The Importance of Firm-Specific Financial Variables for ESG Scores: A Research in Borsa Istanbul Using Random Forest Algorithm Cover Image

Firmaya Özgü Finansal Değişkenlerin ESG Skorları İçin Önemi: Rastgele Orman Algoritması İle Borsa İstanbul’da Bir Araştırma
The Importance of Firm-Specific Financial Variables for ESG Scores: A Research in Borsa Istanbul Using Random Forest Algorithm

Author(s): Melih Kutlu, Mehmet Fatih Sert
Subject(s): Business Economy / Management, Management and complex organizations, Economic development
Published by: Orhan Sağçolak
Keywords: Sustainabilit;y ESG; Financial Performance;

Summary/Abstract: Purpose – In order to strengthen the environmental, social and governance (ESG) scores of companies, company-specific financial variables must be managed in a healthy way. In this study, the order of importance of company-specific financial variables for ESG scores is investigated. Desing/ methodology/approach – In the study in which the random forest algorithm used with ESG scores and internal financial indicators of 65 firms traded on Borsa Istanbul between 2016 and 2022. The random forest algorithm gives the optimum result by running more than one decision tree. Total ESG, environmental, social and governance scores are obtained from the Refinitiv database. Findings – It has been determined that earnings per share, leverage ratio, beta, current ratio and liquidity ratio are more important in terms of company ESG scores. Systematic risk comes to the fore in the environmental score, investor relations management in the social score, and working capital management in the governance score. Discussion – The increasing importance of climate change, energy and water use, carbon emissions, product safety and shareholder protection is reflected in the ESG scores of companies that play a leading role in these issues. Healthy management of the financial structure of companies will affect ESG scores. Strengthening these scores will help companies increase their green investments and reduce problems related to climate change.

  • Issue Year: 17/2025
  • Issue No: 1
  • Page Range: 20-30
  • Page Count: 11
  • Language: Turkish
Toggle Accessibility Mode