یک شبکه عصبی مصنوعی و مدل شبکه بیزی برای ارزیابی ریسک نقد شوندگی در بانکداری

یک شبکه عصبی مصنوعی و مدل شبکه بیزی برای ارزیابی ریسک نقد شوندگی در بانکداری

An ArtiÞcial Neural Network and Bayesian Network Model for Liquidity Risk Assessment in Banking

سال نشر:

2017

نویسندگان:

Madjid Tavana, Amir-Reza Abtahi, Debora Di Caprio, Maryam Poortarigh

تعداد صفحه فارسی/انگلیسی:

77

کلمات کلیدی:

Artificial neural network; Bayesian network; Intelligent systems; Liquidity risk; Banking

دانشگاه

Department of Information Technology Management Kharazmi University, Tehran, Iran

نشریه

Neurocomputing

چکیده مقاله

ABSTRACT

Liquidity risk represent a devastating financial threat to banks and may lead to irrecoverable consequences in case of underestimation or negligence. The optimal control of a phenomenon such as liquidity risk requires a precise measurement method. However, liquidity risk iscomplicated and providing a suitable definition for it constitutes a serious obstacle. In addition,  the problem of defining the related determining factors and formulating an appropriate functional form to approximate and predict its value is a difficult and complex task. To deal with these
issues, we propose a model that uses Artificial Neural Networks and Bayesian Networks. The implementation of these two intelligent systems comprises several algorithms and tests for validating the proposed model. A real-world case study is presented to demonstrate applicability
and exhibit the efficiency, accuracy and flexibility of data mining methods when modeling ambiguous occurrences related to bank liquidity risk measurement.

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