درخت حوزه‌های تخصصی

In financial markets, a primary concern for investors is achieving enhanced returns while effectively managing portfolio risk. Leveraged trading is one potential strategy for increasing returns; however, the fundamental question is to find the optimal degree of leverage that yields the most efficient investment portfolio. This paper investigates the optimal leverage level of cryptocurrency futures within a diversified portfolio comprising digital assets, employing a constrained mean semi-variance model and the Invasive Weed Optimization (IWO) algorithm. The dataset, sourced from Coin Market Cap, consists of daily returns for 10 cryptocurrencies and 5 futures contracts over the period from 2022 to 2025. The proposed model incorporates allocation constraints, wherein each asset in the portfolio is subject to upper and lower bounds on its weight. Due to the imposed constraints, the problem is not solvable via traditional quadratic programming techniques, necessitating the application of the IWO algorithm as the optimization method. Empirical results reveal that incorporating futures into a cryptocurrency portfolio does not inherently enhance its performance. While leverage may increase expected returns, it simultaneously elevates portfolio risk. Consequently, based on the Sortino ratio, the overall risk-adjusted performance of the portfolio does not necessarily improve with the use of leveraged futures.

The development of the nation’s economy is supported by the growing diversity and enthusiasm of interest among academics, particularly in the transforming procedures with an entrepreneurial orientation. The study investigates changing entrepreneurial-oriented practices and the performance of SMEs utilizing a cross-sectional survey amongst the four top grocery registered SMEs operating in Ikorodu local government division of Lagos State, Nigeria. The tool for gathering data is a questionnaire with two sections: bio-data and research questions. While 100 respondents formed the sample size proportionally selected from the study focus. Pearson correlation is the statistical tool for data analysis. The study reveals that creativeness and alleviation of business loss have a highly significant impact on SMEs performance; with pro-activeness having a weak, but positive relevance on SMEs performance. In conclusion, to further improve and optimize entrepreneurial orientation practices and adapt to future threatening changes, firms need to strengthen the desire for healthy competition, identifying and targeting the weaknesses of their competitors. It is recommended that more innovativeness should be sought after as guiding principles for capability and adaptability to handle the complexity of the ever-changing business surrounding, while involvement in risk-taking should be adopted with inevitable zeal and willingness to attain organizational growth and improved performance. Pro-activeness should be given adequate consideration to maintain and surpass existing performance as opportunities come but once. Despite study limitations, future researchers may need to enlarge the sample size and create awareness of research conducted on SMEs generally. Keywords: Change, Entrepreneurial orientation, Performance, Practices, SMEs.

Abstract By regulating the general policies of Article 44 of the Constitution law, downstream oil and gas industries were handed over to the private sector. Bunkering industry or supplying fuel to the ships is identified as one of the downstream industries of oil and gas. Despite having opportunities, such as abundant sources of high-quality fuel, Iran has not been able to play a key role in bunkering industry in the Persian Gulf. Notwithstanding the emphasis of the laws on supporting the private sector, many of the policies have problems in implementation. Expanding the activity of the private sector by analyzing the necessity of creating an independent regulatory body, that will follow single governance at the same time as removing government monopolies is the main goal of this research. The findings of the research show that the bunkering value chain is still under the control of the government, and regulation in the bunkering industry should be done with an integrated and supportive approach with the participation of organizations related to this industry and private sector activists.

Although previous research has examined the application of artificial intelligence (AI) across various areas of finance, there remains limited empirical evidence regarding its impact on corporate financial asset allocation. This gap is particularly evident when considering the organisational capabilities that enable firms to utilise AI technologies effectively. In the rapidly evolving technological landscape, artificial intelligence (AI) has emerged as a pivotal force driving innovation and transformation within corporate financial management. By embedding AI into organisational processes, companies have fundamentally reshaped their financial decision-making frameworks. However, the exact mechanisms through which AI adoption shapes the allocation of financial assets are still not fully understood. This study examines how artificial intelligence (AI) technologies influence the allocation of financial assets within corporations, with a specific focus on the moderating influence of three dynamic organisational capabilities: absorptive capacity, innovation capability, and adaptability. Based on panel data collected from companies listed on the Tehran Stock Exchange between 2020 and 2024, AI adoption is measured through textual analysis of management commentary reports obtained from the Codal system. The dependent variable comprises a set of financial ratios, including the proportion of financial assets relative to a firm’s total assets. The analysis employs multiple regression models with interaction terms to test the proposed hypotheses. Findings indicate that the adoption of AI substantially enhances the effectiveness of distributing financial assets. Moreover, absorptive capacity and innovation capability strengthen the association between AI adoption and the allocation of financial assets within firms' performance, while adaptability shows no statistically significant moderating effect. These results highlight the importance of both technological infrastructure and internal capabilities for leveraging advanced technologies to their fullest potential. This research not only enriches the academic discourse with fresh empirical insights but also offers valuable implications for financial managers, capital market regulators, and policymakers engaged in organisational digital transformation strategies.

This study investigates the role of economic factors such as total annual water withdrawal, total renewable energy consumption, total greenhouse gas emissions, and waste generation in shaping the trajectory of the circular economy. Utilizing a nonlinear multilevel regression model with combined fixed and random effects, the research examines the impact of these variables on the circular economy index in Iran over the period 1993 to 2023. The choice of this model is justified by its ability to incorporate both fixed effects (such as average variable levels) and random effects (to account for unobserved heterogeneity across observations or units). The results indicate that among the factors influencing the circular economy, renewable energy consumption has a positive and statistically significant effect on circular economy index, with a coefficient of 0.004. In other words, higher renewable energy consumption is associated with improvements in the circular economy index, underscoring the positive role of clean and renewable energy in promoting sustainable economic development. Conversely, water withdrawal, greenhouse gas emissions, and waste generation negatively impact the circular economy, with coefficients of -0.091, -0.02, and -0.003, respectively. This implies that increased unsustainable resource use (such as water extraction), higher greenhouse gas emissions, and greater waste generation hinder the development of a circular economy. Strategic and targeted investment in water-efficient technologies, renewable energy development, greenhouse gas mitigation, and comprehensive waste management can serve as fundamental pillars for advancing the circular economy.