Investigate the Optimal Combination of Bank Credit Portfolios by Using Firefly Algorithm (Case Study of agricultural bank)

Document Type : Research Article

Authors

1 PhD student in Agricultural Economics, Ferdowsi University, Mashhad, Iran

2 Professor, Department of Agricultural Economics, Ferdowsi University, Mashhad, Iran

3 Associate Professor, Department of Agricultural Economics, Ferdowsi University, Mashhad, Iran

Abstract

One of the main activities of banks is the allocation of resources, one of the main aspects of which is determining the optimal combination of credits to various economic sectors. Lack of attention to the allocation of financial resources available to the bank, can cause serious damage to the entire economic system. In this study with the purpose of determining the optimal portfolio of the bank, each of the different activities of the creditor was considered as an asset. Given that the fluctuations in the ratio of lending credits collection are the main source of expected bank earnings fluctuations, so the amount of lending credits of each economic activity, which need to be collected are considered as return standard of, and its variance is consider as a risk. Also, in order to determine the range of expected return on assets, the historical average on each asset is calculated. Considering the necessity of reviewing this issue, in this paper, a multi-objective non-linear programming model using the firefly algorithm has been used to determine the optimal portfolio of agricultural bank credits. The main features of this research are the consideration of three optimistic pessimistic and hybrid strategies under different economic conditions. The results showed that the optimal pattern obtained from the firefly algorithm differs from the current model of distribution of bank credits.The present findings can provide managers with a roadmap for choosing the optimal portfolio consistent with the bank's preferences according to different estimates of return and risk, thus leading to the proper management of loans

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References

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Journal of Applied Economics Studies in Iran
Volume 10, Issue 37
April 2021
Pages 53-97

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