Predicting Bank Profitability in Iran by Fuzzy Inference System
Authors
Abstract:
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. Keywords: Fuzzy Inference System, Bank profitability, Membership Function, Linguistic labeling, Facilities JEL Classification: E59, C61, G24
similar resources
Predicting profitability using advice branch bank networks
The literature on social networks and their analysis has undergone explosive growth in the past decade. Network models have been used to study structures as diverse as the interaction of monks in a monastery, the links across theWorldWideWeb, and the structure of organizations. In much of this literature the network itself is viewed as the object of interest, and models are used to elucidate it...
full textEffective Factors on Bank Profitability in Iran
Not only in Iran, but throughout the world, banks and banking industry are considered as very important parts of the economy. This study seeks to investigate the impact of the internal characteristics of banks, the structure of the banking industry and the economic situation of Iran on the profitability of the banking system of Iran by exploring the theory of the Structuralism school concerning...
full textADAPTIVE NEURO-FUZZY INFERENCE SYSTEM OPTIMIZATION USING PSO FOR PREDICTING SEDIMENT TRANSPORT IN SEWERS
The flow in sewers is a complete three phase flow (air, water and sediment). The mechanism of sediment transport in sewers is very important. In other words, the passing flow must able to wash deposited sediments and the design should be done in an economic and optimized way. In this study, the sediment transport process in sewers is simulated using a hybrid model. In other words, using the Ada...
full textAdaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams
A reinforced concrete member in which the total span or shear span is especially small in relation to its depth is called a deep beam. In this study, a new approach based on the Adaptive Neural Fuzzy Inference System (ANFIS) is used to predict the shear strength of reinforced concrete (RC) deep beams. A constitutive relationship was obtained correlating the ultimate load with seven mechanical a...
full textPredicting Survival of Patients with Lung Cancer Using Improved Adaptive Neuro-Fuzzy Inference System
Introduction: Lung cancer is the main cause of mortality in both genders worldwide. This disease is caused by the uncontrollable growth and development of cells in both or one of the lungs. Although the early diagnosis of this cancer is not an easy task, the earlier it is diagnosed, the higher will be the chance of treating. The objective of this study was to develop an optimized prediction mod...
full textFuzzy Inference System Mamdani to Predicting Conformational Epitope Location
Predicting of conformational epitope is one of the major challenge in the field of vaccine design. Several methods have been developed for predicting conformational epitope but that methods have mostly been based on protein sequence and not very effective. This is the first attempt in this are to predict conformational epitope using fuzzy inference system mamdani. The proposed method based on a...
full textMy Resources
Journal title
volume 10 issue 4
pages 51- 77
publication date 2015-10
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023