Asset-Liability Dynamic GAP Forecasting applying Adaptive Neuro-Fuzzy Inference System(ANFIS) and Auto Regressive Fractional Integral Moving Average (arfima): Case Study of a Private Bank in Iran

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Ghasemi Abdolrasool; BAHRAMI JAVID; Shabani Jafroodi Sorayya

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Financial Economics Year:2019 | Volume:12 | Issue:45 Page(s): 93-126

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

807

Download:

Cites:

Information Journal Paper

Title

Asset-Liability Dynamic GAP Forecasting applying Adaptive Neuro-Fuzzy Inference System(ANFIS) and Auto Regressive Fractional Integral Moving Average (arfima): Case Study of a Private Bank in Iran

Author(s)

Ghasemi Abdolrasool | BAHRAMI JAVID | Shabani Jafroodi Sorayya | Issue Writer Certificate

Keywords

Banks liquidity managementQ1

anfis methodQ1

arfima methodQ1

private banksQ1

Abstract

The proper management of liquidity, the ability to raise funds and timely fulfillment of obligations, is a prerequisite for the survival of banks. Proper liquidity management can reduce the likelihood of serious banking problems. Indeed, given that liquidity shortage in a bank can result in widespread systemic consequences, the importance of liquidity for each bank is beyond any other issue. In addition, banks should always monitor their assets and liabilities strictly in order to increase the profitability of the banks and manage the liquidity from banking operations in the best possible way as well. Estimated Maturity of asset-liability gap in future periods is one of the key measures in the direction of optimal liquidity management and identifying the potential of the bank against any deficits in the leading one. In this paper, the asset-liability gap is calculated based on two adaptive-neuro-fuzzy models and long-term memory modeling (ARFIMA) modeling. The results of the research show that, the accuracy of both models in the prediction of the dynamic gap has been high. However, the results of modeling applying a long-term memory pattern show higher accuracy in this regard. Thus banks can assess the long-term position of the asset-liability gap and identify the amount of their surplus liquidity resources using this template.

Cites

No record.

References

No record.

Cite

APA: Copy

Ghasemi, Abdolrasool, BAHRAMI, JAVID, & Shabani Jafroodi, Sorayya. (2019). Asset-Liability Dynamic GAP Forecasting applying Adaptive Neuro-Fuzzy Inference System(ANFIS) and Auto Regressive Fractional Integral Moving Average (arfima): Case Study of a Private Bank in Iran. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), 12(45 ), 93-126. SID. https://sid.ir/paper/229103/en

Vancouver: Copy

Ghasemi Abdolrasool, BAHRAMI JAVID, Shabani Jafroodi Sorayya. Asset-Liability Dynamic GAP Forecasting applying Adaptive Neuro-Fuzzy Inference System(ANFIS) and Auto Regressive Fractional Integral Moving Average (arfima): Case Study of a Private Bank in Iran. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT)[Internet]. 2019;12(45 ):93-126. Available from: https://sid.ir/paper/229103/en

IEEE: Copy

Abdolrasool Ghasemi, JAVID BAHRAMI, and Sorayya Shabani Jafroodi, “Asset-Liability Dynamic GAP Forecasting applying Adaptive Neuro-Fuzzy Inference System(ANFIS) and Auto Regressive Fractional Integral Moving Average (arfima): Case Study of a Private Bank in Iran,” JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), vol. 12, no. 45 , pp. 93–126, 2019, [Online]. Available: https://sid.ir/paper/229103/en

Related Journal Papers