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This is a Quantitative Study study.

October 1, 2025Ekonomi Politika ve Finans Arastirmalari DergisiOpen Access

The Role of Financial Indicators in the Prediction of Voluntary Carbon Disclosure: A Comparative Analysis with Machine Learning Methods

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Machine learning methods achieved over 92% accuracy in predicting voluntary carbon disclosures.
Financial indicators are crucial for understanding corporate carbon emissions in the CDP survey.
Random Forest and XGBoost algorithms demonstrated superior predictive capabilities in this analysis.
The study's findings suggest a new approach for investors in carbon risk assessment.

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Implication

Comparative analysis shows machine learning enhances prediction accuracy of voluntary carbon disclosures, indicating significant financial indicators.

Cite This Study

Yunus Emre Akdoğan (2025) studied this question.

synapsesocial.com/papers/68dd91cbfe798ba2fc498817 https://doi.org/10.30784/epfad.1651693

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Implication

Comparative analysis shows machine learning enhances prediction accuracy of voluntary carbon disclosures, indicating significant financial indicators.

The Role of Financial Indicators in the Prediction of Voluntary Carbon Disclosure: A Comparative Analysis with Machine Learning Methods

Key Points

Discussion

Implication

Cite This Study

The Role of Financial Indicators in the Prediction of Voluntary Carbon Disclosure: A Comparative Analysis with Machine Learning Methods

Key Points

Discussion

Implication

Cite This Study

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