG) performance is attracting increasing attention and favor from investors. This triggers a question: can good ESG performance of listed companies mitigate the "up and down" of the stock market by drawing investor attention? This paper utilizes the data from China's A-share listed companies from 2011 to 2020, with investor attention as a mediating variable, to explore how the ESG performance of listed companies influences abnormal stock price volatility. The findings suggest that stronger ESG performance of listed companies significantly reduces abnormal stock price volatility, in which investor attention plays a partial mediating role. This paper confirms the robustness of the findings through multiple robustness and endogeneity tests. Heterogeneity analysis reveals that listed companies with good ESG performance during the growth period are more likely to significantly mitigate abnormal stock price volatility. Similarly, firms that maintain commendable ESG performance in bear markets significantly reduce abnormal stock price volatility. These findings enrich the theoretical research on the impact of ESG performance on abnormal stock price volatility, provide empirical evidence for listed companies to emphasize ESG investment and encourage investors to consider ESG ratings. Additionally, the study provides a new perspective for government agencies to utilize corporate ESG performance to maintain the sound development of the capital market. [ABSTRACT FROM AUTHOR]

This work explores if behaviour-based asymmetries are likely to impact deal valuation in the life sciences by examining positive public sentiment as a proxy for market behaviour when negotiating under asymmetric conditions to examine heterogeneity in research & development collaboration (RDC) deal data. We use public sentiment as a proxy for behaviour along with stage of development-based RDC deal data to search for latent classes in the deal data using finite mixture modelling. The analysis reveals a nuanced picture: public sentiment emerges as a significant predictor of deal value, but only for approximately 15% of the data set. This subset exclusively includes firms in the Preclinical stage, where projects have moved past discovery but are yet to commence human studies. Interestingly, the research finds that sentiment's impact on deal valuation is particularly pronounced in this stage, suggesting heightened market sensitivity. With recent research demonstrating that knowledge asymmetry and behaviour impact valuation volatility, we take this further by capturing latent classes within the data which demonstrates how behaviour is most influential in deal pricing considerations. We argue that our research demonstrates the impact of asymmetry and market behaviour on a subset of RDCs where products are known, but likelihood of success is difficult to determine. [ABSTRACT FROM AUTHOR]

Although the 2022 cryptocurrency market crash prompted despair among investors, the rallying cry, "wagmi" (We're all gonna make it.) emerged among cryptocurrency enthusiasts in the aftermath. Did cryptocurrency enthusiasts respond to this crash differently compared to traditional investors? Using natural language processing techniques applied to Twitter data, this study employed a difference-in-differences method to determine whether the cryptocurrency market crash had a differential effect on investor sentiment toward cryptocurrency enthusiasts relative to more traditional investors. The results indicate that the crash affected investor sentiment among cryptocurrency enthusiastic investors differently from traditional investors. In particular, cryptocurrency enthusiasts' tweets became more neutral and, surprisingly, less negative. This result appears to be primarily driven by a deliberate, collectivist effort to promote positivity within the cryptocurrency community ("wagmi"). Considering the more nuanced emotional content of tweets, it appears that cryptocurrency enthusiasts expressed less joy and surprise in the aftermath of the cryptocurrency crash than traditional investors. Moreover, cryptocurrency enthusiasts tweeted more frequently after the cryptocurrency crash, with a relative increase in tweet frequency of approximately one tweet per day. An analysis of the specific textual content of tweets provides evidence of herding behavior among cryptocurrency enthusiasts. [ABSTRACT FROM AUTHOR]

Sustainability concerns are increasingly shaping global investment decisions, prioritising sustainable impacts over mere profit-making. This study examines the performance of Environmental, Social, and Governance (ESG) funds in emerging markets, focusing on bull and bear market scenarios. A Markov Regime Switching model was employed to analyse daily price data from BRICS (Brazil, Russia, India, China, and South Africa) ESG market indices spanning from 31 January 2011 to 2 January 2023. The analysis highlights the variability of ESG returns performance across different market conditions, emphasising the need for tailored investment strategies that account for market dynamics. Additionally, patterns in ESG returns and volatility are identified, along with pairwise relationships among ESG markets within the emerging markets bloc. The study also examines the influence of investor sentiments on ESG performance and controlled for the influence of macroeconomic factors on ESG performance amid changing market conditions. Finally, insights into transition probabilities between bullish and bearish market conditions offer guidance for more resilient investment portfolio management. This research contributes to advancing empirical knowledge on ESG investing in emerging markets, emphasising the significance of investor sentiments and market conditions for sustainable investment practices and long-term financial success. [ABSTRACT FROM AUTHOR]

We investigate investor sentiment regarding mandatory corporate social responsibility (CSR) as a public policy. Using the event study methodology, we analysed the cumulative abnormal returns (AR) of companies impacted by Section 135 of the Indian Companies Act 2013. Our findings suggest that setting a CSR expenditure threshold may lead companies lagging in CSR to over‐invest, potentially hindering value maximisation. Specifically, we observed that the cumulative AR for companies lagging in CSR are lower than those leading in CSR. Therefore, mandating CSR practices may be counterproductive for value creation. This event study is one of the first to evaluate the impact of mandatory CSR as public policy on CSR‐leading and lagging firms. [ABSTRACT FROM AUTHOR]

Under the constraints of low-carbon transformation goals, energy enterprises have significantly increased their debt default risk levels due to carbon price fluctuations. This article first analyzes the contagion mechanism of debt default risk among energy enterprises, and based on this, constructs a debt default risk contagion model among energy enterprises considering carbon price fluctuations, and then simulates and analyzes the evolution characteristics of debt default risk contagion among energy enterprises. The research results indicate that: (1) As the proportion of carbon emission cost increment and investor sentiment index increase, the stability of the debt network of energy enterprises strengthens. As the ratio of commercial credit among energy enterprises and influence of energy enterprises increase, the impact of debt risk gradually intensifies. (2) The investor sentiment index has a strengthening effect on the influence of energy enterprises, the proportion of commercial credit among energy enterprises, and the proportion of carbon emission cost increment. The commercial credit ratio between energy enterprises and its influence has a mutually reinforcing effect. (3) The investor sentiment index has suppressed debt default risk for various energy enterprises. The joint risk suppression effect of the proportion of carbon emission cost increment and the influence of energy enterprises in petroleum and petrochemical enterprises is more prominent. The joint risk constraint ability between the proportion of carbon emission cost increment and investor sentiment index in coal enterprises is stronger. [ABSTRACT FROM AUTHOR]

This study uses unique South Korean data to demonstrate whether the public disclosure of audit hour (effort) information influences investor sentiment, proxied by stock price volatility. Over the 2005–2018 sample period, empirical results show that clients that secure increasing levels of audit hours enjoy lower stock price volatility. Furthermore, incrementally higher levels of audit hours reduce stock price volatility to a greater extent for Big4 clients, compared to Non-Big4 clients. Results are consistent after performing various additional tests including endogeneity, fixed/year effects, and after controlling for the audit fee premium effect. The aforementioned findings are interpreted from an audit demand theory perspective. More specifically, following South Korea's unique audit hour disclosure policy, market participants can make audit quality assertions using audit hour information, which influences investment/disinvestment speculation. Given that audit hour information reporting is rare internationally, the results have important audit policy and business planning implications. [ABSTRACT FROM AUTHOR]

Purpose: The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders. Design/methodology/approach: This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further. Findings: The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy. Research limitations/implications: One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics. Practical implications: The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools. Originality/value: Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision. [ABSTRACT FROM AUTHOR]

The registration-based initial public offering (IPO) system is a pivotal initiative in China's comprehensive capital market reform, but little is known about its effectiveness. Our study aims to explore the impact of the registration-based IPO reform on enterprises' environmental, social, and governance (ESG) greenwashing behaviors. Drawing on data from 2,490 enterprises listed on the Chinese growth enterprise market and the main board of the Shenzhen Stock Exchange during 2012-2022, we find that the registration-based IPO reform significantly aggravates ESG greenwashing with an effect of 0.1696. Building upon this evidence, we explore the underlying mechanism. Peer competition and retail investor sentiment play a partial mediating role and become two channels through which the registration-based IPO reform may aggravate enterprises' ESG greenwashing. Analysts' attention can alleviate the impact of registration-based IPO reform on enterprises' ESG greenwashing while management myopia intensifies it, and they both play a moderating role. Moreover, the aggravating effect of the registration-based IPO reform on ESG greenwashing is more pronounced in enterprises belonging to heavily polluting industries, in the Western region, and with low information transparency. Thus, our findings offer new insights into enterprises' ESG greenwashing behaviors in the context of the registration-based IPO reform. [ABSTRACT FROM AUTHOR]

ESG performance has become vital for business in recent years. Consumers, stakeholders and investors alike seek companies that can show that they are environmentally and socially responsible, especially in periods of uncertainty. Using a new measure of uncertainty, the Climate Policy Uncertainty Index developed by Gavriilidis (Measuring climate policy uncertainty, 2021), this study investigates environmental, social and governance (ESG) performance, firm performance and carbon dioxide emission performance in the context of major developments related to climate policy and events. Further, the study provides insights into how ESG performance moderates the impact of climate policy uncertainty on firm performance and carbon dioxide emission performance. Finally, this paper examines how investor sentiment influences ESG performance during periods of high uncertainty. Based on a large sample of 2640 firms (6462 firm-year observations) from the US Fortune 1000 list covering the years 2008–2018, the empirical results demonstrate that climate policy uncertainty positively affects ESG performance and negatively affects firm performance and carbon dioxide emission performance. In addition, we find that firms enhance their ESG performance when investors are pessimistic, especially during periods of high uncertainty. Finally, we show that ESG performance does not moderate the effects of climate policy uncertainty on firm performance and carbon dioxide emission performance. These findings may help managers and policymakers to boost ESG performance to reap the benefits of ESG activities during periods of uncertainty related to changes in climate policy. Further, the results identify a promising channel via investor power that the government and ESG reporting advocates can utilise to encourage firms to act responsibly during periods of uncertainty. [ABSTRACT FROM AUTHOR]

The market value of a stock is a function of firm performance and market sentiment. Specific events can alter returns and present several challenges to market performances. Through an event study design, this study examines five real estate investment trusts (REITs) market indices' responses to market shock from the initial COVID-19 outbreak. The results revealed negative cumulative abnormal returns for lodging, health care, and retail REITs over the 20-day trading window. Considering their lower drawdown losses, the remaining REIT sectors showed greater resilience than their counterparts. Block bootstrapping confirmed the returns were significantly worse for all sectors, with retail and lodging sectors having the poorest returns. This study advances the literature on pandemic-related market crashes along with how COVID-19 affected cross-sector REIT equities compared to other market indices. REIT firms can use the findings to develop more effective policy measures as responses to pandemic market conditions. [ABSTRACT FROM AUTHOR]

Digital technology has the function of information governance, and digital transformation of enterprises may be the key way to identify and restrain ESG greenwashing. Based on the theory of digital empowerment, this study analyzes the influence and mechanism of digital transformation on restraining corporate green washing behavior from the perspective of internal and external factors. This study takes A-share listed companies in 2012–2022 as research samples and tests the effectiveness of digital transformation. Research has found that (1) digital transformation can significantly suppress corporate greenwashing behavior, and this conclusion still holds after a series of endogeneity and robustness tests. (2) In the context of high environmental awareness among executives, the inhibitory effect of digital transformation on corporate ESG greenwashing is more pronounced. (3) Mechanism analysis shows that digital transformation has inhibited the company's greenwashing behavior by increasing the attention of investors. (4) Heterogeneity analysis shows that in state-owned enterprises, non-heavily polluting industries, high-tech industries, and enterprises located in the eastern region digital transformation has a more effective inhibitory effect on corporate greenwashing behavior. This study examines the impact of digital transformation on corporate ESG greenwashing, expands the research on the non-economic effects of digital transformation, and may provide empirical evidence for improving the quality of ESG information disclosure and sustainable development of enterprises. [ABSTRACT FROM AUTHOR]

Purpose: This study examines the investment horizon influence, mediated by market optimism, on earnings management based on accruals and real activities. Based on short-termism, the authors argue that earnings management increases in optimistic periods to boost corporate profits. Design/methodology/approach: The authors analyzed non-financial Brazilian publicly traded firms from 2010 to 2020 by estimating industry-fixed effects of groups of short- and long-horizon firms to compare their behavior on earnings management practices during bullish moments. For robustness, the authors used alternate measures and trade-off analyses between earning management practices. Findings: The findings indicate that, during bullish moments, companies prioritize managing their earnings through real activities management (RAM) rather than accruals earnings management (AEM), depending on their time horizon. The results demonstrate the trade-off between earnings management practices. Research limitations/implications: This study presents limitations when using proxies for earnings management and investor sentiment. Practical implications: Investors and regulators should closely monitor companies' operations, especially during bullish market conditions to prevent fraud. Originality/value: The study addresses investor sentiment mediation in the earnings management discussion, introducing the short-termism approach. [ABSTRACT FROM AUTHOR]

The study analyses the statistical relationship between the degree of seasonal depression and stock index returns. For this analysis, we examine the daily returns of two US and five European stock indices using OLS regression. The analysis found a statistically significant relationship between seasonal depression and the change in returns. However, due to the limited use of the reduced form, this only confirms the link between seasonal depression and returns, and further observations would be required to confirm a causal relationship. [ABSTRACT FROM AUTHOR]