4.7 Article

Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty

Journal

RESOURCES POLICY
Volume 79, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.resourpol.2022.103141

Keywords

Climate policy; Renewable energy; Predictability; Uncertainty

Ask authors/readers for more resources

This study investigates the forecasting ability of the Climate Policy Uncertainty (CPU) index on the global renewable energy market returns. It shows that CPU is an excellent positive predictor of the returns of the renewable energy market, outperforming other predictors. The study also finds that a higher CPU index has a stronger predictive ability, especially after the Paris agreement. Additionally, the predictive power of CPU index enhances the economic gain on asset allocation.
This study investigates the forecasting ability of the Climate Policy Uncertainty (CPU) index on the global renewable energy market returns. We show that CPU is of great excellence positive predictor of the returns of the renewable energy market, and better than the forecasting ability of other predictors. Moreover, we show that a higher CPU index owns more remarkable predictive ability than a lower CPU index and the CPU index is more powerful in predicting the renewable energy market returns after the Paris agreement, which indicates the sensitivity of the renewable energy market to climate policy has dramatically increased. We also find that the predictive power CPU index can enhance the economic gain on asset allocation. Furthermore, we find some similar predictive results on the global renewable energy market in the US NASDAQ OMX Renewable Energy Generation return (GRNREG), Global X Renewable Energy Producers ETT (RNRG), and Renewable Energy Group Inc (REGI) markets.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available