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This study presents a hybrid multicriteria decision-making approach for evaluating stocks in the Saudi Stock Market. The objective is to provide investors and stakeholders with a robust evaluation methodology to inform their investment decisions. With a market value of USD 2.89 trillion dollars in September 2022, the Saudi Stock Market is of significant importance for the country's economy. However, navigating the complexities of stock market performance poses investment challenges. This study employs the best–worst method and the technique for order preference by similarity to identify an ideal solution to address these challenges. Utilizing data from the Saudi Stock Market (Tadawul), this study evaluates stock performance based on financial criteria, including return on equity, return on assets, net profit margin, and asset turnover. The findings reveal valuable insights, particularly in the banking sector, which exhibited the highest net profit margin ratios among sectors. The hybrid multicriteria decision-making-based approach enhances investment decisions. This research provides a foundation for future investigations, facilitating a deeper exploration and analysis of additional aspects of the Saudi Stock Market's performance. The developed methodology and findings have implications for investors and stakeholders, aiding their investment decisions and maximizing returns. [ABSTRACT FROM AUTHOR]

This article offers a conceptual framework for developing the Sharīʿah-Compliant Asset Pricing Model (SCAPM) using the Maqāṣid al-Sharīʿah and Islamic Wealth Management (IWM). This article also provides a new perspective on finding Islamic financial benchmarks as an alternative to conventional financial benchmarks in the Islamic finance industry. This research was conducted using a qualitative research method with deep reference to published journal articles and books in the fields of Maqāṣid al-Sharīʿah, Islamic Wealth Management, and asset pricing model. As a measure of the expected minimum rate of return in an asset pricing model, this article proposes the fulfilment of basic necessities (ḍarūriyyāt) and zakāt rate as proxy for investors' required rate of return. This study acknowledges both systematic and non-systematic risk's effects on asset pricing. [ABSTRACT FROM AUTHOR]

Purpose - Today, due to the breadth, diversity and multiplicity of investment projects, decision makers and investors are faced with the issue of choosing the most profitable project. The economic rate of return (ERR) index is one of the proper indices that has been presented to determine the profitability of the projects. However, the ERR index has important shortcomings that have led to serious limitations in its use. In this regard, this paper introduces a new measure called the reliable economic rate of return (RERR), which has originated from ERR measure, but it has resolved the drawbacks of ERR index. On the other hand, this paper proposes a new solution by considering the values of the cash flow in terms of fuzzy numbers. After calculating the fuzzy economic rate of return, the profitability potentiality degree of the investment projects can be determined as well as their reliability based on the net present value (NPV) method. Design/methodology/approach - This paper proves that if we equate the initial cash flow of investment projects with the sum of the negative values of the relevant cash flow stream, then the RERR value would be greater than '-1'. In this regard, this paper proposes a solution to modify the initial and final values of the investment cash flow stream, merely without changing middle values. Thereby, the NPV of the modified cash flow does not change. On the other hand, it is sometimes difficult to estimate the values of cash flows as a crisp number, which may lead to a wrong decision in accepting or rejecting projects. For this purpose, this paper considers the values of cash flow stream as fuzzy numbers and describes a solution for calculating the fuzzy RERR using the α-cut method and the RERR index. The proposed solution is compatible with the NPV method and also has fewer calculations than the other methods. This paper also proposes a method that calculates the profitability potentiality degree of projects and provides more comprehensive information to the decision makers by examining the intervals obtained from cutting the fuzzy values of the projects and presenting a new and reliable solution. Findings - Using the @RISK software, it was found that the estimation of fuzzy return rate using RERR index and α-cut method is very close to the simulation result. It confirms the appropriate accuracy of the proposed solution. Also, the results obtained from the software in determining the profitability of projects indicated that the proposed solution is more accurate than the methods of 'comparison of the expected intervals' and 'strict exceedance possibility'. It is also fully compatible with the NPV method. Research limitations/implications - In this research the market rate is assumed constant, while, in practice it can vary over the periods. Defining the market rate as an inconstant parameter, using the robust optimization approach and investigating the subject of this paper under other uncertainty environments are future study suggestions to both researchers and practitioners. Practical implications - One of the most important applications of this study is in risky projects wherein estimating the values of cash flow stream as a crisp number is difficult. The results of this paper help decision makers in reducing risk and determining the project profitability. It is worth mentioning that the solution proposed in this paper can be used for all projects with any cash flow stream value. Social implications - Failure to make the correct decision regarding the acceptance or rejection of the projects could have major negative consequences for the companies, organizations and even society. This paper helps decision makers, investors and organizations to determine the projects profitability that could benefit organizations and society. Originality/value - This paper proposes the RERR measure as a profitability index such with several favorable properties: (ⅰ) it exists and is unique, (ⅱ) it is NPV-consistent in accepting/rejecting decisions, (ⅲ) it provides values greater than '-1', (ⅳ) it takes into account all of the project's outflows which may be regarded by some practitioners as an appropriate indicator of the overall investment. Furthermore, this paper proposes an appropriate method for calculating the fuzzy RERR and a new method for determining the profitability potentiality degree of the investment projects based on the NPV method. [ABSTRACT FROM AUTHOR]

Renewable energy technologies play a crucial role in solving global energy and environmental issues, and the pace of the energy transition directly depends on improving their efficiency. Presently, the development and implementation of renewable energy systems are ensured mainly through state funding, the possibilities of which are limited. The potential of attracting private investments depends directly on their impact on companies' profitability indicators, and the uncertainty regarding the return on investments is one of the main barriers affecting investors' decision-making. Based on a vector autoregressive model for analysing the stationary time series, the paper explores the impact of long-term investments and research and development costs in renewable energy technologies on the financial performance of ten of the largest companies operating in this field. The study's results showed that investments and spending on research and development positively affect such companies' profitability indicators as earnings before interest, taxes, depreciation and amortisation, earnings before interest and tax, net income, and return on investment. The obtained results can be used to substantiate the economic effectiveness of investments in developing and improving renewable energy technologies when forming the companies' financial policies to support them. [ABSTRACT FROM AUTHOR]

In 2014, FERC adopted a new theory of capital markets for the purpose of setting authorized returns-on-equity: that all observed dividends and interest rates were anomalous and therefore unreliable indicators of the returns necessary for investors to hold the stocks and bonds of transmission owners. The new theory, used to justify higher authorized ROEs, rejected evidence of fundamental conditions in capital markets and explicitly adopted arguments by investor-owned utilities regarding unreliable markets. After a judicial remand, FERC abandoned the new theory, but consumers in New England and the Midwest were arbitrarily charged hundreds of millions of dollars over several years due to unjust and unreasonable rates for transmission service. [ABSTRACT FROM AUTHOR]

In the traditional portfolio models, the return rates of risky assets are usually defined as random variables or fuzzy variables. However, when some events such as financial crises or wars occur that can cause instability in financial markets, the results of these assumptions are not always satisfactory. Therefore, some scholars try to use uncertain variables to express the return rates. In this paper, a two-factor uncertain portfolio problem under optimistic value criteria is studied, where we use the optimistic value instead of expected value to describe the investment return and study the impact of economic circumstance factor and corporation's specificity factor on the return rates. Firstly, a two-factor optimistic value-variance-entropy model with background risk is constructed, in which the total investment return consists of the risky asset return and the background asset return. Then, considering the investors with two kinds of risk preferences, a three-step method is applied to convert the bi-objective optimization model. Moreover, a moment estimation method is used to process the expert-estimated data on the return rates. Finally, a numerical simulation is presented for showing the applicability of our models and solution method. • We use optimistic value to represent the return rather than expected value. • The multiple factors and background risk are considered simultaneously. • Three-step method is used to convert the model into two single-objective models. [ABSTRACT FROM AUTHOR]

With the development of financial market, people invest their savings into different financial products to increase return. However, financial market is an extremely complex system, where investment opportunities and risk often coexist. For investors, it is necessary to take effective measures to avoid risk while obtaining considerable return. In recent decades, actively managing investment in the form of a portfolio is widely accepted by investors. In this paper, we propose a new three-objective Sortino ratio-expected shortfall-turnover rate (SR-ES-TR) portfolio optimization (PO) model. The Sortino ratio is used to measure the risk-adjusted rate of return. The expected shortfall is used to measure the tail risk of a portfolio. Portfolio liquidity risk is characterized by turnover rate. We constructed a portfolio of ten stocks and solved the SR-ES-TR model by the novel MOPSO-SODE algorithm. Compared with other four multi-objective algorithms, the better performance and validity in solving SR-ES-TR model by MOPSO-SODE algorithm have been verified. • Established a three-objective SR-ES-TR portfolio optimization model with liquidity ratio. • Designed a MOPSO-SODE algorithm based on the MOPSO framework. • Verified the effectiveness of the MOPSO-SODE algorithm in solving SR-ES-TR model. [ABSTRACT FROM AUTHOR]

• A cloud theory-based multi-objective portfolio selection model is proposed. • The crisp numerical characteristics of the cloud model theory are defined. • The acceptance and rejection functions with variable risk appetite are constructed. • A compromise programming approach is utilized to aggregate the objectives. • Several schemes as per investors' preferences regarding all objectives are devised. This study proposes a cloud theory-based multi-objective portfolio selection model with variable risk appetite, which incorporates four objectives of mean, variance, skewness, and liquidity constrained by several realistic constraints. Cloud model theory is employed to characterize the return rates and liquidity of assets due to the superiority of simultaneously capturing the ambiguity and randomness of information. The crisp numerical characteristics of the cloud model are defined to obtain the crisp form of the proposed model. To highlight and portray the investors' risk (averse-neutral-seeking) appetites, the generalized acceptance and rejection functions are modeled by using the extreme values of each objective and introducing a variable risk appetite parameter. Thus the corresponding model is transformed with the objective functions of maximizing acceptance and minimizing rejection, which is solved through the compromise programming approach. The extended model provides investors with an opportunity to adjust risk parameters according to current market status. Moreover, the preference ratio vector is introduced when optimizing, which provides investors with overall control over the preferences regarding all objectives, so that investors can derive optimal portfolios well compatible with their expectations through customized weighting schemes. A real-world empirical application is presented to demonstrate the effectiveness of the proposed model [ABSTRACT FROM AUTHOR]