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Banka işletmelerinde çok boyutlu mali başarısızlık tahmin modeli

Multi dimensional forecasting methods to analize financial distress in banking enterprises

  1. Tez No: 94517
  2. Yazar: BLEDA GÖKHAN AKMUT
  3. Danışmanlar: PROF.DR. YÜKSEL KOÇ YALKIN
  4. Tez Türü: Yüksek Lisans
  5. Konular: Bankacılık, İşletme, Banking, Business Administration
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 1999
  8. Dil: Türkçe
  9. Üniversite: Ankara Üniversitesi
  10. Enstitü: Sosyal Bilimler Enstitüsü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 113

Özet

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Özet (Çeviri)

SUMMARY In Turkey a number of factors helped to stabilize the banking environment in recent years.The industry was heavily regulated. Commercial banking operations were basically collecting resources and lending. Limited competition faciliated fair and stable profitability.The regulators were concerned by the safety the industry and the control of its money creation power. The seventies and eighties were the periods of the first drastic waves of changes in the industry.. Among the main driving forces, three factors were stifling those changes:The inflating role of the financial markets,deregulation,and the increase in competition. On foreign exchange markets, the floating exchange rates accelerated the growth of uncertainty. Monetary policies favouring high levels of interest rates and stimulating their volatility emerged. The starting point of the first chapter of this study is a description of the banking sectors in Turkey. In the second part of the chapter all kind of risks such as default risk, liquidity risk, foreign exchange nadd interest rate risks are explained. Chapter two presents a simplified overview of mutivariate data analysis.lt stresses that multivariate analysis methods will increasingly influence not onlythe analyticalaspacts of research but also the design and approach to data collection for decision making and problem solving. A classification of the several types of multivatiate techniques (Multiple Regression, Multiple Discriminant Analysis, Logit, Probit) is presented and general guidelines for their application are provided. The 95chapter concludes with a discussion of the database that is utilized throughout most of the second chapter to illustrate the application of Multiple Regression and Logit in the Turkish Banking Industry. At the end of the chapter a summary table which indicates that four variable X3, Xo, X13, Xi6 entered the model and are significant for the estimation of the bancruptcy of the banks. 96

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