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Presenting the asset-liability management model (ALM) in explaining profit quality indicators using the fuzzy method
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Mina Farzaneh1   , Esmaeil Eghdami2 , Soghra Barari nokashti3 |
1- PhD student of accounting department, Rasht branch, Islamic Azad University, Rasht, Iran
2- Assistant Professor of Accounting Department, Lahijan Branch, Islamic Azad University, Lahijan, Iran , esmail.eghdami@iau.ac.ir
3- Assistant Professor, Department of Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran |
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Abstract: (2984 Views) |
Asset and debt management is one of the most important analytical indicators in the long-term strategic planning process. Today, the economic crises and uncertainties caused by the financial markets have affected the stability of institutions and banks, which as a result of the instability of the financial sectors, most investors have faced various environmental restrictions in achieving satisfactory returns.
The profitability of banks can be considered as an important parameter in the analysis of the performance of the banking system and a tool for measuring and comparing the liquidity management of the banking system. Several factors affect the profitability of banks, the most important of which is the management of assets and liabilities. Achieving the optimal profitability requires a fundamental management of the bank's assets and liabilities. In this research, optimal models (ALM) are presented in the explanation of profit quality indicators using the fuzzy method. The results indicate a positive and significant effect of ALM on profit predictability, profit stability and cost-to-income matching, but ALM did not have a significant effect on the institution's conditional conservatism. In the following, by fuzzifying the relationship of three significant hypotheses, the optimal model of each is presented.
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Article number: 17 |
| Keywords: asset-liability management, profit quality, fuzzy method, optimization |
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Full-Text [PDF 1524 kb]
(409 Downloads)
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Article type: Research |
Subject:
General
Received: 2023/03/27 | Accepted: 2023/06/2 | Published: 2023/07/1
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