Predictors of Clean Energy Stock Returns: An Analysis with Best Subset Regressions
Finance Research Letters
; : 103912, 2023.
Article
in English
| ScienceDirect | ID: covidwho-2307934
ABSTRACT
We investigate the determinants of clean energy stock returns by considering a large set of variables. We focus on the Covid-19 period and use a novel statistical technique, best subset regressions with non-Gaussian errors, for variable selection. Our examination shows that clean energy stocks are significantly exposed to small company and emerging market equities, a new finding to the literature. Moreover, we find no influence from the oil market, contrary to conclusions of a large part of the prior work.
Full text:
Available
Collection:
Databases of international organizations
Database:
ScienceDirect
Type of study:
Prognostic study
Language:
English
Journal:
Finance Research Letters
Year:
2023
Document Type:
Article
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