درخت حوزه‌های تخصصی

The Iranian economy is intensely affected by the size of the government and oil income. Oil incomes might influence the relationship between inflation and government size since financing the budget in Iran is based to a significant degree on oil revenues. Due to the significance of government size and oil income on the price level, the oil revenue-government size-inflation nexus in Iran during the period 1991-2021 is considered. Estimation results of a Markov switching model recommend that government size incorporates a significant positive affect on inflation. Moreover, the growth of oil income is found to have a significant negative affect on the inflation. Based on the findings, it appears that there are two regimes being considered: Regime 1, which represents a high inflation regime, and Regime 2, which represents a low inflation regime. Our findings suggest that once in the low inflation regime (Regime 2), there is a moderate chance of remaining in that state. However, if initially in the high inflation regime (Regime 1), there is a higher probability of staying in that state and a lower probability of transitioning to the low inflation regime.

As we are looking for knowledge of stock future returns in portfolio optimization, we are practically faced with two principal concepts: Uncertainty and Information about variables. This paper attempts to introduce a pragmatic bi-objective investment model based on uncertainty, instead of probability space and information theory, instead of variance and other moments as a risk measure for portfolio optimization. Not only is uncertainty space expected to be more in line with investment theory, but also, applying and learning this approach seems more straightforward and practical for novice investors. The proposed model simultaneously maximizes the uncertain mean of stock returns and minimizes uncertain entropy as a measure of portfolio risk. The uncertain zigzag distribution has been used for variables to avoid the complexity of fitting distributions for data. This uncertain mean-entropy portfolio optimization (UMEPO) has been solved by three meta-heuristic methods of multi-objective optimization: NSGA-II, MOPS, and MOICA. Finally, it was observed that the optimal portfolio obtained from the proposed model has a higher return and a lower entropy as a risk measure compared to the same model in the probability space.

The integration of new technologies, although beneficial, poses significant regulatory challenges. This article emphasizes that while standardization is essential to prevent inconsistency and unpredictability, maintaining a certain degree of discretion is also necessary. Using insights from microeconomic theory and international best practices, the article categorizes regulatory challenges such as competition, conflicts of interest, job displacement, rent-seeking, security and privacy concerns, fraud, tax evasion, corruption, money laundering, and compliance with anti-terrorism measures. Several regulatory tools are identified to effectively manage these challenges. These include transparency and disclosure, collaboration and information sharing, financial incentives (grants, subsidies, and tax incentives), reducing barriers to market entry and exit, open standards and interoperability, and whistleblower protection. A survey was conducted to assess expert opinions on the gap between current regulatory practices and optimal standards for each tool. The results revealed notable discrepancies, particularly regarding barriers to market entry and exit. The results indicated that current regulations for market entry are overly restrictive compared to the optimal levels recommended. Additionally, the survey highlighted that reducing barriers to exit for large financial institutions requires greater discretionary flexibility compared to smaller firms. The results show a need for targeted regulatory adjustments based on institutional differences and systemic importance.

The history of the Central Bank in issuing securities, especially partnership bonds, began in the 1990s with the approval of development program laws. According to Article 4 of the Law on the Procedure for Issuing Cooperative Bonds, the Central Bank was in a way the custodian of the license for issuing cooperative bonds, which was subsequently transferred to the Securities and Exchange Organization with the approval of the Securities Market Law. However, Article 27 of this law exempted the Central Bank's cooperative bonds from registration with the Stock Exchange Organization. In addition, Article 91 of the Third Development Plan Law issued the first legal license for the issuance of cooperative bonds by the Central Bank for the purpose of liquidity management. The main issue of the present study is the ambiguity in the current authority of the Central Bank in issuing securities after the approval of the new Central Bank Act; Part Three, Clause "B" of Article 4 of this law granted the Central Bank the authority to "design and issue various types of financial securities," but the conflict of this authority with the requirements of the Securities Market Law has created legal challenges. Based on research conducted with library resources and using a descriptive-analytical method, the findings show that the Central Bank is exempt from registration with the Stock Exchange Organization only when issuing participation bonds, and the issuance of other securities requires compliance with the processes stipulated in the Securities Market Law.

This study investigates the impact of customer behavioral factors on digital banking decisions by integrating key constructs from the Technology Acceptance Model (TAM) with trust theory and social influence. A cross-sectional, questionnaire-based survey collected data from 550 digital banking users across major urban regions in Isfahan. The analysis utilized descriptive statistics, multiple regression, and structural equation modeling (SEM) to examine the relationships between perceived ease of use, perceived usefulness, trust, social influence, and digital banking adoption. Findings indicate that perceived usefulness and perceived ease of use are the strongest predictors of digital banking decisions, while trust and social influence also exhibit significant positive effects. Collectively, these factors explain approximately 42% of the variance in digital banking adoption, underscoring the multifaceted nature of customer decision-making in this domain. The study contributes to both theory and practice by extending the TAM framework to include relational constructs such as trust and social influence, thereby offering a more comprehensive model of digital banking adoption. Practical implications for financial institutions include the need to enhance platform usability, implement robust security measures, and leverage positive social endorsements to improve customer engagement. These insights provide a valuable roadmap for optimizing digital banking strategies in an increasingly competitive market.