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The purpose of this paper is to analyze the efficiency of Islamic banks operating in different countries, over the period 2006-2009.We applied a non-parametric approach, or a Data Envelopment Analysis (DEA), that utilizes both the constant returns to scale (CRS) and the variable returns to scale (VRS) assumptions to offer measures of the technical and scale efficiency. The outcomes reveal a considerable degree of dispersion of technical efficiency between banks within the sample of the year-to-year basis. To inspect the determinants of efficiency, we apply the panel regression analysis. In fact, we used panel regression analysis in order to explain the variation in the dependent variable (calculated efficiencies) by a set of independent variables, such as banks size, asset quality, management capability, liquidity, sensitivity to markets risks, and capitalization.We find that banks with higher liquidity and a good management capability are more likely to operate at higher levels of technical efficiency. In addition, the results show that size, seem to contribute negatively to the evolution of efficiency scores of Islamic banks operating in the world.

Purpose The purpose of this study is to investigate factors influencing the net stable funding ratio (NSFR) in the Islamic banking system. More specifically, the authors analyze the impact of the deposit structure on the liquidity ratio using the two-step generalized method of moments approach during the 2000–2014 period. Design/methodology/approach Based on IFSB-12 and the GN-6, the authors calculated the NSFR for 35 Islamic banks operating in the Middle East and North Africa (MENA) region. Findings The findings of this study show the following: first, ratio of profit-sharing investment accounts have a positive impact on the NSFR, while ratio of non profit-sharing investment accounts increase the maturity transformation risk; second, the results highlight that asset risk, bank capital and the business cycle have a positive impact on the liquidity ratio, while the returns on assets, bank size and market concentration have a negative impact; and third, these results support the IFSB’s efforts in developing guidelines for modifying the NSFR to enhance the liquidity risk management of institutions offering Islamic financial services. Research limitations/implications The most prominent limitation of this research is the availability of data. Practical implications These results will be useful for authorities and policy makers seeking to clarify the implications of adopting the liquidity requirement for banking behavior. Originality/value This study contributes to the knowledge in this area by improving our understanding of liquidity risk management during liquidity stress periods. It analyzes the modified NSFR that was adopted by the IFSB. Besides, this study fills a gap in the literature. Previous studies have used the conventional ratios to determinate the main factors of the maturity transformation risk in a full-fledged Islamic bank based on an early version of NSFR. Finally, most studies focus on the NSFR as proposed by the Basel Committee, whereas the authors investigate the case of the dual-banking system in the emerging economies of seven Arab countries in the MENA region.

Purpose The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR parametric models. Design/methodology/approach The authors test the performance of several VaR models using Kupiec and Engle and Manganelli tests at 95 and 99 per cent levels for long and short trading positions, respectively, for the period from August 10, 2006 to December 14, 2014. Findings The authors’ findings show that the VaR under Student and skewed Student distribution are preferred at a 99 per cent level VaR. However, at 95 per cent level, the VaR forecasts obtained under normal distribution are more accurate than those generated using models with fat-tailed distributions. These results suggest that VaR is a good tool for measuring market risk. The authors support the use of RiskMetrics during calm periods and the asymmetric models (Generalized Autoregressive Conditional Heteroskedastic and the Asymmetric Power ARCH model) during stressed periods. Practical implications These results will be useful to investors and risk managers operating in Islamic markets, because their success depends on the ability to forecast stock price movements. Therefore, because a few Islamic financial institutions use internal models for their capital calculations, the regulatory committee should enhance market risk disclosure. Originality/value This study contributes to the knowledge in this area by improving our understanding of market risk management for Islamic assets during the stress periods. Then, it highlights important implications regarding financial risk management. Finally, this study fills a gap in the literature, as most empirical studies dealing with evaluating VaR prediction models have focused on quantifying the model risk in the conventional market.