MACHINE LEARNING METHODS IN CAPITAL STRUCTURE DECISIONS; APPLICATION IN BIST

Abstract

This study was conducted to create a model based on machine learning methods to determine and develop firm-specific factors that significantly affect the funding decisions of firms. The study consists of firms listed in the forest, paper and printing index of Borsa Istanbul between 2014-2023, and their capital structure decisions were analyzed with machine learning methods. As a result of the analyzes made using machine learning methods, it was determined that the performance values of the model created with the XGBoost method and the Random Forest model, in particular, performed better than the AdaBoost and SVM models. It was seen that the models created with the XGBoost and Random Forest methods were a better option for determining corporate capital structures. It was understood that the SVM model had the worst performance value.

Keywords

• Capital Structure
• Financial Ratio
• Machine Learning

MAKİNE ÖĞRENMESİ YÖNTEMLERİ İLE SERMAYE YAPISININ BELİRLENMESİ; BİST’TE UYGULAMA

Abstract

Bu çalışma, firmaların fonlama kararlarını önemli ölçüde etkileyen firmaya özgü faktörleri belirlemek ve geliştirmek için makine öğrenmesi yöntemlerine dayalı bir model oluşturmak amacıyla gerçekleştirilmiştir. Çalışma, 2014-2023 yılları arasında Borsa İstanbul’da orman, kâğıt ve basım endeksinde sıralanan firmalardan oluşmakta olup makine öğrenmesi yöntemleri ile sermaye yapısı kararları analiz edilmiştir. Makine öğrenmesi yöntemleri kullanılarak yapılan analizler sonucunda oluşturulan modeller içerisinde özellikle XGBoost yöntemi ile oluşturulan model ve Random Forest modelinin performans değerlerinin AdaBoost ve SVM modeline göre daha iyi performans gösterdiği tespit edilmiştir. Özellikle XGBoost ve Random Forest yöntemi ile oluşturulan modellerin kurumsal sermaye yapılarının belirlenmesi için daha iyi bir seçenek olduğu görülmüştür. En kötü performansın ise SVM modeli olduğu anlaşılmıştır.

Keywords

• Sermaye Yapısı
• Finansal Oran
• Makine Öğrenme

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