درخت حوزه‌های تخصصی

Corporate Governance debates raised seriously in scandals and financial crisis of recent decades in large companies and banks. The focus of this debate is not merely the corporate governance system, and its main function is to preserve the interests of stakeholders. At the macro level, economic efficiency, sustainable growth and financial stability are important effects of the system. Establishing an efficient corporate governance system in the banking system and evaluating and ranking them requires a comprehensive model that encompasses all the internal and external mechanisms affecting corporate governance and localized indices and relevant international principles. In this research, corporate governance in banks has been evaluated via a model developed in the framework of systematic thinking which includes three dimensions 1) Inputs (structures and inputs), 2) Roles and processes, and 3) Outputs (goals, performance and results of them). The main objectives of this study are to evaluate the compliance status of 27 banks with the indicators of corporate governance model and their efficiency and effectiveness, as well as to examine the correlation between the components of corporate governance within the system including inputs, processes and outputs. According to the results, 47.8% of the qualitative indicators are covered in the current situation of the banks of the country, but there is a significant gap between the full compliance with the model. Based on the results in the performance sector, private banks scored the highest and state banks scored the lowest. The results of evaluating the correlation between the components of corporate governance model showed that there is a positive and significant relationship between the dimensions of inputs and processes with the goals, results and performance of banks. Accordingly, by improving the status of input indicators and the corporate governance model process, the status of target indicators, results and performance of banks will also improve

The Central Bank of Iran banned online currency trading through Forex brokers in November 2016. However, some Iranian speculators still trade in the online Forex market. Is this prohibition on Forex trading reasonable? According to reports, the majority of Forex day traders fail and leave the market within six months to a year. Some scholars attribute this failure to the changeable characteristics of the losing traders, including low startup capital, failure to manage risk, lack of discipline, and impatience. The purpose of this study was to explore why the majority of traders fail and to investigate the relationship between the Forex market features and the risk of failure. We developed a previous model to address this issue. Given the Forex market is a zero-sum game; the break-even point of the representative player was formulated. The model and simulation results indicated that the expected likelihood of loss is directly related to market features such as leverage, volatility, and the frequency of trading. The minimum rate of expected return, high volatile days, and spread were the other factors affecting the risk of loss. In conclusion, the study confirms the extremely high level of risk in Forex trading, which is inappropriate for the majority of individual investors. Moreover, policymakers need to consider the high risk of loss in this market, and some appropriate regulations seem reasonable on the Forex trading.

The present study suggests a model for predicting liquidity gap, based on source and cost of funds approach concerning the daily time series data (25 March 2009 to 19 March 2018), in order to control and manage the liquidity risk. Using the family of autoregressive conditional heteroscedasticity models, the behavior of bank liquidity gap is modeled and predicted. The results show that the APGARCH with the Johnson-SU distribution is the most suitable model for explaining the liquidity gap behavior. Based on the rolling window method the more accurate model has been selected to be the APGARCH model with T-Student distribution which provides the least error in forecasting liquidity gap.