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Article . 2019
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TFRS 9 ve temerrüt olasılığı modellemesi

TFRS 9 and modelling probability of default
descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2019 Turkey Turkish Publisher:Denta Florya ADSM Limited Company
Authors: Turanlı, Münevver; Taşkın, Celil;

handle: 11467/3120

TFRS 9 ve temerrüt olasılığı modellemesi

Abstract

Bu makalede, 01 Ocak 2018’de yürürlüğe giren Finansal Araçlar Raporlama Standardının bankacılığa etkisi temerrüt olasılığı bağlamında ele alınmıştır. Standart gereği, bankaların beklenen kredi zararı hesaplamasında kullanılmak üzere raporlama döneminden sonraki on iki ayda ve kredi ömrü boyunca müşteriler için temerrüt etme olasılıklarının hesaplanması gerekmektedir. Temerrüt olasılığının hesaplanmasında kullanılan modellerde lojistik regresyon yaygın olarak kullanılan bir tekniktir. Çalışmada gerçek bir veri seti ile lojistik regresyon uygulanarak temerrüt olasılığı hesaplama süreci aşama aşama anlatılmaya çalışılmıştır.

Country
Turkey
Related Organizations
Keywords

Lojistik Regresyon, Temerrüt Olasılığı, Credit Risk, IFRS 9, Kredi Riski, TFRS 9, Logistic Regression, Probability of Default

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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