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Journals / Uluslararası Ekonomi ve Yenilik Dergisi / 2020 / Cilt: 6 - Sayı: 2

Financial Failure Prediction with Decision Tree Algorithms: Textile, Wearing Apparel and Leather Sector Application

Karar Ağacı Algoritmalarıyla Finansal Başarısızlık Tahmini: Dokuma, Giyim Eşyası ve Deri Sektörü Uygulaması

Duygu ARSLANTÜRK ÇÖLLÜ
Leyla AKGÜN
Ecevit EYDURAN
Pages
225–246
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

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Objective & Hypothesis: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.
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Key Findings & Data: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.
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Conclusion & Impact: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.
🔬Design:Research Article
📍Scope:2016-2018 Verileri
⚙️Variables:Finansal Performans · karar Ağacı Algoritmaları · Tekstil Sektörü

Abstract

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.

Özet

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.

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Cite This Article

ÇÖLLÜ, D. A., AKGÜN, L., EYDURAN, E. (2020). Financial Failure Prediction with Decision Tree Algorithms: Textile, Wearing Apparel and Leather Sector Application. Uluslararası Ekonomi ve Yenilik Dergisi, Cilt: 6 - Sayı: 2, 225–246. https://ajindex.com/articles/339595

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