درخت حوزه‌های تخصصی

Exchange rate fluctuations and economic sanctions are recognized as two key factors in Iran’s economy that can have significant impacts on the country’s financial and product markets. This study examines the effect of exchange rate changes and the intensified financial sanctions on the return of the Tehran Stock Exchange Index using the time-varying parameter vector autoregressive (TVP-VAR) method. It allows for changes in parameters over time, providing flexibility in adjusting coefficients according to changes in conditions. The variables include Tehran Stock Exchange index return, exchange rate growth and financial sanctions. The data employed covers the period from 2011 to 2023 with monthly frequency. Impulse response function of the Tehran Stock Exchange returns to financial sanctions shock and to exchange rate growth shock are illustrated in the paper in different points of time. The results suggest that the increase in exchange rate led to a decrease in stock market returns between August 2013 and November 2015 and until September 2018. Therefore, the Tehran Stock Exchange index has experienced varying and asymmetric effects from financial sanctions and exchange rate fluctuations over different time periods.

Despite the 60-year activity of the Central Bank in the field of monetary and banking policy-formulation and regulation in the country, there is no explicit statement about the legal nature of this institution in laws, regulations, and legal writings, and the laws only refer to the exclusion of general laws and regulations from this institution, except in cases of specifying the name. Considering the abrogation of this ruling and according to the Central Bank Law, it is necessary to identify the nature of the Central Bank and the rulings and effects governing it in cases of special silence and the establishment of general laws. In this research, we examined the legal nature of the Central Bank among types of public legal entities using an analytical method and a documentary method. According to the examination of the criteria of the Central Bank and its compliance with the four entities of the ministry, government institution, government company, and non-governmental public institution, we must say that although the Central Bank is similar to government companies in terms of some characteristics - especially financial and structural matters - due to the difference in the purpose of activity between these two institutions, especially after the establishment of the general policies of Article 44 of the Constitution, it is not possible to place the Central Bank under the government company with a profit-making purpose. Therefore, the closest category to the Central Bank is the same non-governmental public institution, because in both, there are basic common characteristics such as the purpose of providing public service, the existence of legal independence, including administrative, financial, and relative structural independence from the government, securing the dominant budget through the institution itself, and formation with the permission of the law. Given the conflict between the definitions of non governmental public institutions in the Civil Service Management Law and the Public Accounting Law, it is suggested that, in addition to amending the law, the Central Bank be included under the category of non governmental public institutions to remove any ambiguity. It is also better to explicitly mention the Central Bank in the laws related to judicial supervision.

This study examines the interplay between deposit insurance, central bank supervision, and banking stability, emphasizing the mediating role of moral hazard. Deposit insurance, initially designed as a safeguard to prevent bank runs and protect depositors, may paradoxically undermine financial stability if implemented without adequate supervisory mechanisms. In such contexts, the assurance of depositor protection can encourage banks to engage in excessive risk-taking behavior, thereby increasing systemic vulnerability. Using a panel dataset of 118 countries over the period 1980-2004, the study employs a random-effects logistic regression model to evaluate how deposit insurance schemes, in interaction with credit expansion to the private sector (a proxy for moral hazard), influence the likelihood of banking instability. The analysis distinguishes between two types of instability, bank runs and bank insolvencies, to capture both liquidity-driven and solvency-driven crises. The findings reveal that deposit insurance alone does not have a statistically significant effect on banking stability; however, when combined with high levels of credit growth and weak regulatory oversight, it significantly increases the probability of banking crises. Moreover, the design features of deposit insurance, such as full coverage or government-funded mechanisms, exacerbate instability when central bank supervision is weak. The study concludes that effective coordination between deposit insurance systems and central bank oversight is essential to mitigate moral hazard and promote sustainable financial stability.

This study aims to demonstrate the performance of algorithmic trading strategies compared to traditional trading methods in artificial financial markets. This research uses a hybrid model based on agent-based modeling and machine learning methods to simulate agents' behavior in an artificial financial market. This model includes two categories, traditional agents and intelligent agents. Traditional agents are divided into three groups: liquidity providers, liquidity consumers, and noise traders. Intelligent agents are trained using deep learning techniques and recurrent neural networks. Based on the developed algorithms, the agent-based model simulates both categories of traditional and trained agents in an artificial financial market. Sensitivity analysis tests were used to test the validity and reliability of the model, and the values of the fat-tailed distribution of returns, volatility clustering, autocorrelation of returns, long memory in order flow, concave price impact, and extreme price events are calculated in the model and compared with the standardized values. Historical data was used to predict stock prices, and model simulations were used to generate trading signals and update the limited order book. The results of executing the model show the ability of intelligent agents to trade in artificial financial markets compared to traditional agents.

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.

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.