ESG Scores and Stock Performance Prediction: A Quantitative Study Using Random Forest Model
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ESG Scores and Stock Performance Prediction: A Quantitative Study Using Random Forest Model

Feiya Su 1*
1 University College London (UCL)
*Corresponding author: sofia.su.23@ucl.ac.uk
Published on 4 July 2025
Volume Cover
AEMPS Vol.195
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-169-3
ISBN (Online): 978-1-80590-170-9
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Abstract

Environmental, Social, and Governance (ESG) factors have become increasingly relevant in financial investment decisions. Although previous research has focused on ESG’s long-term financial impact, the predictive power of ESG scores on stock returns remains uncertain. This study employs a machine learning approach, utilizing a Random Forest model to investigate whether ESG scores can predict stock performance. Historical stock returns and ESG scores for the S&P 500 companies’ dataset are used, originally extracted from sources like Yahoo Finance. The dataset is used to train multiple machine learning models, including Random Forest, Logistic Regression, Decision Tree, and Support Vector Machine (SVM), distinguishing between high- and low-return stocks based on ESG metrics. The correlation analysis and feature importance analysis are carried out to examine the real impact of the ESG scores on stock performances. The findings suggest that ESG scores exhibit minimal to no predictive power in forecasting stock performance, challenging the notion that ESG-driven investment strategies yield superior returns. These results contribute to the growing debate on the financial relevance of ESG factors.

Keywords:

ESG Investing, Quantitative Finance, Random Forest, Portfolio Performance, Stock Returns

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Su,F. (2025). ESG Scores and Stock Performance Prediction: A Quantitative Study Using Random Forest Model. Advances in Economics, Management and Political Sciences,195,141-148.

References

[1]. Michael, A. (2022, October 10). ESG Investing: The Only Way Is Ethics - Or Is It? Forbes Advisor UK. https://www. forbes. com/uk/advisor/investing/what-is-esg-investing/

[2]. Morgan Stanley. (2024, January 26).  Sustainable Investing Interest | Morgan Stanley. Morgan Stanley. https://www. morganstanley. com/ideas/sustainable-investing-on-the-rise

[3]. Zala, R. (2023). S&P 500 ESG and Stocks Data 2023-24. Kaggle. com. https://www. kaggle. com/datasets/rikinzala/s-and-p-500-esg-and-stocks-data-2023-24?select=sp500_esg_data. csv

[4]. Whelan, T. , Atz, U. , Holt, T. , & Clark, C. (2021). ESG AND FINANCIAL PERFORMANCE: Uncovering the Relationship by Aggregating Evidence from 1, 000 Plus Studies. In NYU Stern. https://www. stern. nyu. edu/sites/default/files/assets/documents/NYU-RAM_ESG-Paper_2021%20Rev_0. pdf

[5]. ESG investing. (2024). Hargreaves Lansdown. https://www. hl. co. uk/learn/responsible-investment/esg-investing

[6]. Luo, D. (2022). ESG, liquidity, and stock returns.  Journal of International Financial Markets, Institutions and Money,  78, 101526. https://doi. org/10. 1016/j. intfin. 2022. 101526

[7]. Nour, S. (2023, October 31).  Understanding the Pearson Correlation Coefficient: Exploring Perfect Correlation. Medium. https://medium. com/@sarah. ahmed. aboelseoud/understanding-the-pearson-correlation-coefficient-exploring-perfect-correlation-c6389c995759

[8]. IBM. (2021, October 20).  Random Forest. Ibm. com. https://www. ibm. com/think/topics/random-forest

[9]. IBM. (2021, August 16).  Logistic Regression. Ibm. com. https://www. ibm. com/think/topics/logistic-regression

[10]. IBM. (2021, November 2).  Decision tree. Ibm. com. https://www. ibm. com/think/topics/decision-trees

[11]. IBM. (2023, December 12). Support Vector Machine. IBM. https://www. ibm. com/think/topics/support-vector-machine

References

[1]. Michael, A. (2022, October 10). ESG Investing: The Only Way Is Ethics - Or Is It? Forbes Advisor UK. https://www. forbes. com/uk/advisor/investing/what-is-esg-investing/

[2]. Morgan Stanley. (2024, January 26).  Sustainable Investing Interest | Morgan Stanley. Morgan Stanley. https://www. morganstanley. com/ideas/sustainable-investing-on-the-rise

[3]. Zala, R. (2023). S&P 500 ESG and Stocks Data 2023-24. Kaggle. com. https://www. kaggle. com/datasets/rikinzala/s-and-p-500-esg-and-stocks-data-2023-24?select=sp500_esg_data. csv

[4]. Whelan, T. , Atz, U. , Holt, T. , & Clark, C. (2021). ESG AND FINANCIAL PERFORMANCE: Uncovering the Relationship by Aggregating Evidence from 1, 000 Plus Studies. In NYU Stern. https://www. stern. nyu. edu/sites/default/files/assets/documents/NYU-RAM_ESG-Paper_2021%20Rev_0. pdf

[5]. ESG investing. (2024). Hargreaves Lansdown. https://www. hl. co. uk/learn/responsible-investment/esg-investing

[6]. Luo, D. (2022). ESG, liquidity, and stock returns.  Journal of International Financial Markets, Institutions and Money,  78, 101526. https://doi. org/10. 1016/j. intfin. 2022. 101526

[7]. Nour, S. (2023, October 31).  Understanding the Pearson Correlation Coefficient: Exploring Perfect Correlation. Medium. https://medium. com/@sarah. ahmed. aboelseoud/understanding-the-pearson-correlation-coefficient-exploring-perfect-correlation-c6389c995759

[8]. IBM. (2021, October 20).  Random Forest. Ibm. com. https://www. ibm. com/think/topics/random-forest

[9]. IBM. (2021, August 16).  Logistic Regression. Ibm. com. https://www. ibm. com/think/topics/logistic-regression

[10]. IBM. (2021, November 2).  Decision tree. Ibm. com. https://www. ibm. com/think/topics/decision-trees

[11]. IBM. (2023, December 12). Support Vector Machine. IBM. https://www. ibm. com/think/topics/support-vector-machine

Cite this article

Su,F. (2025). ESG Scores and Stock Performance Prediction: A Quantitative Study Using Random Forest Model. Advances in Economics, Management and Political Sciences,195,141-148.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICMRED 2025 Symposium: Effective Communication as a Powerful Management Tool

ISBN: 978-1-80590-169-3(Print) / 978-1-80590-170-9(Online)
Editor: Lukáš Vartiak
Conference website: https://2025.icmred.org/Bratislava.html
Conference date: 30 May 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.195
ISSN: 2754-1169(Print) / 2754-1177(Online)

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