Financial Integration, ESG, and Credit Risk in Islamic and Financial Integration, ESG, and Credit Risk in Islamic and Conventional Systems: Evidence from Global Markets and MENA Conventional Systems: Evidence from Global Markets and MENA Banking

Abstract

While Islamic and conventional stock markets are experiencing significant global growth, the extent of their integration remains uncertain. This study investigates the dependence structure and co-movement between Islamic and conventional Dow Jones indexes across varying market conditions (bullish, normal, and bearish). Using daily data from 2015 to 2025, we employ Quantile-on-Quantile Regression (QQR) bolstered by the Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) method to capture nonlinear, asymmetric dependencies that standard models overlook. Our results reveal significant regime-dependency: integration strengthens during bullish markets, with coefficients rising from 0.92 to 1.11, compared to 0.86 0.91 in bearish markets. While Asia-Pacific and U.S. Islamic indexes exhibit partial decoupling at lower quantiles (0.81–0.89), European and global markets show coefficients exceeding unity (1.03–1.10), signaling intensified shock transmission. The QQKRLS method confirms that integration is most volatile during positive market conditions, where tail-dependence coefficients reach 1.30. These findings provide critical insights for policymakers and investors regarding the limitations of diversification strategies. Keywords: Islamic Finance, Quantile-on-Quantile Regression, Financial Integration, Dow Jones Indexes, Nonlinear Dependence.

Environmental, Social, and Governance (ESG) considerations have grown in the banking sector and regulators. This study investigates the impact of ESG performance on banks' non-performing loans (NPLs) in Gulf Cooperation Council (GCC) countries (Saudi Arabia, UAE, Kuwait, Qatar, Bahrain, Oman) and MENA countries (Morocco, Egypt, and Tunisia). We use System GMM and Difference GMM estimators to measure the persistence of non-performing loans (NPLs) endogeneity and unobserved heterogeneity. Using a dynamic panel data method from 2010 to 2023. Our results indicate that ESG performance reduces the NPL ratio across all model specifications (one- and two-lag structures). ESG performance reduces the NPLs by (- 0.000273) in Difference GMM and by (- 0.000810) in System GMM. This indicates improving loan quality and reducing credit risk. The results show a positive correlation between institutional quality and non-performing loans (NPLs) in both models. This indicates that countries with strong governance frameworks have a more rigorous approach to identifying problem loans and a higher level of transparency. Overall, these results indicate that ESG improves bank risk management by improving governance, effective screening, and monitoring practices. Keywords: ESG performance, Non-performing loans (NPLs), sector of banking, Credit risk, GCC and MENA countries, System GMM, and Difference GMM.