İşletme Bölümü

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Citation - WoS: 2
Citation - Scopus: 9
Predicting Financial Failure of the Turkish Banks
(World Scientific Publ Co Pte Ltd, 2006) Doganay, M. Mete; Ceylan, Nildag Basak; Aktas, Ramazan; Akta, Ramazan
Banks are the most important financial institutions in Turkey because other financial institutions are not developed efficiently yet. Turkish banks experienced financial difficulties and a substantial amount of banks failed in the past. This event urged the government to initiate measures to prevent banks from getting into financial difficulties. As a result of these measures, Turkish banking system currently seems to be very attractive for the foreign investors willing to invest in this sector. One of the main concerns of the foreign investors is a possibility of a new banking crisis although it is very remote at this time. The purpose of this study is to develop early warning systems predicting the financial failure at least three years ahead of financial date. A number of multivariate statistical models such as multiple regression, discriminant analysis, logit, probit are used. We found that the most appropriate model is logit. The significant variables obtained from the models explain very well the causes of the bank failures. Our models can be used to assist interested parties to predict the probability of financial failure of Turkish banks.
Predicting the Bond Ratings of S&P 500 Firms
(2012) Doğanay, M. Mete; Körs, Murat; Akta, Ramazan
In this paper, we have developed models to find out as to what factors are important in determining the bond ratings of the non-financial firms which are included in S&P 500 index. Our analysis is different from other analyses in the literature because we have used the more recent data, i.e., the ratings belong to the years 2008, 2009 and 2010. We have performed two types of analyses. In the first analysis, all the variables are used as explanatory variables after eliminating some variables to avoid multicollinearity. In the second analysis, factor analysis is performed to group the variables into factors, and variables whose correlations with the factors are the highest are used as explanatory variables. In both the analyses, multiple discriminant analysis, ordered logit, and ordered probit models are estimated. The best model is the ordered logit model that used all the variables. The important factors that determine the bond ratings are long-term liabilities/total assets ratio, return on equity, net profit margin, trade payables, and operating income. The firms that need to improve their bond ratings must pay attention to these factors. Also, by using the models presented in the paper, investors can have an idea about the credibility of the issuers.

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