COMPARISON OF VARIOUS METHODS FOR ESTIMATING THE FINANCIAL FAILURES OF FIRMS: CASE OF BIST

Year 2023, , 149 - 169, 08.08.2023

Melike Kurtaran Çelik , Ahmet Kurtaran

https://doi.org/10.18092/ulikidince.1167940

Abstract

The aim of this study is to create the best forecasting model by comparing the forecasting power of Discriminant Analysis and Artificial Neural Networks models, which are widely used in the literature, among various forecasting models developed to date, in order to predict the financial failures of companies. In the study, the probability of financial failure of the companies was tried to be estimated 1, 2 and 3 years ago by using the financial ratios of 355 companies traded in BIST. For this purpose, separate forecasting models were created for each year before the financial failure, according to discriminant analysis and artificial neural networks. As a result of the study, the artificial neural network model, which was created with the discriminant analysis rates of the models that best predicted the probability of financial failure of the companies, compared to one and three years ago; Two years ago, it was determined that there was an artificial neural network model created with all financial ratios.

Keywords

Financial Failure, Financial Forecasting, Bankruptcy, Discriminant Analysis, Artificial Neural Networks

FİRMALARIN FİNANSAL BAŞARISIZLIKLARININ TAHMİNİNDE ÇEŞİTLİ YÖNTEMLERİN KARŞILAŞTIRILMASI: BIST ÖRNEĞİ

Abstract

Bu çalışmanın amacı firmaların finansal başarısızlıklarını önceden tahmin edebilmek için, bugüne kadar geliştirilen çeşitli tahmin modellerinden literatürde oldukça yaygın kullanılan Diskriminant Analizi ve Yapay Sinir Ağları modellerinin tahmin güçlerini karşılaştırarak en iyi tahmin modelinin oluşturulmasıdır. Çalışmada BIST’te işlem gören 355 firmaya ait finansal oranlar kullanılarak firmaların finansal başarısızlığa düşme olasılıkları 1, 2 ve 3 yıl öncesinden tahmin edilmeye çalışılmıştır. Bu amaçla finansal başarısızlıktan önceki her bir yıl için diskriminant analizine ve yapay sinir ağlarına göre ayrı ayrı tahmin modelleri oluşturulmuştur. Çalışma sonucunda firmaların finansal başarısızlığa düşme olasılıklarını en iyi tahmin eden modellerin bir ve üç yıl öncesine göre diskriminant analizi oranlarıyla oluşturulan yapay sinir ağı modeli; İki yıl öncesine bakıldığında tüm finansal oranlarla oluşturulan yapay sinir ağı modeli olduğu tespit edilmiştir.

Keywords

finansal başarısızlık, finansal tahmin, iflas, diskriminant analizi, yapay sinir ağları

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