Bankaların gözetiminde bir araç olarak kümeleme analizi: Türk bankacılık sektörü için bir uygulama
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Date
2008
Authors
Doğan, Bariş
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Kadir Has Üniversitesi
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Abstract
Gelişmiş ülkelerde bankacılık sektörünün gözetiminden sorumlu otoritelerin bankaların gözetimi amacıyla yerinde ve uzaktan yaptıkları incelemelerde geleneksel ve istatistiksel tekniklerden faydalandıkları görülmektedir. Bankacılığın karmaşık ve hızla değişen yapısını dikkate alan gözetim otoritelerinin bankacılık sektörünün etkin bir biçimde gözetimi amacıyla mevcut teknikleri geliştirmek ve yeni teknikler bulmak için çalışmalar yaptıkları bilinmektedir.Bu çalışmada, Türk Bankacılık Sektörü'nde (1998-2006) dönemi itibariyle faal olan ticaret bankalarına ait finansal oranlar baz alınarak yapılan ``Kümeleme Analizi'' uygulamaları ile elde edilen sonuçların, bankalar için yapılan finansal analiz sonuçları ile uyumluluğu tartışılarak elde edilen sonuçlar ışığında ``Kümeleme Analizi'' tekniğinin bankaların finansal performanslarını belirlemek ve finansal açıdan benzer bankaları tanımlamak amacıyla, bankaların gözetiminde kullanılan mevcut teknikleri tamamlayıcı bir teknik olarak kullanılabilirliği irdelenmektedir
Bank supervision authorities of developed countries use traditional and statistical techniques during on-site and off-site examinations of banks. Such systems are collectively termed ?supervisory risk assessment and early warning systems??. Supervision authorities continuously search for improvement of current techniques as well as new techniques for effective bank supervision by considering the complex and fast changing nature of banking institutions. This study is based on a Cluster Analysis approach to a data set generated through financial ratios of active Turkish Commercial Banks between years 1998 and 2006. In this respect, first, Hierarachical Cluster Analysis techniques are applied to each data set and then a financial analysis work rendered for each individual bank in order to be able to measure the correctness of clusters generated by clustering algorithms. The objective of the study is set as to compare the Cluster Analysis results with the financial analysis results in terms of significance and determine the appropriatness of usage of Clustering techniques by supervision authorities for measurement of bank financial performance and recognition of financially similar banks
Bank supervision authorities of developed countries use traditional and statistical techniques during on-site and off-site examinations of banks. Such systems are collectively termed ?supervisory risk assessment and early warning systems??. Supervision authorities continuously search for improvement of current techniques as well as new techniques for effective bank supervision by considering the complex and fast changing nature of banking institutions. This study is based on a Cluster Analysis approach to a data set generated through financial ratios of active Turkish Commercial Banks between years 1998 and 2006. In this respect, first, Hierarachical Cluster Analysis techniques are applied to each data set and then a financial analysis work rendered for each individual bank in order to be able to measure the correctness of clusters generated by clustering algorithms. The objective of the study is set as to compare the Cluster Analysis results with the financial analysis results in terms of significance and determine the appropriatness of usage of Clustering techniques by supervision authorities for measurement of bank financial performance and recognition of financially similar banks
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Ekonomi, Economics
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WoS Q
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1
End Page
389