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This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

This research examines the impact of the COVID-19 pandemic and governance structure on corporate narrative reporting (CNR) concerning Industry 4.0 (I4.0) technologies in Jordanian commercial banks. The study aims to explore how these factors influence the extent and nature of disclosures in annual reports.

The study uses a comprehensive manual content analysis method to investigate the annual reports from all 15 Jordanian commercial banks from 2010 to 2022. This approach allows for the detailed examination of I4.0 disclosures, using a specially developed index to measure various disclosure dimensions. An ordinary least squares model is used to assess the determinants of CNR on I4.0, considering factors such as the pandemic’s impact and various governance attributes.

The findings indicate that both the COVID-19 pandemic and specific governance factors (e.g. board size and audit committee size) significantly enhance the disclosure of I4.0 technologies. The study reveals that during the pandemic, banks significantly increased their level of detailed disclosures about I4.0 strategies, challenges and benefits, reflecting a strategic response to the pandemic’s disruption.

This study introduces a novel I4.0 Reporting Index for banks, measuring disclosures across strategy implementation, business model transformation, challenges and benefits. It adds to the existing literature by offering insights into narrative reporting practices concerning I4.0 technologies within the banking sector and illuminates the impact of the COVID-19 pandemic on these practices.

Given the competitiveness of the business environment globally, environmental, social and governance (ESG), which represents a sustainable development framework that integrates environmental, social and corporate governance factors, has become an increasingly recognized concept in emerging markets. In the case of Ghana, its implementation is influenced by several factors, including leadership.

Drawing on the resource-based view theory, higher-order theory and stakeholder theory, we developed and evaluated a serial mediation model to explain how ESG performance and corporate reputation can connect transformational leadership to enhance competitive advantage. Utilizing the Process Macro model 6 in SPSS, data were collected from 340 senior managers/executives and middle-level managers from European multinational firms operating in Ghana.

The results indicate that transformational leadership positively affects ESG performance. Enhanced ESG performance, in turn, leads to improved corporate reputation, which subsequently results in a stronger competitive advantage.

This study is limited to European multinational firms operating in Ghana, which may restrict the generalizability of the findings to other contexts or regions.

The findings suggest that organizations aiming to strengthen their competitive advantage should prioritize transformational leadership practices that foster ESG initiatives, as these are critical drivers of corporate reputation and market positioning.

This study provides new insights into the interwovenness between ESG performance and leadership in enhancing corporate reputation and competitive advantage within the context of emerging markets.

This study examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.

A balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.

The findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.

The use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.

The current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.

To the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.