جستجوی مقالات مرتبط با کلیدواژه "friedman test" در نشریات گروه "حسابداری"

The Profitability of commercial banks is a very significant and complex issue that is influenced by the management of intellectual capital and financial capital as accounting factors and also indicators of the banking industry and macroeconomics as environmental factors. The main purpose of this study is to determine the importance and ranking of factors and indicators affecting the profitability of commercial banks, in order to help effective decisions of central bank policymakers and bank managers. The statistical population includes 17 commercial banks active in Tehran Stock Exchange during the years between 2016 to 2021. To achieve the purpose of this study, the Friedman ranking test in SPSS software was used. The results show that financial capital and intellectual capital as accounting factors were more valuable than the indicators of the banking industry and macroeconomics as environmental factors. The ranking of indicators has shown that the variables of bank size, human capital efficiency, ownership concentration and management efficiency are the most important factors, respectively; In contrast, the variables of capital efficiency of innovation, competition, GDP and communication capital efficiency were the least important in the profitability of commercial banks, respectively. Therefore, based on empirical evidence of this study suggests that managers of commercial banks, along with environmental factors, should pay sufficient attention to the management at their disposal resources. In particular, the increase in assets through the attracting deposits and the increase of capital, and the optimal use of human capital have a decisive role in improving profitability.

The purpose of this research is to develop a dynamic regression model for prediction of future operating cash flows of firms accepted in Tehran Stock Exchange. So, the information of 250 companies were considered during 2004 to 2017. In this study, operational and economic variables were added to the fundamental model of Bart, Cram and Nelson (BCN). Due to the simultaneous effect of sales growth rate on working capital accruals (independent variables) and future operating cash flows (dependent variable) to fit the model, the gray box method was used with the help of the Pade approximant. To estimate the model were used three meta heuristics algorithm, grey wolf optimization, particle swarm optimization and inspired optic optimization. The results showed that the model which estimated by gray wolff algorithm has the least cash flows prediction error among all algorithms. In order to investigate the superiority of the gray wolf algorithm, the Friedman test was used. The results of this test also confirmed the superiority of the gray wolf algorithm in predicting future cash flows.