ESG在可持续发展中的作用:基于机器学习的分析

Akshat Gupta, U. Sharma, S. Gupta
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引用次数: 4

摘要

随着环境恶化、公司治理不善和社会不和谐的日益加剧,采用可持续的做法是确保长寿和健康生活质量的必要条件。环境、社会和治理(ESG)投资是一种促进可持续发展的社会责任投资形式。ESG评级定量衡量公司的可持续实践,评级越低意味着采用的可持续实践越多。为了实现联合国可持续发展目标17,首先,我们提出了一种方法,用于创建包含全球上市公司ESG和财务参数的数据集。其次,我们提出了一个框架,用于进行统计分析和利用机器学习技术来衡量ESG参数对投资决策的重要性,以及它们如何影响公司的财务绩效。在ESG评级最高的公司中,“股本回报率”高于其他公司。在使用线性和随机森林回归模型时,当ESG数据与财务数据一起作为输入时,增长变量“利润率”和“资产回报率”的预测精度提高了。拥有最高“利润率”的公司是拥有最好ESG评级的公司。通过这项研究,我们希望加强可持续发展的全球合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of ESG in Sustainable Development: An Analysis Through the Lens of Machine Learning
With the ever-increasing environmental degradation, poor corporate governance, and social disharmony, adopting sustainable practices is imperative to ensure a prolonged and healthy quality of life. Environmental, social and governance (ESG) investing is a form of socially responsible investing promoting sustainability. ESG ratings quantitatively measure the sustainable practices of companies, with lower ratings meaning more sustainable practices adopted. With the goal of contributing to United Nations' sustainable development goal number 17, first, we present a methodology for creating a dataset that houses both ESG and financial parameters of publicly listed companies worldwide. Second, we present a framework for conducting statistical analysis and leveraging machine learning techniques to gauge the importance of ESG parameters for investment decisions and how they affect financial performance of firms. For companies with the best ESG ratings, ‘return on equity’ was found to be greater than rest of the companies. While using linear and random forest regression models, prediction accuracy of growth variables ‘profit margin’ and 'return on assets' increased when ESG data was used along with financial data as input. Companies having the highest 'profit margins' were the ones having the best ESG ratings. With this study, we hope to bolster worldwide collaboration for sustainable development.
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