Makroekonomik faktörlerle finansal oranlar arasındaki bağlantı: Gelişmekte olan ülkelerde şirket karlılığının bütünsel analizi

Year 2023, Volume: 22 Issue: 48 - İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, Aralık/Güz 2023, Cilt 22, Sayı 48, 1101 - 1123, 30.12.2023

Dilek Yomralıoğlu , Gökhan Silahtaroğlu

https://doi.org/10.46928/iticusbe.1347449

Abstract

Çalışmanın Amacı; Bu çalışmanın temel amacı, şirket karlılığına etki eden makroekonomik faktörler, ilgili endeksler (dışsal değişkenler olarak), finansal oran göstergeleri (şirket içi değişkenler olarak) arasındaki örüntüleri bütüncül bir yaklaşımla ortaya çıkarmaktır. Bu araştırma aynı zamanda BİST’e (Istanbul Menkul Kıymetler Borsası) kayıtlı gıda, kimya ve metal eşya sektörlerinde faaliyet gösteren borsaya kote üretim şirketlerinin kar elde edebilmesi için bu değişkenlerin alacağı eşik değerleri ve marjlarını netleştirmeyi amaçlamaktadır. Araştırma kapsamına Haziran 2007-Aralık 2022 döneminde net kar marjı sıfırdan büyük olan şirketler alınmıştır.
Metodoloji: Çalışmada KNIME (The Konstanz Information Miner) Veri Analiz Platformu üzerinde denetimli makine öğrenmesi algoritmaları kullanılmıştır. Rastgele Orman ve Gradyan Artırma algoritmalarıyla başarılı bir model sunulmuştur.
Bulgular: Rastgele Orman Algoritmasıyla şirketlerin kar/zarar etme olasılığını tahmin etmeye yönelik on belirgin kural elde edilmiştir.
Uygulamaya yönelik sonuçlar: Bu çalışmadan elde edilen bulgular, karar vericilerle doğrudan bağlantılı olacak şekilde, kar elde etmek için değişkenlerin değerlerinin farklı kombinasyonlarını sunmaktadır. Ayrıca, finansal göstergelerin eşik değerlerinin elde edilmesiyle iç ve dış faktörlere ilişkin bilgilerimizin derinleştirilmesi ve gelişmekte olan ülke piyasalarının daha iyi anlaşılması beklenmektedir.
Özgünlük: Önceki çalışmalar çoğunlukla iki veya üç makro değişkenin seçilen şirket finansal oranlarıyla ilişkisi üzerine yoğunlaşmıştır. Ayrıca, gelişmekte olan ülke piyasaları üzerine yapılan çalışmalar oldukça azdır ve bunların yok denecek kadar azında makine öğrenimi algoritmaları kullanılmıştır. Bu çalışma, bütüncül bir yaklaşımla değişkenlerin şirket karı üzerinde ne yönde rol oynadığını göstermeyi amaçlamaktadır. Kâr elde etmek için bağımsız değişkenlerin değerlerinin farklı kombinasyonları, ülkeye özgü piyasa koşulları altında eşik değerleri ile birlikte değerlendirilecektir.

Keywords

makroekonomi, karlılık, finansal oranlar, makine öğrenmesi

EXPLORING THE NEXUS OF MACROECONOMIC FACTORS AND FINANCIAL RATIOS: A HOLISTIC ANALYSIS OF COMPANY PROFITABILITY IN DEVELOPING MARKETS

Abstract

Purpose of the Study; The primary objective of this document is to find out the patterns among macroeconomic factors, related indexes (as external variables), financial ratio indicators (as internal drivers) that had impact on company’s profit with a holistic approach. This research also aims to clarify the threshold values and the margin of these variables to achieve profit for the listed manufacturing companies which are registered to BIST (Istanbul Stock Exchange) and operating in food, chemistry and metalware sectors. The companies which have net profit margin greater than zero are taken into the pool of investigation for the period from June 2007 to December 2022.
Methodology; The study utilized supervised machine learning algorithms on KNIME Analytics Platform (The Konstanz Information Miner). A successful model has been achieved by using Random Forest Learner and Gradient Boosted Trees Learner Algorithms.
Findings; Ten prominent rules have been extracted by Random Forest algorithm to predict profit/loss probability of companies.
Practical implications; The findings derived from this study have direct relevance for decision makers by formulating the values of variables in different combinations to earn profit. Besides, the threshold values of the financial indicators which deepens our knowledge of the internal and external factors is expected to provide a better insight on the markets of developing countries.
Originality/Value; Previous studies are mostly concentrated on the relationship of two or three macro variables with the chosen financial ratios of the companies. Besides a few studies were conducted on the markets of developing countries and if not none of them, very few of them have employed machine learning algorithms. This study aims to show what direction the variables play a role on company’s profit with a holistic approach. The diverse combination of the values of independent variables to generate profit will be evaluated with their threshold values under the country specific conditions of the markets.

Keywords

macoeconomic, financial ratios, profit, machine learning

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