İşletme Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/403
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Browsing İşletme Bölümü Yayın Koleksiyonu by Author "Alp, Ali"
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Article How to Manage the Mortgage Credit Risk in Turkey? Can Dual-indexed Mortgages be a Remedy?(2007) Alp, Ali; 112010; 01. Çankaya ÜniversitesiA market-oriented housing finance system has been under discussion in Turkey recently. In this article we analyze different types of mortgages that have been used in developed and developing countries to select the one that is most appropriate for Turkey-one which minimizes risks for both lenders and borrowers. Each type of mortgage presents different risks to borrowers and lenders. After taking into consideration the economic history of Turkey, we conclude that the most appropriate mortgage for Turkey that minimizes risk is the dual-indexed mortgage model. We test this model by using data from the most volatile period of the Turkish economy, applying historical simulation and Monte-Carlo simulation. We find that, using this model; the total loan is paid off in a reasonable period without causing substantial difficulty for lenders and borrowers. Analyses confirm that borrowers and lenders are exposed to minimum risk if this type of mortgage is originated in Turkey.Article Citation - WoS: 18Citation - Scopus: 26Prediction of Financial Information Manipulation by Using Support Vector Machine and Probabilistic Neural Network(Pergamon-elsevier Science Ltd, 2009) Ogut, Hulisi; Aktas, Ramazan; Alp, Ali; Doganay, M. Mete; 1109; 6974; 112010; 03.04. İşletme; 03. İktisadi ve İdari Birimler Fakültesi; 01. Çankaya ÜniversitesiDifferent methods have been used to predict financial information manipulation that can be defined as the distortion of the information in the financial statements. The purpose of this paper is to predict financial information manipulation by using support vector machine (SVM) and probabilistic neural network (PNN). A number of financial ratios are used as explanatory variables. Test performance of classification accuracy, sensitivity and specificity statistics for PNN and SVM are compared with the results of discriminant analysis, logistics regression (logit), and probit classifiers, which have been used in other studies. We have found that the performance of SVM and PNN are higher than that of the other classifiers analyzed before. Thus, both classifiers can be used as automated decision support system for the detection of financial information manipulation. (C) 2008 Elsevier Ltd. All rights reserved.Article Towards Predicting Financial Information Manipulation(2007) Aktaş, Ramazan; Alp, Ali; Doğanay, Mehmet Mete; 112010; 03.04. İşletme; 03. İktisadi ve İdari Birimler Fakültesi; 01. Çankaya ÜniversitesiManipulation is one of the important issues in securities markets because manipulative actions send false signals to the investors and make them buy or sell securities they otherwise would not buy or sell. There are different types of manipulations that can deceive investors. One type of manipulation is financial information manipulation. Manipulators, who use this type of manipulation, distort information in the financial statements in order to give false information about the prospects of the issuing firms. This paper attempts to predict financial information manipulation by using the multivariate statistical techniques and neural networks. A number of financial ratios are used as explanatory variables. The multivariate statistical techniques used are discriminant analysis, logistics regression (logit), and probit. Unlike other studies, the present study takes multicollinearity between financial ratios into account and conclude that the estimated multivariate statistical models rather than the neural networks can be used as early warning systems to detect possible financial information manipulations.
