Xiao Ling Ding, Razali Haron and Aznan Hasan
This study aims to determine how Basel III capital requirements affect the stability of Islamic banks globally during the global financial crisis and the COVID-19 pandemic.
Abstract
Purpose
This study aims to determine how Basel III capital requirements affect the stability of Islamic banks globally during the global financial crisis and the COVID-19 pandemic.
Design/methodology/approach
The secondary data for all Islamic banks worldwide from 2004 to 2021 is obtained from the FitchConnect database. The main technique was a two-step generalized method of moment (GMM) system, and the data were tested using pooled ordinary least squares, fixed effects and difference GMM models for robustness checks.
Findings
Regression results support the moral hazard hypothesis based on evidence that both the total capital ratio and the Tier 1 capital ratio have a statistically significant positive impact on the stability of Islamic banks globally. Furthermore, neither the global financial crisis of 2008–2009 nor COVID-19 (2020–2021) significantly impacted the stability of Islamic banks worldwide. The results are robust across alternative measures of stability, capital buffers, dummy variables and estimation techniques. According to the descriptive statistics, the number of Islamic banks that disclose their regulatory capital ratios to the public has increased over the study period, and the mean of total capital and Tier 1 ratios are considerably greater than what is required by Basel II and Basel III.
Research limitations/implications
Bankers, regulators and policymakers should benefit from the evidence on capital and risk management in Islamic banking according to Basel Committee on Banking Supervision (BCBS) and Islamic financial services board (IFSB) international standards in various jurisdictions.
Originality/value
This research builds on earlier studies that were both beneficial and instructive by exploring the relationship between BCBS and IFSB capital guidelines and the trustworthiness of Islamic banks in greater depth. This study uses numerous capital ratios, buffers and stability measures to provide an international context for research on Islamic banking. In addition, the database is up-to-date to include information about the COVID-19 pandemic aftereffects in the year 2021. This study also introduces the Basel membership of Islamic banks to provide context for countries still at the Basel II stage or are yet to begin implementing the Basel III international standard.
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Faisal, Aroosa Ramzan, Moeed Ahmad and Waseem Abbas
This study aims to develop a neurocomputational approach using the Levenberg–Marquardt artificial neural network (LM-ANN) to analyze flow and heat transfer characteristics in…
Abstract
Purpose
This study aims to develop a neurocomputational approach using the Levenberg–Marquardt artificial neural network (LM-ANN) to analyze flow and heat transfer characteristics in mixed convection involving radiative magnetohydrodynamic hybrid nanofluids. The focus is on the influence of morphological nanolayers at the fluid–nanoparticle interface, which significantly impacts coupled heat and mass transfer processes.
Design/methodology/approach
This research simplifies a complex system of higher-order nonlinear coupled partial differential equations governing the flow between orthogonal coaxially porous disks into ordinary differential equations via similarity transformations. These equations are solved using the shooting method, and parametric studies are conducted to observe the impact of varying important parameters. The resulting data sets are used to train, validate and test the LM-ANN model, which ensures high predictive accuracy. Machine learning and curve-fitting techniques further enhance the model’s capability to generate detailed visualizations.
Findings
The findings of this study indicate that increased nanolayer thickness (0.4–1.6) significantly improves thermal performance, while changes in the chemical reaction parameter (0.2–1) have a notable effect on enhancing the Sherwood number. These results highlight the critical role of morphological nanolayers in optimizing thermal and mass transfer efficiency in MHD nanofluids.
Originality/value
This research provides a novel neurocomputational framework for understanding the thermal and mass transfer dynamics in MHD nanofluids by incorporating the effects of interfacial nanolayers, an aspect often overlooked in conventional studies. The use of LM-ANN trained on computational data sets enables high-fidelity predictive analysis, offering new insights into the enhancement of thermal and mass transfer efficiency in hybrid nanofluid systems.
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Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed
Syed Ali Raza, Darakhshan Syed, Syed Rizwan and Maiyra Ahmed