چکیده:
The main purpose of this study is to develop a Fuzzy inference system to predict bank profitability in Iran and help investors in their investment decisions. For this purpose, the main effective variables on bank profitability, including facilities, deposits, manpower costs, and assets were recognized. In the next step, the data of 13 banks were collected from 2001 to 2011. The membership functions and Fuzzy rules were developed in the MATLAB software and then, Fuzzy inference system was developed. The findings revealed that the system has an appropriate performance in predicting profitability of Iranian banks and rarely makes any error in this area. The predicted profitability of many banks has increased during the study period and also the predicted profitability of private banks was more than public banks. The banks of Industry and Mine and Karafarin Bank had the least profitability and Mellat Bank had the highest. Finally, Post Bank had the most errors while Mellat Bank had the fewest errors.
خلاصه ماشینی:
"(2012), developed a Hybrid model which is an adaptive Mimetic Algorithm combined with fuzzy approach that generates and optimizes a set of "if-then" rules for bankruptcy prediction for Tehran Stock Exchange (TSE) data bank, adopting 18 variables all of which are accounting ones, between 2001 and 2009.
Inference from introduction to conclusion In order to determine fuzzy set and membership functions of quantitative characteristics, weight of each rule should be defined.
(رجوع شود به تصویر صحفه) The main variables in this article are divided into two categories: The inputs, including the actual volume of total assets, actual volume of total interests, actual volume of facilities and actual price of total labor and the output, including the actual level of total profitability.
1 (رجوع شود به تصویر صحفه) Since the present study aims to develop a fuzzy inference system, the final output will be a system based on the input variables of banks.
4. Data Analysis and Empirical Evaluation Indeed, the present study aims to develop a fuzzy inference system for predicting bank profitability in a given year.
In order to predict bank profitability level through input variables, including assets, deposits, facilities, labor costs, the statistical data were collected from 2001 to 2011.
Determining Range of Research Variables (رجوع شود به تصویر صحفه) Based on the results of tables 4 and 5, membership function of five linguistic groups is presented in figure 2.
"Analysis of the Effective Factors on Profitability of Commercial Banks (Refah Bank as Case Study)", Journal of Financial Researches, Vol. 8, Issue 21, pp."