YAPAY SİNİR AĞLARI MODELİ İLE FİNANSAL BAŞARISIZLIK TAHMİNİ

İşletmelerin finansal durumları gerek uygulamacılar gerekse araştırmacılar tarafından incelemelere konu olmaktadır. Özellikle son yirmi yılda sermayenin önündeki engellerin kalkması ve sermaye piyasalarının küresel bir hal alması işletmelerin faaliyetlerini sürdürmelerinde içsel dinamikler kadar dışsal dinamiklere de önem vermeleri gerektiğini ortaya koymuştur. Birçok işletme bu içsel ve dışsal nedenlerden dolayı finansal başarısızlık ile karşı karşıya kalmaktadır. Özellikle kriz dönemlerinde gelişmekte olan piyasaların kırılganlığı işletmelerin başarısızlık riskini arttırmaktadır. Finansal başarısızlık karşısında firmalar çeşitli olumsuz durumlarla yüz yüze kalabilmektedir. Firmaların bu tip olumsuzluklara karşı önlem almakta gecikmesi iflas olasılıklarını arttırmaktadır. Bu sebeple firmaların finansal başarısızlıklarının tahmin edilebilmesi oldukça önemlidir. Finansal başarısızlığın tahmin edilebilmesi için literatürde birçok model geliştirilmiştir. Bu modellerden bazıları muhasebe verilerine, bazıları da piyasa verilerine dayalıdır. Finansal başarısızlık tahmin modelleri içerisinde yapay sinir ağları önemli bir yer tutmaktadır. Bu çalışma ile finansal başarısızlık tahmin modeli olarak yapay sinir ağlarının kullanımı ile ilgili olarak araştırmacılara yol gösterilmesi amaçlanmaktadır.

FINANCIAL FAILURE PREDICTION WITH ARTIFICIAL NEURAL NETWORKS MODEL

The financial situation of enterprises is subject to both the practitioners and the researchers. Especially in the last twenty years, it has been revealed that external dynamics as well as internal dynamics are influential in the operations of the enterprises with the removal of barriers to capital and the globalisation of the capital markets. Many enterprises face financial failure due to these internal and external causes. The fragility of emerging markets, especially during times of crisis, increases the risk of failure. In the event of financial failure, companies may face various negative situations. The delay of firms in taking measures against these types of negativities increases the probability of bankruptcy. For this reason, it is very important to be able to predict the financial failures of firms. Several models have been developed in the literature to predict financial failure. Some of these models are based on accounting data and others are based on market data. Artificial neural networks play a significant role in financial failure prediction models. With this study, it is aimed to guide the researchers about the use of artificial neural networks as a financial failure prediction model.

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