V. D'Amato, R. D’Ecclesia, Susanna Levantesi

2021.11.12Decisions in Economics and Finance

DOI: 10.1007/s10203-021-00364-5

tlooto Summary

Using the Bloomberg ESG scores, the role of structural variables adopting a machine learning approach is investigated, in particular, the Random Forest algorithm and it is found that financial statements items represent a powerful tool to explain the ESG score.

Abstract

Abstract is not available.

Citation format

D'AMATO, V.; D’ECCLESIA, R.; LEVANTESI, Susanna. Fundamental ratios as predictors of ESG scores: A machine learning approach. Decisions in Economics and Finance, 2021, 44: 1087–1110.