Journals / Osmaniye Korkut Ata Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2023 / Cilt: 7 Sayı: 1

MEASUREMENT OF FIRM PERFORMANCE USING ACCOUNTING BASED RATIOS WITH ARTIFICIAL NEURAL NETWORKS AND DECISION TREE METHODS: A STUDY IN BORSA ISTANBUL

Yapay Sinir Ağları Ve Karar Ağacı Yöntemleri İle Muhasebeye Dayalı Oranlar Kullanılarak Firma Performansının Ölçülmesi: Borsa İstanbul’da Bir Uygulama

Pages
89–102
Publication Date
2023-06-30
DOI
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AI Summary & Key Takeaways

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

As a result, when both data mining methods were compared, it was seen that the analysis prediction values made with artificial neural networks were more consistent than the decision tree model.

📌 3 Key Takeaways

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Objective & Hypothesis:Sustainability, which is one of the most basic purpose of companies, can be achieved with high company performance.
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Key Findings & Data:Many financial and non-financial performance measurement tools can be used to measure firm performance.
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Conclusion & Impact:As a result, when both data mining methods were compared, it was seen that the analysis prediction values made with artificial neural networks were more consistent than the decision tree model.
🔬Design:Modeling & Simulation
📍Scope:2021 Verileri
⚙️Variables:Yönetim Muhasebesi · Finansal Performans Ölçümü · Yapay Sinir Ağları

Abstract

Sustainability, which is one of the most basic purpose of companies, can be achieved with high company performance. Many financial and non-financial performance measurement tools can be used to measure firm performance. Performance evaluation is an important management accounting tool as a process that allows future decisions to be based on solid foundations. Ratio analysis is one of the financial measurement tools used to measure firm performance. These ratios, which are sometimes a leading indicator, may indicate that companies should take various measures. This study aimed to determine the relationship between accounting-based ratios and firm performance using artificial neural networks and decision tree methods, which are data mining techniques. For this purpose, analyzes were carried out on the ratios obtained by using the 2021 financial statements of the companies in the Borsa Istanbul (BIST) holdings and investment companies sector. As a result, when both data mining methods were compared, it was seen that the analysis prediction values made with artificial neural networks were more consistent than the decision tree model.

Özet

Firmaların en temel amaçlarından biri olan sürdürülebilirlik, yüksek şirket performansı ile sağlanabilir. Firma performansını ölçmek için birçok finansal ve finansal olmayan performans ölçüm aracı kullanılabilir. Performans ölçümü, geleceğe yönelik kararların sağlam temellere dayanmasını sağlayan bir süreç olarak önemli bir yönetim muhasebesi aracıdır. Oran analizi, firma performansını ölçmek için kullanılan finansal ölçüm araçlarından biridir. Kimi zaman öncü gösterge niteliğinde olan bu oranlar, şirketlerin çeşitli önlemler alması gerektiğinin göstergesi olabilir. Bu çalışmada, veri madenciliği tekniklerinden yapay sinir ağları ve karar ağacı yöntemleri kullanılarak muhasebe tabanlı oranlar ile firma performansı arasındaki ilişkinin belirlenmesi amaçlanmıştır. Bu amaçla Borsa İstanbul (BİST) holding ve yatırım şirketleri sektöründe yer alan şirketlerin 2021 yılı mali tabloları kullanılarak elde edilen oranlar üzerinde analizler yapılmıştır. Sonuç olarak her iki veri madenciliği yöntemi karşılaştırıldığında yapay sinir ağları ile yapılan analiz tahmin değerlerinin karar ağacı modeline göre daha tutarlı olduğu görülmüştür.

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Cite This Article

KILLI, M., IŞIK, Y. (2023). MEASUREMENT OF FIRM PERFORMANCE USING ACCOUNTING BASED RATIOS WITH ARTIFICIAL NEURAL NETWORKS AND DECISION TREE METHODS: A STUDY IN BORSA ISTANBUL. Osmaniye Korkut Ata Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 7 Sayı: 1, 89–102. https://ajindex.com/articles/962295

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