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This study explores the variance in investor responses to the corporate social responsibility (CSR) performance of firms, as influenced by information sources and investor types.

This study applies a short-term event study and cross-sectional analysis with unique CSR datasets obtained from newspaper articles and the Dow Jones Sustainability Index.

Investor reactions are significantly shaped by their sources of information. Individual investors are found to predominantly respond to accessible news announcements, whereas institutional investors show heightened sensitivity to adverse news from both scrutinized sources. Foreign investors, mirroring institutional investors' patterns, uniquely react positively to index additions.

Investors’ assessment of CSR activities varies due to the differing sources of information obtained; further, it is affected by the type of investor.

The findings guide public relation managers in strategizing CSR communication toward diverse investor types. This includes recommending targeted approaches for Japanese individual investors through newspapers and TV, exercising caution in disseminating adverse news to Japanese institutions, and promoting and justifying CSR actions to foreign investors. It underscores the need for a strategic investor relations frameworks that considers accessibility, literacy, and investors' interests.

This study examines the relationship between sources of information for CSR activities and investors’ responses, an area under-represented in the literature. The author uses CSR announcement data, collected from newspapers to make the results more accurate and relevant.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

Based on stakeholder, agency and institutional theory, this study aims to examine the role of institutional ownership in the relationship between environmental, social and governance practices and CEO compensation.

Utilizing a fixed-effect panel regression analysis, this research utilized a panel data approach, analyzing data spanning from 2014 to 2021, focusing on US companies listed on the S&P500 stock market index. The dataset encompassed 219 companies, leading to a total of 1,533 observations.

The analysis identified that environmental scores significantly impact CEO equity-linked compensation, unlike social and governance scores. Additionally, it was found that institutional ownership acts as a moderating factor in the relationship between the environmental score and CEO equity-linked compensation, as well as the association between the social score and CEO equity-linked compensation. Interestingly, the direction of these moderating effects varied between the two relationships, suggesting a nuanced role of institutional ownership.

This research makes a unique contribution to the field of corporate governance by exploring the relatively understudied area of institutional ownership's influence on the ESG practices–CEO compensation nexus.

The study attempts to examine the impact of mandatory corporate social responsibility (CSR) spending and inclusion of firms into the environment, social and governance (ESG) index of BSE India on the performance of firms constituting firms under the Bombay Stock Exchange (BSE) 100 Index.

The stock prices of the firms were collected from the official website of BSE India for a total of 32 firms and the System Generalized Method of Moments (GMM) model was utilized for analyzing the data for the present study.

The study found that the investors in the Indian market do consider the CSR spending and ESG listing as a factor while framing the investment strategy; however, ESG listing is least preferred. Among the other variables, AGE, DPS, EPS and BVPS have a significant positive bearing on the firm's performance, while SIZE has a significant negative impact on the firm's performance.

Further investigation is needed to understand the factors that influence investment decision-making, including why investors tend to overlook CSR and environmental protection. Future research can identify ways to increase the importance of these factors in investment decision-making. Future research can explore the long-term impact of investing in socially responsible companies, including whether such investments lead to better long-term performance.

There is a need for increased awareness of the importance of CSR among investors. Educational programs and campaigns can be used to inform investors about the potential benefits of considering social responsibility factors in investment decision-making. Companies that prioritize CSR and environmental protection should distinguish themselves from competitors in the eyes of investors. This can lead to higher investment and potentially higher returns for these companies.

Since mandatory CSR expenditure and the launch of the ESG index by the BSE have been introduced in India recently, hardly any study in India has examined the impact of the same on the firm's performance.

This study aims to, firstly, develop a red flag checklist for cryptocurrency Ponzi schemes and, secondly, to test this red flag checklist against publicly available marketing material for Mirror Trading International (MTI). The red flag checklist test seeks to establish if MTI’s marketing material posted on YouTube^® (in the form of a live video presentation) exhibits any of the red flags from the checklist.

The study uses a structured literature review and qualitative analysis of red flags for Ponzi and cryptocurrency Ponzi schemes.

A research lacuna was discovered with regard to cryptocurrency Ponzi scheme red flags. By means of a structured literature review, journal papers were identified that listed and discussed Ponzi scheme red flags. The red flags from the identified journal papers were subsequently used in a qualitative analysis. The analyses and syntheses resulted in the development of a red flag checklist for cryptocurrency Ponzi schemes, with five red flag categories, containing 18 associated red flags. The red flag checklist was then tested against MTI’s marketing material (a transcription of a live YouTube presentation). The test resulted in MTI’s marketing material exhibiting 88% of the red flags contained within the checklist.

The inherent limitations in the design of using a structured literature review and the lack of research regarding the cryptocurrency Ponzi scheme red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes. The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The red flag checklist can be applied to a cryptocurrency investment scheme’s marketing material to establish if it exhibits any of these red flags.

The study provides a red flag checklist for cryptocurrency Ponzi schemes.

Stock market has always been lucrative for various investors. But, because of its speculative nature, it is difficult to predict the price movement. Investors have been using both fundamental and technical analysis to predict the prices. Fundamental analysis helps to study structured data of the company. Technical analysis helps to study price trends, and with the increasing and easy availability of unstructured data have made it important to study the market sentiment. Market sentiment has a major impact on the prices in short run. Hence, the purpose is to understand the market sentiment timely and effectively.

The research includes text mining and then creating various models for classification. The accuracy of these models is checked using confusion matrix.

Out of the six machine learning techniques used to create the classification model, kernel support vector machine gave the highest accuracy of 68%. This model can be now used to analyse the tweets, news and various other unstructured data to predict the price movement.

This study will help investors classify a news or a tweet into “positive”, “negative” or “neutral” quickly and determine the stock price trends.

As public awareness of the concept of sustainable development has increased, a new investor market has appeared. These investors will only make investments in sustainable financial instruments. Yet, how corporate managers can effectively exploit this new financing concept to make their companies risk resilient remains unaddressed. This study, a conceptual research, aims to examine the impact of sustainable finance (SF) on business risk resilience (BR) and the impact of SF on risk management infrastructure (RI). It also addresses the impact of RI on BR and the mediating effect of the former between SF and BR in the corporate world. Finally, this research explores the moderating effect of managerial capability (MC) and firm technology-focused innovation capability (IC) between SF and RI.

This study incorporates both theoretical and empirical works in the sustainability, innovation, risk management and HRM fields. Afterwards, it constructs a conceptual model alongside suppositions that can be tested in further studies.

This study proposes that SF will enhance BR and RI. Moreover, RI will promote BR and positively intervene between SF and BR. Furthermore, MC and IC will reinforce the SF–RI impact such that the SF–RI impact will be strengthened for companies whose MCs and ICs are high than low.

This research affords suggestions for researchers in multidisciplinary fields. It reinforces BR and RI by introducing SF, MC and IC as tactical devices. It also serves as a reference point for forthcoming academics to investigate this conceptual model, empirically, in diverse industries worldwide.

Practical lessons for finance, investment and risk managers, as well as corporate investors are discussed.

This study provides a new research model that demonstrates how SF can be exploited to promote BR and build RI. It also shows how RI can bolster BR and how RI can connect SF to BR. This new model also exhibits how MC and IC moderate the impacts of SF and RI. Thus, it attempts to advance existing knowledge and theoretical frameworks.

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

This study investigates the relationship between board gender diversity (BGD) and the time to Initial Public Offering (IPO), which stands as an entrepreneurially risky choice, particularly challenging in family firms. We also investigate the moderating role of family ownership dispersion (FOD).

We draw on an integrated theoretical framework bringing together the upper echelons theory and the socio-emotional wealth (SEW) perspective and on hand-collected data on a sample of Italian family IPOs that occurred in the period 2000–2020. We employ ordinary least squares (OLS) regression and alternative model estimations to test our hypotheses.

BGD positively affects the time to IPO, thus, it increases the time required to go public. FOD negatively moderates this relationship. Our findings remain robust with different measures for BGD, FOD, and family business definition as well as with different econometric models.

The article develops literature on family firms and IPO and it enriches the academic debate about gender and IPOs in family firms. It adds to studies addressing the determinants of the time to IPO by incorporating gender diversity and the FOD into the discussion. Finally, it contributes to research on women and outcomes in family firms.