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The world of investing has changed drastically. Investors are willing to invest the companies that give high priority to environmental, social and governance issues (ESG). This study delves into the performance of the BSE CARBONEX index in comparison to the BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas. It seeks to examine the impact of calendar anomalies, particularly focusing on the day-of-the-week effect, on these indices. To accomplish this, daily closing prices of the BSE CARBONEX, BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas were gathered from the BSE official website. The study period was divided into three segments: the full period, period I (2017–2020) and period II (2020–2022). The study's findings reveal that throughout the full period, period I and period II, BSE Energy exhibited the highest mean daily return compared to the other selected indices. There appears to be a discernible Tuesday effect on the daily average mean returns of BSE CARBONEX, BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas in both the full sample period and period II. Results from ordinary least squares (OLS) analysis by day indicate a notably high positive and statistically significant daily return on Tuesdays, particularly during the full sample period and period II. Furthermore, the GARCH (1,1) model suggests a significant Tuesday effect on the BSE Energy and BSE Oil & Gas indices.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

Introduction: Political stability is an essential source of stock market dynamics. Investors are confident about countries that have higher political stability. Political stability in an economy enables investors to develop their ability to predict the future and thus to tend towards longer-term and permanent economic and financial activities.

Purpose: The study aimed to investigate the impact of political instability in BRICS countries and Türkiye on their stock market volatilities.

Methodology: The study analysed the univariate exponential generalised autoregressive conditional heteroskedasticity (EGARCH) Model. The model employed the credit default swap (CDS) 5-year USD Bond data of the BRICS countries and Türkiye to represent political instability. The daily stock exchange index return data from 1 January 2015 to 15 January 2023 was used for model estimation.

Findings: The results of the EGARCH model indicate that political instability is a crucial factor in stock market volatility. The coefficients suggest that when CDS increases in BRICS countries and Türkiye, the volatility of stock returns also increases. The analysis shows that the impact of political instability on the stock market of BRICS countries and Türkiye is not uniform. However, the significant effect of political instability on volatility is higher for Türkiye than for BRICS countries. This indicates that investors perceive the political risk of Türkiye to be greater than that of BRICS countries when investing in the stock market of Türkiye.

We adopt an information risk view and argue that higher levels of pledge risk incurred by insiders incentivize opportunistic financial disclosure and impair the quality of information available to analysts to forecast firm performance.

We sample Chinese listed companies from 2010 to 2022. Following the literature, we apply established models to measure and test analysts’ forecasting accuracy/dispersion related to controlling shareholders pledging equity and the amount of margin call pressure. Analyst characteristics and nonfinancial disclosures proxied by CSR reports are also examined as factors likely to influence the relationship between pledge risk and analysts’ forecast quality.

We find that analysts’ earnings predictions are less accurate and more dispersed as the proportion of shares pledged (pledge ratio) increases and in combination with greater margin call pressure. Pledge ratios are significantly associated with several information risk proxies (i.e. earnings permanence, accruals quality, audit quality, financial restatements, related party transactions and internal control weaknesses), validating the channel through which equity pledges undermine analysts’ forecast quality. The results also demonstrate that forecast quality declines for a wide variety of analysts’ attributes, including high- and low-quality analysts and analysts from small and large brokerage firms. Importantly, nonfinancial disclosures, as proxied by CSR reporting, improve analysts’ forecasts.

We extend the literature by demonstrating that incremental pledge risk increases non-diversifiable information risk; all non-pledging shareholders pay a premium through more diverse and less accurate earnings forecasts. Our study provides important policy implications with economically significant costs to investors associated with insider equity pledges. Our results highlight the benefits of nonfinancial disclosures in China, which has implications for the current debate on the global convergence of CSR reporting.

After considering the price reversal among countries' indices as a global, coordinated and generalized phenomenon, this paper aims to examine the profitability of the reversal strategy internationally and find an economically essential and predictive reversal effect. Indices' portfolios form based on the prior 48 months; prior losers outperform prior winners by 8.86% per year during the subsequent 48 months. Interestingly, the reversal effect is substantially stronger for emerging countries, yielding 14.04% annually. It remains profitable post-globalization, countering the concern of whether the integration of equity markets synchronized the price reversal worldwide. Returns' differences consistent with portfolio formation approaches are also observed.

This study follows the methodology De Bondt and Thaler (1985) set out and uses the same methodological framework Wouassom et al. (2022) put forward. Nevertheless, this study does not focus on stocks. Still, it employs global equity indices from the viewpoint of an international investor who can switch between worldwide equity indices using a contrarian trading strategy.

My findings indicate that reversal strategies with overlapping portfolios are profitable over the entire sample period and every formation and holding period. These returns are highly statistically significant and vary considerably from one horizon to another. More importantly, the reversal strategies remain, on average, profitable and significant in the period post-1994 but are not particularly distinctive, which implies that the reversal effect survives the globalization impact and indicates that the integration of equity markets together with the international correlation among markets do not synchronize the prices reversal effect around the world given that.

Further work would be recommended to study a more extended period dating back to the nineteenth century or the Victorian Era, characterised by rapid economic development in almost every domain, to verify if reversal is historically compensation for carrying risks exclusively during contraction.

My analysis takes on particular significance given the association between lagged market movement in share prices and investors’ optimism that appears among traders, generating an increasing reversal effect (Siganos and Chelley-Steley, 2006) and has direct implications for predicting and controlling trading costs associated with asset allocation strategies.

The difficulty with using the reversal strategy to uncover the long-term return reversal effects in the equity markets today resides in the fact that the globalization of the economy has fuelled the concentration of assets within institutional investors. The critical insight is that the concentration of equity in the hands of institutional investors activated international equity trading. These institutional investors seek to maximize their shareholder value from the opportunity by simultaneously dealing in many markets while constructing and holding portfolios that include assets from various countries using highly profitable investment strategies such as reversal.

To the best of the authors’ knowledge, this is the first paper to show an easily implemented contrarian strategy that switches back and forth between country indices and generates extraordinarily high abnormal returns of more than 8.86% per annum. We also show that these returns compensate for global risks and for investors ready to take them during contraction.

This chapter addresses one of the most common and long-standing problems among college students, namely depression, as well as a potential consequence of depression, suicide. A formal definition of depression is presented, and symptoms of depression are discussed. Notably, clinical depression is differentiated from “feeling down” or having “the blues.” Common measures of depression for college students are described, and the current prevalence of depression among college students is explored, along with data pertaining to trends and trajectories. Particular attention is devoted to differences in rates and severity of depression among students of various ethnicities, gender identities, disabilities and sexual orientations. Next, the chapter covers various theories about and studies on the causes and consequences of depression, as well as preventive and remedial efforts that students can engage in to minimize the adverse effects of depression. The chapter concludes with a focus on college student suicide, including its prevalence, predictors of suicidal thoughts and behaviors and prevention and treatment of college student suicide.

Artificial Intelligence (AI) is widely used in higher education teaching and learning. This trend of AI integration will continue to emerge within the education system. To stay ahead of the curve in the education realm, educators shall involve the usage of AI in teaching activities, assessments, and learning experiences. This book chapter aimed to highlight the challenges faced by higher education while proposing refined solutions to educators in involving the usage of AI tools in their teaching pedagogy. The suggested solutions were drafted from three different perspectives of AI to be integrated into its curriculum, namely the 3As triadic approach. Activities are identified as the essential asset to fostering a collaborative learning environment encouraging students to make use of cocreated AI in activities creation. Meanwhile, assessment preparation requires rigorous restrictions on AI usage to portray higher order thinking skills while abiding by ethical guidelines and legal framework. Academic content is prudent in ensuring latest findings and research are credible while bridging the gap between interactive academic materials with students' learning outcomes. Concurrently, we highlighted several approaches to achieve AI collaborative learning and enhance students' experience.

Sociologists have long thought of the integration of people in communities – social integration – and hierarchical social systems – systemic integration – as contradictory goals. What strategies allow organizations to reconcile social and systemic integration? We examine this question through 40 in-depth, longitudinal interviews with leaders of nonprofit organizations that engage in the dual pursuit of social and systemic integration. Two processes reveal how the internal structure of organizations often mirrors the ways in which organizations are embedded in their local environments. When organizations engage in loose demographic coupling, relegating those who “match” the community to the work of social integration, they produce internal inequalities and justify them by claiming community building as sacred work. When engaging in community anchoring, organizations challenge internal and external inequalities simultaneously, but this process comes with costs. Our findings contribute to a constructivist understanding of community, the mechanisms by which organizations produce inequalities, and a place-based conception of organizations as embedded in community.