A data-driven approach to green investments: environmental performance, mispricing, and momentum

Vasenin, Mikhail (2022) A data-driven approach to green investments: environmental performance, mispricing, and momentum. Doctoral thesis, Northumbria University.

Text (Doctoral thesis)
Vasenin.Mikhail_phd 19023161.pdf - Submitted Version

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This study aims to investigate the relationship between environmental performance of companies and their stock market performance. It has substantially contributed to the crucial endeavour of estimating the implications of environmental performance, momentum, and mispricing on a vast array of subsamples, portfolio construction techniques, and asset pricing models, decidedly demonstrating their importance and carving a place for environmental long-minus short portfolios in the established “zoo of factors”. Through the analysis of the data related to the greenhouse gas emissions, water usage, and waste intensity from 6,391 companies, two sets of systematic risks factors were found represented by environmental performance and momentum; the outperformance of greener stocks observed in most of the samples was confirmed; the explanatory power of the environmental variables was determined, while the existence of environmental predictive power was denied. Established outcomes are contrasting with most of the literature observed in the SRI field, providing a detailed description on evidence occurring in multiple regional-, country-, status-, and sector- wise samples. The study has substantial implications for corporate social responsibility, empirical finance, asset pricing, and green finance literature as well as for individual and institutional investors and policymakers.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: socially responsible investment, green finance, ESG, asset pricing, financial econometrics
Subjects: N300 Finance
Department: Faculties > Business and Law > Newcastle Business School
University Services > Graduate School > Doctor of Philosophy
Depositing User: John Coen
Date Deposited: 30 Jan 2023 12:07
Last Modified: 30 Jan 2023 12:15
URI: https://nrl.northumbria.ac.uk/id/eprint/51267

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