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Improving risk assessment techniques in the banking sector / Ahmed Mahmoud Salim Eliwa ; Supervised Hegazy Mohamed Zaher , Assem Abdelfattah Tharwat , Ramadan Abdelhamed Zenelden

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Mahmoud Salim Eliwa , 2019Description: 176 P. : charts ; 25cmOther title:
  • تحسين اساليب تقييم المخاطر فى قطاع البنوك [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Operations Research Summary: This thesis uses a fuzzy numbers to improve risk measure for operational risk in banking sector. Firstly, to increase the accuracy of estimated operational loss in future period, we improved Loss Distribution Approach through using triangular fuzzy number to generate the random numbers, which represents the frequency and severity for operational risk instead of depending on the probability distribution. Secondly, to improve the estimated required capital to meet operational risk, the fuzzy number was used to introduce a fuzzy risk measure. This fuzzy risk measure can be used as an early warning indicator to operational risk and as an alternative the Value at Risk and Expected Shortfall
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.05.Ph.D.2019.Ah.I (Browse shelf(Opens below)) Not for loan 01010110079380000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.05.Ph.D.2019.Ah.I (Browse shelf(Opens below)) 79380.CD Not for loan 01020110079380000

Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Operations Research

This thesis uses a fuzzy numbers to improve risk measure for operational risk in banking sector. Firstly, to increase the accuracy of estimated operational loss in future period, we improved Loss Distribution Approach through using triangular fuzzy number to generate the random numbers, which represents the frequency and severity for operational risk instead of depending on the probability distribution. Secondly, to improve the estimated required capital to meet operational risk, the fuzzy number was used to introduce a fuzzy risk measure. This fuzzy risk measure can be used as an early warning indicator to operational risk and as an alternative the Value at Risk and Expected Shortfall

Issued also as CD

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