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Participatory contracts reflect the true spirit of Islamic finance. However, these contracts face several challenges during their implementation. This is reflected by the low volume of contracts processed by Islamic banks and the low number of Sukuk issued. This study aims to introduce a new parameter related to the valuation of Sukuk Musharakah when the underlying asset is a joint venture.

The author applies the Gordon & Shapiro model on the valuation of Sukuk Musharakah with a joint venture as underlying. A new pricing framework is introduced with several usual parameters such as the profit and loss sharing ratio, besides a new parameter, which is the dividend payout ratio. The framework shall contain price, duration and convexity computation. The new framework differs from the classic bond pricing methodology broadly used nowadays in determination of Sukuk prices.

The results indicate that negotiating only the profit and loss sharing ratio is not sufficient to have a fair price of Sukuk Musharakah when the underlying is a joint venture. It is due to the mismatch of interest between investors and issuers. Thus, another parameter should be negotiated which is the dividend payout ratio.

The research focuses exclusively on Sukuk Musharakah with joint venture as underlying. Also, the choice of Gordon & Shapiro formula, by definition of the model, restricts the calculation of the net asset value by using only the future expected dividends with constant growth. This choice is made primarily to explain the objective of this paper in a simple way.

For investors, a compatible pricing framework with the underlying flows and risks of an asset is essential to create a liquid market. This work would help investors to boost the Sukuk Musharakah market.

Several studies have analyzed the various challenges in Sukuk markets. Few of them dealt with specificities of Sukuk Musharakah by focusing on the underlying nature. So far, the profit and loss sharing ratio is the only parameter analyzed in these studies. Thus, the authors contribute to the literature by studying other parameters that can solve the various challenges of Sukuk Markets.

The displaced commercial risk is one of the specific risks in the Islamic finance that creates a serious debate among practitioners and researchers about its management. The purpose of this paper is to assess a new approach to manage this risk using machine learning algorithms.

To attempt this purpose, the authors use several machine learning algorithms applied to a set of financial data related to banks from different regions and consider the deposit variation intensity as an indicator.

Results show acceptable prediction accuracy. The model could be used to optimize the prudential reserves for banks and the incomes distributed to depositors.

However, the model uses several variables as proxies since data are not available for some specific indicators, such as the profit equalization reserves and the investment risk reserves.

Previous studies have analyzed the origin and impact of DCR. To the best of authors’ knowledge, none of them has provided an ex ante management tool for this risk. Furthermore, the authors suggest the use of a new approach based on machine learning algorithms.

This study aims to provide an interest-free valuation methodology for Murabaha and Musharakah Moutanaquissah contracts. Indeed, In Islamic finance, Murabaha contracts are widely negotiated. Their yield depends mainly on the contracted profit margin. In the current practices, this latter is based on a reference interest rate, which is highly criticized in Islamic literature, just like Musharakah Moutanaquissah contracts. In this perspective, authors suggest a new valuation methodology with parameters related to the real economy.

The authors apply an indirect method to determine a lower bound of the profit margin of a Murabaha contract. Considering Musharakah Moutanaquissah as an equivalent contract, the new valuation methodology is based on participation and focuses on parameters from the real economy: the market rent and the rate of return used for an equivalent project.

The results show that the pricing of Musharakah Moutanaquissah contracts could be based on several parameters linked to the real economy. Consequently, an implied value of the profit margin could be computed. Also, the interest rate is no longer implicated in the pricing of neither Murabaha nor Musharakah Moutanaquissah contracts.

The valuation methodology is applicable only if the underlying asset’s financing can be made with Murabaha and Musharakah Moutanaquissah contracts.

This work will restore the link between Islamic contracts and the real economy. For Islamic banks in particular, the suggested model would reduce the exposure to reputational risk and enhance the compliance to the Sharia (Islamic Law).

Several studies have analyzed the dependence between Islamic contracts and interest rates. In general, these studies confirm this dependence and few of them have suggested alternatives. Thus, the authors contribute to the literature by providing a practical and applicable model to detach the valuation of Murabaha and Musharakah Moutanaquissah from the interest rate.

The purpose of this paper is to provide an improved genetic algorithm to solve 0/1 multidimensional knapsack problem (0/1 MKP), by proposing new selection and crossover operators that cooperate to explore the search space.

The authors first present a new sexual selection strategy that significantly improves the one proposed by (Varnamkhasti and Lee, 2012), while working in phenotype space. Then they propose two variants of the two-stage recombination operator of (Aghezzaf and Naimi, 2009), while they adapt the latter in the context of 0/1 MKP. The authors evaluate the efficiency of both proposed operators on a large set of 0/1 MKP benchmark instances. The obtained results are compared against that of conventional selection and crossover operators, in terms of solution quality and computing time.

The paper shows that the proposed selection respects the two major factors of any metaheuristic: exploration and exploitation aspects. Furthermore, the first variant of the two-stage recombination operator pushes the search space towards exploitation, while the second variant increases the genetic diversity. The paper then demonstrates that the improved genetic algorithm combining the two proposed operators is a competitive method for solving the 0/1 MKP.

Although only 0/1 MKP standard instances were tested in the empirical experiments in this paper, the improved genetic algorithm can be used as a powerful tool to solve many real-world applications of 0/1 MKP, as the latter models several industrial and investment issues. Moreover, the proposed selection and crossover operators can be incorporated into other bio-inspired algorithms to improve their performance. Furthermore, the two proposed operators can be adapted to solve other binary combinatorial optimization problems.

This research study provides an effective solution for a well-known non-deterministic polynomial-time (NP)-hard combinatorial optimization problem; that is 0/1 MKP, by tackling it with an improved genetic algorithm. The proposed evolutionary mechanism is based on two new genetic operators. The first proposed operator is a new and deeply different variant of the so-called sexual selection that has been rarely addressed in the literature. The second proposed operator is an adaptation of the two-stage recombination operator in the 0/1 MKP context. This adaptation results in two variants of the two-stage recombination operator that aim to improve the quality of encountered solutions, while taking advantage of the sexual selection criteria to prevent the classical issue of genetic algorithm that is premature convergence.