Bu çalışma, 2016-2018 döneminde Borsa İstanbul (BIST)’da listelenen dokuma, giyim eşyası ve deri sektöründeki şirketlerin finansal başarısızlığının araştırılması, bu durumu etkileyen finansal oranların tespit edilmesi ve veri madenciliği algoritmalarının finansal başarısızlığı tahmin etmedeki güçlerinin test edilmesini sağlamak amacıyla gerçekleştirilmiştir. Bu kapsamda sektörde yer alan 20 şirketin üç yıllık finansal durumu Altman Z skoru yardımıyla değerlendirilmiş ve başarılı ve başarısız şirketler tespit edilmiştir. Ardından çeşitli finansal oranlar kullanılarak, veri madenciliği algoritmalarından CHAID, Exh-CHAID, CART ve QUEST’in şirketleri finansal başarısızlık açısından ne derece doğru sınıflandırdığı ve finansal başarısızlığı en çok etkileyen faktörlerin neler olduğu tespit edilmeye çalışılmıştır. Yapılan analizler sonucunda kullanıma en uygun tahminleme yönteminin, genel şirket sınıflandırmasını %95, başarısız şirket sınıfladırmasını ise %97.6 oranında bir doğruluk payıyla gerçekleştiren CART olduğu belirlenmiştir. Ayrıca başta özsermaye karlılığı olmak üzere, cari oran, duran varlıkların özsermayeye oranı, ticari alacakların aktiflere oranı, stok devir hızı ve faiz karşılama oranının finansal başarıyı etkilediği tespit edilmiştir.
This study was carried out in 2016-2018 with the aim of investigating the financial failure of companies in the textile, clothing and leather sector listed in the Borsa Istanbul (BIST), identifying the financial rates affecting this situation and ensuring that data mining algorithms are tested their strength in predicting financial failure. In this context, the three-year financial status of the 20 companies involved in the industry has been assessed with the help of Altman Z score and successful and unsuccessful companies have been identified. Then, using various financial rates, data mining algorithms have been tried to determine how accurately CHAID, Exh-CHAID, CART and QUEST classified companies in terms of financial failure and what are the factors that most influence financial failure. The analysis found that the most suitable method of prediction for use was the CART, which performed the overall company classification by 95% and the failed company classification by 97.6% with an accuracy share. In addition, it has been found that, primarily, the profitability of the asset, the rate of the assets to the asset, the rate of the assets of the commercial recipients, the rate of stock turnover and the rate of interest satisfaction have an impact on the financial success.
This study was conducted to investigate financial failures of textile, wearing apparel and leather sector firms listed on the Borsa İstanbul (BIST) during the 2016-2018 period using data mining algorithms i.e. CART, CHAID, Exhaustive CHAID and QUEST. In this context, determining the financial ratios affecting financial failures and comparing the classification performance of the algorithms used is the main purpose of the study. Within this framework, three years’ financial performance of 20 firms in the sector were evaluated using Altman-Z score and financially successful and unsuccessful firms were detected. Then classification performances of CART, CHAID, Exhaustive CHAID and QUEST were evaluated based on various financial ratios about correctly classifying firms in the financial failures, and it was tried to ascertain the most influential factors affecting the financial failures. As a result of the statistical evaluations, it was determined that CART was the best algorithm due to general accuracy classification ratio (95%) and the correct classification of financially unsuccessful firms (97.6%). It was concluded that financial performance was influenced by return on equity, followed by current ratio, fixed assets/equity ratio, trade receivables/assets ratio, stock turnover and interest coverage ratio.
Alan : Sosyal, Beşeri ve İdari Bilimler
Dergi Türü : Uluslararası
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