ANT COLONY OPTIMIZATION APPROACH TO PREDICTING FINANCIAL DISTRESS: A RESEARCH IN BORSA ISTANBUL

Year 2021, Volume: 20 Issue: 40, 525 - 541, 25.06.2021

Serkan Terzi , İlker Kıymetli Şen

https://doi.org/10.46928/iticusbe.868360

Cited By: 1

Abstract

Purpose: The purpose of this paper is to develop a reliable model to determine predicting financial distress of manufacturing companies in Borsa Istanbul. In order to achieve this purpose, 18 variables calculated from financial statements of 100 manufacturing companies quoted in Borsa Istanbul between 2005-2019 are used in the analysis.
Approach: The ant colony algorithm-based approach (AntMiner+) is used in the optimization algorithm for predicting the financial distress.
Findings: As a result of the paper, rules for financial distress with the highest success rate are determined. Some of the variables that are directly related to the risk of financial distress are determined. In addition, It has been determined that the success rate for the generated rules between 82%-93%, and the average success is 88%. Thus, the algorithm used during the analyses is found valid according to the literature.
Originality: There are few studies in the literature that use the ant colony algorithm (AntMiner+) to detect financial failure. In Turkey, there are no studies in determining financial distress with this algorithm.

Keywords

Financial Distress, Ant Colony, Borsa Istanbul

FİNANSAL BAŞARISIZLIK TAHMİNİNDE KARINCA KOLONİSİ OPTİMİZASYON YAKLAŞIMI: BORSA İSTANBUL’DA BİR ARAŞTIRMA

Abstract

Amaç: Bu çalışmanın amacı, Borsa İstanbul İmalat Sanayiinde işlem gören şirketlerin finansal başarısızlık tahmininde güvenilir bir model geliştirmektir. Bunun için Borsa İstanbul’da kayıtlı 100 üretim şirketinin 2005-2019 yılları arasında finansal tablolarından elde edilen 18 değişken analizde kullanılmıştır.
Yaklaşım: Finansal başarısızlık tahmininde optimizasyon algoritmaları içinde yer alan karınca kolonisi algoritması tabanlı bir yaklaşım (antminer +) kullanılmıştır.
Bulgular: Yapılan çalışma sonucunda finansal başarısızlık tahmininde en yüksek başarım oranına sahip kurallar tespit edilmiştir. Bazı değişkenlerin finansal başarısızlık riski ile doğrudan ilişkili olduğu belirlenmiştir. Ayrıca oluşturulan kuralların başarı oranlarının %82-%93 arasında olduğu belirlenmiş olup, ortalama başarı oranı ise %88 olarak tespit edilmiştir. Bu nedenle kullanılan algoritmanın literatüre göre geçerli olduğu tespit edilmiştir.
Özgünlük: Literatürde finansal başarısızlığın tespiti için karınca koloni algoritmasının (AntMiner+) kullanıldığı az sayıda çalışma mevcuttur. Türkiye’de ise finansal başarısızlık tespitinde bu algoritmayla yapılan çalışma bulunmamaktadır.

Keywords

Finansal Başarısızlık, Karınca Kolonisi, Borsa İstanbul

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