درخت حوزه‌های تخصصی

A healthy and profitable banking system can better withstand economic shocks and play a more effective role in the sustainability and stability of the financial system. The creation of this type of banking system is possible when all financial institutions operating in a country's money market are sound institutions and have appropriate financial indicators. The experience of the recent financial crisis and the devastating effects of transition the crisis from the monetary sector to the real sector of the economy have shown that it is necessary to pay more attention to the issue of banking health. Therefore, the main purpose of this article was to investigate the factors affecting the asset quality ratio of the country's banking system, as one of the main indicators of banking system soundness with the emphasis on business cycles, macroeconomic variables and banking variables in the time period between the years 2001 to 2018. The statistical population in the study was 29 banks operating in Iran. In this research, the dynamic panel model, system Generalized Method of Moments (GMM) has been used to achieve the desired goals. The results show that business cycles have a significant negative correlation with the quality of assets in the banking system. Also, all macroeconomic and banking variables have a significant correlation with the ratio of asset quality in the banking system.

The purpose of this study is to identify the effect of stock tendency to deal with fluctuations and price fluctuation thresholds in creating fluctuations. The statistical population of the present study is the companies listed on the Tehran Stock Exchange that were present in the stock exchange during the years 2005 to 2018. In order to confirm and reject the research hypothesis, Eviews software has been used. In Tehran Stock Exchange, following severe stock price fluctuations, the stock price fluctuation mechanism is used to limit severe stock price fluctuations, and according to certain periods, the range of stock price fluctuations changes and over time the range of fluctuations increases. The basis of trial and error has been determined and in a short period of time there have been many changes in the procedures related to the application of stock price fluctuations, without really measuring the impact of these decisions in the market and investors' reaction to changes in price fluctuations. Findings showed that the number of times each share hits the price fluctuation Yield fluctuation has a significant effect.slow efficiency fluctuations have a significant effect; And in line with the concepts of hyper-reactive theory, it can be justified, that is, after the price reaches the range of fluctuation, the trend reverses and the basis of the fluctuation limit changes; It has changed the volatility of stock returns based on jump and price continuity.

The economic aspects of technological advances in the drilling industry using the maximum reservoir contact (MRC) method compared to other drilling technologies have been investigated in this study. Field and survey methods from combined implementation research methods have been performed by a dynamic approach using Vensim software. Professors, drilling and reservoir engineering professionals in the oil and gas drilling industry, or equivalent positions, comprised the study’s statistical population. Finally, 120 individuals were chosen by nonprobabilistic sampling (judgment) and the snowball method. In the Vensim dynamic environment, the simulation completion time (based on the 2017 dynamics model) and the initial simulation time (based on the 2013 dynamics model) were adjusted to generate a flow diagram analyzing the economic aspects of technological improvements in this type of drilling industry. According to the causal tree results, the drilling industry’s performance has the highest priority among studies of economic aspects of technological changes in the drilling industry using the MRC method. It has a significant relationship with technological changes in the drilling industry. The sensitivity analysis chart demonstrated that with a change in the variable of indicators of the drilling industry at an average level of 5.25 to 5.5, the target variable, i.e., the performance of the drilling industry, had the least sensitivity and had no particular effect on it. On the other hand, by modifying the effectiveness of the drilling industry, effectiveness indicators at the average level of 6.95, the target variable had the maximum sensitivity and had a very significant effect on it.