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A new classifier design with fuzzy functions
(Springer-Verlag Berlin, 2007) Celikyılmaz, Aslı; Türkşen, I. Burhan; Aktaş, Ramazan; Doğanay, M. Mete; Ceylan, N. Başak; 112010
This paper presents a new fuzzy classifier design, which constructs one classifier for each fuzzy partition of a given system. The new approach, namely Fuzzy Classifier Functions (FCF), is an adaptation of our generic design on Fuzzy Functions to classification problems. This approach couples any fuzzy clustering algorithm with any classification method, in a unique way. The presented model derives fuzzy functions (rules) from data to classify patterns into number of classes. Fuzzy c-means clustering is used to capture hidden fuzzy patterns and a linear or a non-linear classifier function is used to build one classifier model for each pattern identified. The performance of each classifier is enhanced by using corresponding membership values of the data vectors as additional input variables. FCF is proposed as an alternate representation and reasoning schema to fuzzy rule base classifiers. The proposed method is evaluated by the comparison of experiments with the standard classifier methods using cross validation on test patterns.
Detecting stock-price manipulation in an emerging market: The case of Turkey
(Pergamon-Elsevier Science LTD, 2009) Öğüt, Hulusi; Doğanay, M. Mete; Aktaş, Ramazan; 112010; 1109
This paper aims to develop methods that are capable of detecting manipulation in the Istanbul Stock Exchange. We take the difference between manipulated stock's and index's average daily return, average daily change in trading volume and average daily volatility and used these statistics as explanatory variables. The data in post-manipulation and pre-manipulation periods are used as non-manipulated instances while the data in the manipulation period are used as manipulated instances. Test performance of classification accuracy, sensitivity and specificity statistics for Artificial Neural Networks (ANN) and Support Vector Machine (SVM) are compared with the results of discriminant analysis and logistics regression (logit). We found that the data mining techniques (ANN and SVM) are better suited to detect stock-price manipulation than multivariate statistical techniques (discriminant analysis, logistics regression) as the performances of the data mining techniques in terms of total classification accuracy and sensitivity statistics are better than those of multivariate techniques. We also found that unit change in difference between average daily return of manipulated stock and the index has the largest effect while unit change in difference between average daily change in trading volume of manipulated stock and index has the least effect on multivariate classifiers' decision functions
Fama-French üç faktör varlık fiyatlama modelinin İMKB’de uygulanması
(2006) Doğanay, M. Mete; 112010
Finansal Piyasalar ve Kurumlar
(Beta Yayınları, 2019) Aktaş, Ramazan; Doğanay, M. Mete; 112010
Gelişmekte Olan Hisse Senedi Piyasalarının Piyasa Verilerine Göre Gruplanması
(2007) Aktaş, Ramazan; Doğanay, M. Mete; 112010
Bu çalışmada, kümeleme (cluster) analizi yöntemi ile gelişmekte olan hisse senedi piyasaları farklı gruplara ayrılmıştır. Çalışmada, borsaya kayıtlı şirket sayısı, toplam piyasa değeri, işlem hacmi, devir hızı, fiyat endeksindeki yüzde değişim, fiyat-kazanç oranı (P/E) ve piyasa değerinin defter değerine oranı gibi temel piyasa verileri kullanılmıştır. Analizlerin sonucunda, gelişmekte olan piyasaları farklılaştıran temel değişkenlerin toplam piyasa değeri, işlem hacmi ve devir hızı olduğu belirlenmiştir. Çalışmada ayrıca, piyasa verileri esas alındığında gelişmiş ve gelişmekte olan piyasa ayrımının halâ geçerli olup olmadığını belirlemek amacıyla, yatırım yapılabilir gelişmekte olan hisse senedi piyasaları ile gelişmiş hisse senedi piyasaları da gruplanmıştır. Analiz, piyasa verileri esas alındığında bu ayrımın kaybolduğunu göstermiştir. Bu sonuçlara dayanarak, gelişmiş ve gelişmekte olan piyasa ayrımı yerine; büyük, orta büyüklükte ve küçük; likiditesi yüksek, orta seviyede likiditeye sahip ve likiditesi düşük piyasalar şeklinde bir ayrımın daha uygun olacağı değerlendirilmiştir.
Hisse senetlerinde risk ayrışımı ve İstanbul Menkul Kıymetler Borsası’nda bir uygulama
(2006) Doğanay, M. Mete; Aktaş, Ramazan; Ban, Ünsal; 112010
Bu çalışmada İMKB’de işlem gören hisse senetlerinin toplam riskleri, 1997-2004 dönemi esas alınarak piyasa riski, endüstri riski ve firma riski bileşenlerine ayrılmıştır. Toplam risk içinde piyasa riskinin ağırlığı kriz dönemlerinde artmakta, istikrar dönemlerinde azalmakta, firma riskinin ağırlığı ise kriz dönemlerinde azalmakta, istikrar dönemlerinde artmaktadır. Yapılan analizlerde toplam risk içindeki en ağırlıklı bileşenin tüm dönemlerde firma riski olduğu belirlenmiştir. Bu durum, sistematik olmayan riski ortadan kaldırmak için, finans yazınında tavsiye edildiği gibi iyi çeşitlendirilmiş bir portföy oluşturmanın oldukça zor olduğunu ortaya koymaktadır. Çalışmada ortaya çıkan diğer bir sonuç ise, toplam riski içinde firma riskinin ağırlığı yüksek olan hisse senetlerinin getirilerinin de yüksek olduğudur. Bu durum, yatırımcıların sistematik olmayan riski almalarından dolayı da ödüllendirildiklerini göstermektedir.
How to Manage the Mortgage Credit Risk in Turkey? Can Dual-indexed Mortgages be a Remedy?
(2007) Alp, Ali; 112010
A 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.
Increasing accuracy of two-class pattern recognition with enhanced fuzzy functions
(Pergamon-Elsevier Science Ltd, 2009) Doğanay, Mehmet Mete; Türkşen, İsmail Burhan; Aktaş, Ramazan; Doğanay, Mehmet Mete; Ceylan, Nildağ Başak; 122648; 1109; 112010; 108611
In building an approximate fuzzy classifier system, significant effort is laid oil estimation and fine tuning of fuzzy sets. However, in such systems little thought is given to the way in which membership functions are combined within fuzzy rules. In this paper, a robust method, improved fuzzy classifier functions (IFCF) design is proposed for two-class pattern recognition problems. A supervised hybrid improved fuzzy Clustering for classification (IFC-C) algorithm is implemented for structure identification. IFC-C algorithm is based oil it dual optimization method, which yields simultaneous estimates of the parameters of (c-classification functions together with fuzzy c partitioning of dataset based oil a distance measure. The merit of novel IFCF is that the information oil natural grouping of data samples i.e., the membership values, are utilized as additional predictors of each fuzzy classifier function to improve accuracy of system model. Improved fuzzy classifier functions are approximated using statistical and soft computing approaches. A new semi-non-parametric inference mechanism is implemented for reasoning. The experimental results Of the new modeling approach indicate that the new IFCF is it promising method for two-class pattern recognition problems
Predicting Financial Failure Of The Turkish Banks
(2006) Doganay, M. Mete; Ceylan, Nildag Basak; Aktas, Ramazan; 112010
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; 112010
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.
Prediction of bank financial strength ratings: the case of Turkey
(Elsevier Science BV, 2012) Öğüt, Hulusi; Doğanay, M. Mete; Ceylan, Nildağ Başak; Aktaş, Ramazan; 112010; 108611; 1109
Bank financial strength ratings have gained widespread popularity especially after the recent financial turmoil. Rating agencies were criticized because of their ratings and failure to predict the bankruptcy of the banks. Based on this observation, we investigate whether the forecast of the rating of bank's financial strength using publicly available data is consistent with those of the credit rating agency. We use the data of Turkish banks for this investigation. We take a country-specific approach because previous studies found that proxies used for environmental factors (political, economic, and financial risk of the country) did not have any explanatory power and it is hard to find international data for other important factors such as franchise value, concentration, and efficiency. We use two popular multivariate statistical techniques (multiple discriminant analysis and ordered logistic regression) to estimate a suitable model and we compare their performances with those of two mostly used data mining techniques (Support Vector Machine and Artificial Neural Network). Our results suggest that our predictions are consistent with those of Moody's financial strength rating in general.. The important factors in rating are found to be profitability (measured by return on equity), efficient use of resources, and funding the businesses and the households instead of the government that shows efficient placement of the funds.
Prediction of financial information manipulation by using support vector machine and probabilistic neural network
(Pergamon-Elsevier Science LTD, 2009) Öğüt, Hulusi; Aktaş, Ramazan; Alp, Ali; Doğanay, M. Mete; 1109; 6974; 112010
Different 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.
Sayısal Karar Verme Yöntemleri
(2020) Doğanay, Mete M.; Gökmen, Yunus; Gazibey, Yavuz; Türen, Ufuk; 112010
The role of liquidity in the pricing of stocks traded on the Istanbul Stock Exchange
(Bilgesel Yayıncılık San&Tic Ltd, 2010) Yüksel, Aslı; Doğanay, Mehmet Mete; Doğanay, Mehmet Mete; 11028; 37770; 112010
The role of liquidity in the pricing of stocks traded on the Istanbul Stock Exchange This paper extends the empirical literature on the relationship between liquidity and stock returns by providing evidence from the Istanbul Stock Exchange. Using share turnover as a proxy for liquidity, this relationship is examined in two alternative ways. First, Fama and MacBeth (1973) cross-sectional regressions are employed with liquidity, beta, size and book to market ratio serving as potentia firm characteristics that may be relevant for pricing. Second, the role of liquidity is examined in a Fama and French (1993) framework. The findings reveal the following: Liquidity and book-to-market value are identified as two firm characteristics that appear to contain information about variation in expected returns. Moreover based on the explanatory power of the model and the Outcome of the Gibbon, Ross, and Shanken (1989) test, Fama and French (1993) three-factor asset-pricing model augmented by the liquidity factor appears to fit the data well
Towards Predicting Financial Information Manipulation
(2007) Doğanay, Mehmet Mete; Alp, Ali; Doğanay, Mehmet Mete; 112010
Manipulation 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.
Türkiye'de İpotekli Konut Kredi Riskinin Yönetimi: Çift Endeksli Krediler Çözüm Olabilir mi?
(2007) Alp, Ali; Doğanay, Mete; 112010
Türkiye'de son zamanlarda piyasa tabanlı bir konut finansman sistemi arayışları mevcuttur. Bu çalışmada, gelişmiş ve gelişmekte olan ülkelerde kullanılan ipotekli konut kredileri araştırılmış ve Türkiye için hem kredi veren finansal kurumların hem de kredi kullanan kişilerin maruz kalabilecekleri riskleri minimize eden bir ipotekli konut kredisi modeli belirlenmeye çalışılmıştır. Değişik ipotekli konut kredisi türleri kredi verenler ve kredi kullanalar açısından değişik riskler taşımaktadır. Türkiye'de yaşanan ekonomik tecrübeler dikkate alındığında, tüm riskleri minimize eden ipotekli konut kredisi türünün çift endeksli kredi modeli olduğu tespit edilmiştir. Bu kredi modeli, ekonominin en dalgalı olduğu döneme ait veriler kullanılarak, tarihi simülasyon ve Monte-carlo simülasyonu yöntemleriyle test edilmiştir. Test sonuçları, çift endeksli ipotekli konut kredilinin gerek kredi veren finansal kurumları gerekse kredi kullanan kişileri önemli bir sıkıntıya sokmadan oldukça makul bir sürede ödenebildiğim göstermiştir. Analizler, bu tür kredilerin kullanılması durumunda kredi verenlerin ve kredi kullananların minimum riske maruz kalacaklarını teyit etmiştir.
Türkiye'de Televizyon Dizisi Sektörü
(2021) Doğanay, Mete; Aktaş, Mansur Konuralp; 112010
Bu çalışmanın temel amacı Türkiye’de önemli bir iletişim ve eğlence aracı olarak kabul edilen televizyon yayınlarının en çok izlenen ikinci program türü olan dizi filmlerini yapımcılık açısından incelemektir. Bu amaçla dizi sektörü temsilcileri ile görüşmeler yapılmış ve konu ile ilgili birçok kaynak incelenmiştir. Türkiye’de dizi sektörü 2010’lu yılların ilk yarısında önemli bir gelişme göstermiş ve ihracat rakamları önemli ölçüde artmıştır. Türk televizyon dizilerini diğer ülkelerin dizilerinden ayıran önemli farklar olarak, dizilerin yapım kalitelerinin yüksek olması, duyguları çok iyi yansıtması, çoğunlukla melodram türü olmakla beraber hikâyelerinin ve sunumlarının diğer ülke melodramlarından farklı olması, seyircinin merakını canlı tutan olaylar zinciri üzerine kurulması, oyunların fiziki özellikleri ile oyunculuk yetenekleri, çekimlerim değişik ve ilgi çeken mekânlarda gerçekleştirilmesi ve özellikle müziklerinin etkileyici olması değerlendirilebilir. Türk dizi film sektörü çok önemli aşamalar kaydetmiş ve günümüzde dünyaca tanınmış bir sektör haline gelmiştir. Sektörün kendini etkileyen tüm gelişmeleri gözeterek bir strateji oluşturması ve bu stratejiye göre hareket etmesi bundan sonraki başarılarını devam ettirmesi için ön

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