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This study aims to investigate the spillover between the Middle East and North Africa (MENA) stock index and several security indices, including Sukuk and conventional bond, and ultimately compare the hedge effectiveness of Sukuk and conventional bond.

The study uses VAR (1)-asymmetric Baba, Engle, Kraft and Kroner-multivariate generalized autoregressive conditional heteroskedasticity (1,1) model to analyze the volatility and shock and asymmetric shock spillover between Sukuk index and several bond indices in the MENA region including, Bond, All Bond, High Yield Bond and Bond and Sukuk and MENA stock market index and ultimately compare the hedging capabilities of Sukuk and conventional bonds by calculating the optimal portfolio weights for securities indices and stock portfolios and hedge effectiveness of security indices.

Results indicate that there is no shock, volatility and asymmetric shock spillover between the Sukuk index and MENA stock index, implying that Sukuk indices behave independently from MENA stock indices; however, there is shock and asymmetric shock spillover between MENA stock indices and security indices that include conventional bonds. The result of optimal portfolio weights and corresponding hedge effectiveness indicate that Sukuk is the most significant asset among other security indices in diversifying and hedging stock MENA portfolios. Moreover, the hedge effectiveness of Sukuk shows persistent trends during both the normal and crisis periods.

The study suggests that MENA stock market investors and investment managers should add Sukuk instead of the conventional bond to their portfolio to hedge their portfolio against investment risks during both normal and crisis periods.

Although many studies compare many aspects of Sukuk and conventional bonds, this is the first study that compares the hedge effectiveness of Sukuk and conventional bond based on the time-varying optimal portfolio weights strategy.

The purpose of this study is to investigate the correlation between the price return of leading cryptocurrencies, including Bitcoin, Ethereum, Ripple, Litecoin, Monero, Stellar, Peercoin and Dash, and stock return of technology companies' indices that mainly operate on the blockchain platform and provide financial services, including alternative finance, democratized banking, future payments and digital communities.

This study employs a Bayesian asymmetric dynamic conditional correlation multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (BADCC-MGARCH) model with skewness and heavy tails on daily sample ranging from August 11, 2015, to February 10, 2020, to investigate the dynamic correlation between price return of several cryptocurrencies and stock return of the technology companies' indices that mainly operate on the blockchain platform. Data are collected from multiple sources. For parameter estimation and model comparison, the Markov chain Monte Carlo (MCMC) algorithm is employed. Besides, based on the expected Akaike information criterion (EAIC), Bayesian information criterion (BIC), deviance information criterion (DIC) and weighted Deviance Information Criterion (wDIC), the skewed-multivariate Generalized Error Distribution (mvGED) is selected as an optimal distribution for errors. Finally, some other tests are carried out to check the robustness of the results.

The study results indicate that blockchain-based technology companies' indices' return and price return of cryptocurrencies are positively correlated for most of the sampling period. Besides, the return price of newly invented and more advanced cryptocurrencies with unique characteristics, including Monero, Ripple, Dash, Stellar and Peercoin, positively correlates with the return of stock indices of blockchain-based technology companies for more than 93% of sampling days. The results are also robust to various sensitivity analyses.

The positive correlation between the price return of cryptocurrencies and the return of stock indices of blockchain-based technology companies can be due to the investors' sentiments toward blockchain technology as both cryptocurrencies and these companies are based on blockchain technology. It could also be due to the applicability of cryptocurrencies for these companies, as the price return of more advanced and capable cryptocurrencies with unique features has a positive correlation with the return of stock indices of blockchain-based technology companies for more days compared to the other cryptocurrencies, like Bitcoin, Litecoin and Ethereum, that may be regarded more as speculative assets.

The study results may show the positive role of cryptocurrencies in improving and developing technology companies that mainly operate on the blockchain platform and provide financial services and vice versa, suggesting that managers and regulators should pay more attention to the usefulness of cryptocurrencies and blockchains. This study also has important risk management and diversification implications for investors and companies investing in cryptocurrencies and these companies' stock. Besides, blockchain-based technology companies can add cryptocurrencies to their portfolio as hedgers or diversifiers based on their strategy.

This is the first study analyzing the connection between leading cryptocurrencies and technology companies that mainly operate on the blockchain platform and provide financial services by employing the Bayesian ssymmetric DCC-MGARCH model. The results also have important implications for investors, companies, regulators and researchers for future studies.

This paper aims to investigate the impact of market structure and market share on the performance of the Islamic banks operating in the Iranian banking system based on the structure-conduct-performance (SCP) paradigm.

The Iranian Islamic banking system’s market structure is evaluated by using the econometrics method to test the validity of the traditional SCP paradigm. For this purpose, the authors estimate a simple regression model that is consisted of several independent variables, such as the market share, bank size, real gross domestic product, liquidity and Herfindahl-Hirschman index as a proxy variable for concentration and one dependent variable, namely, the profit as a proxy for performance. The panel data includes a data sample of 22 Islamic banks operating from 2006 to 2019. Data are extracted from the balance sheet of Islamic banks and the time-series database of the Central Bank of Iran and World Bank.

The study’s findings indicate that both concentration and market share have a positive impact on the performance of banks in the Iranian Islamic banking system. This result is contradicted with both traditional SCP and efficient structure hypotheses; however, it confirms the existence of oligopoly or cartel in the Iranian Islamic banking system that few banks try to gain the highest share of profit and maintain their market share by colluding with each other. This result is in contradiction with other research studies about the market structure in the Iranian banking system that claimed that banks in Iran operate under monopolistic competition. In addition, it shows that the privatization of some banks in Iran does not improve and help competition in the Iranian banking system.

This paper is a pioneer empirical study analyzing the market structure, concentration and collusion based on the SCP paradigm in Iranian Islamic banking. The results of the study support the existence of collusive behavior among the Islamic bank in Iran that is not aligned with Sharia. This study clearly shows the difference between ideal Islamic banking and Islamic banking in practice in Islamic countries. This clearly indicates that only prohibiting some operations like receiving interest, gambling and bearing excessive risk is not enough. In fact, the Islamic banking system should be based on the Sharia rule in all aspects and much more modification and study have to be done to achieve an appropriate Islamic banking system. These possible modifications to overcome the issues of cartel-like market structure and collusive behavior in the Iranian Islamic banking system include making the Iranian banking system more transparent, letting foreign banks enter the Iranian banking system and minimizing the government intervention in the Iranian banking system.

The aim of this work is to determine the average surface temperature of a conical antenna. Its cooling is ensured by means of a nanofluid-saturated porous structure. The volume fraction of the H₂O–Cu nanofluid ranges between 0% (pure water) and 5%, whereas the ratio between the thermal conductivity of the used porous materials and that of water (fluid base) varies in the wide 4–41.2 range. The antenna is contained in a coaxial conical closed cavity with a variable distance between the cones, leading to an aspect ratio varying between 0.2 and 0.6. The axis of the assembly is also inclined with respect to the gravity field by an angle varying between 0° (a vertical axis with top of the cone oriented upwards) and 180° (a vertical axis with top of the cone oriented downwards).

Simulations have been done by means of the volume control method based on the SIMPLE algorithm.

Results of the numerical approach show that the cavity’s aspect ratio and inclination with respect to the gravity field significantly affect the thermal behavior of the active cone. Otherwise, the work confirms that the Maxwell and Brinkman models used to determine the nanofluid’s effective thermal conductivity and viscosity, respectively, are adapted to the considered assembly.

A new correlation is proposed, allowing the determination of the average surface temperature of the active cone and its correct thermal sizing. This correlation could be used in various engineering fields, including electronics, examined in the present study.