Can climate change attention predict energy stock returns?

Environ Sci Pollut Res Int

School of Statistics and Mathematics, Central University of Finance and Economics, Shahe Higher Education Park, Changping District, Beijing, 102206, People's Republic of China.

Published: August 2023

We propose a climate change attention (CCA) index based on Google search volume index (GSVI) from 2004 to 2021 and show that it is an economically and statistically significant negative predictor for next month's energy stock returns. The index is extracted using principal component analysis (PCA), but the results are similar by using the equal-weighted average method. Compared with 14 traditional macroeconomic predictors, CCA performs the best and provides complementary information when added into bivariate and multivariate macro predictive models. When further considering the effect of CCA's forecasting power over different periods, strong evidence is shown that this outperformance is especially prominent in economic depressions and down market conditions. From the asset allocation perspective, CCA can provide a mean-variance investor with significant economic gains under alternative risk aversions. Our empirical results prove that investors' attention to climate change contains predictive information for excess returns of global traditional energy stock index.

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Source
http://dx.doi.org/10.1007/s11356-023-28731-2DOI Listing

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