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Journals / Yönetim ve Ekonomi Araştırmaları Dergisi / 2022 / Cilt: 20 - Sayı: 3

A NEW BANKRUPTCY FORECAST MODELLING FOR ENERGY COMPANIES

ENERJİ FİRMALARI İÇİN İFLAS TAHMİN MODELLEMESİ

Gerçek ÖZPARLAK
Pages
33–58
Publication Date
2022-11-06
DOI
—
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AI Summary & Key Takeaways

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

According to the sensitivity and specificity (R.O.C.) results, the performance of the model was found to be strong for distinguish differ between bankrupted and non-bankrupted companies.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Due to the Covid-19 epidemic, there was a significant increase in company bankruptcies in 2020.
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Key Findings & Data:For the study sample, 30 financial ratios of 23 energy companies that declared bankruptcy in the U.S.A. in 2020 and 30 financial ratios of 23 energy companies that were financially successful in the same period were selected.
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Conclusion & Impact:According to the sensitivity and specificity (R.O.C.) results, the performance of the model was found to be strong for distinguish differ between bankrupted and non-bankrupted companies.
🔬Design:Modeling & Simulation
📍Scope:2020 Verileri
⚙️Variables:Domain Parameters

Abstract

Due to the Covid-19 epidemic, there was a significant increase in company bankruptcies in 2020. In this period, especially the energy sector has been one area where bankruptcies are the most seen. In this context, this study aims to build a model that can predict financially unsuccessful companies that have declared bankruptcy and successful companies operating in the energy sector in the U.S.A. For the study sample, 30 financial ratios of 23 energy companies that declared bankruptcy in the U.S.A. in 2020 and 30 financial ratios of 23 energy companies that were financially successful in the same period were selected. The multiple discriminant analysis (M.D.A.) was chosen to differentiate between the groups. According to the research results, the accuracy rate of the created function was found to be 87.0%. According to the sensitivity and specificity (R.O.C.) results, the performance of the model was found to be strong for distinguish differ between bankrupted and non-bankrupted companies.

Özet

Covid-19 salgını nedeniyle 2020 yılında şirket iflaslarında büyük artışlar yaşanmıştır. Bu dönemde özellikle enerji sektörü, en çok iflasların görüldüğü alanlardan bir tanesi olmuştur. Bu bağlamda bu çalışmanı amacı, ABD’de de enerji sektöründe faaliyet gösteren finansal açıdan başarısız firmalar (iflasını açıklamış firmalar) ile başarılı firmaları önceden tahmin edebilen bir model oluşturmaktır. Çalışmanın örneklemi için 2020 yılında ABD’de iflasını açıklayan 23 adet enerji şirketi ve aynı dönemde finansal açıdan başarılı olan 23 adet enerji şirketi seçilmiştir. Gruplar arasındaki ayrımı yapmak için çoklu ayırma analizi metodu yöntem olarak seçilmiştir. Araştırmanın sonuçlarına göre, oluşturulan fonksiyonun başarı oranı %87,0 olarak bulunmuştur. Duyarlılık ve özgüllük (R.O.C.) sonuçlarına göre, iflas etmiş ve iflas etmemiş şirketleri ayırt etmede modelin performansı güçlü bulunmuştur.

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Cite This Article

ÖZPARLAK, G. (2022). A NEW BANKRUPTCY FORECAST MODELLING FOR ENERGY COMPANIES. Yönetim ve Ekonomi Araştırmaları Dergisi, Cilt: 20 - Sayı: 3, 33–58. https://ajindex.com/articles/647514

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