Lasisi, L.A.; Ngwu, F.N.; Nnamdi, K.C. Commodity Market Volatility and Climate Policy Uncertainty: A GARCH-MIDAS Approach. Preprints2024, 2024011972. https://doi.org/10.20944/preprints202401.1972.v1
APA Style
Lasisi, L.A., Ngwu, F.N., & Nnamdi, K.C. (2024). Commodity Market Volatility and Climate Policy Uncertainty: A GARCH-MIDAS Approach. Preprints. https://doi.org/10.20944/preprints202401.1972.v1
Chicago/Turabian Style
Lasisi, L.A., Franklin Nnaemeka Ngwu and Kelechi Chijindu Nnamdi. 2024 "Commodity Market Volatility and Climate Policy Uncertainty: A GARCH-MIDAS Approach" Preprints. https://doi.org/10.20944/preprints202401.1972.v1
Abstract
In this study, we employ the GARCH-MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the predictability of commodity return volatility in relation to US climate policy uncertainty (CPU). Our analysis utilizes the 20-day annualized realized commodity volatility returns of nine global commodities (Aluminium, Cocoa, Coffee, Copper, Cotton, Rice, Soybean, Sugar, and Wheat) to construct the GARCH-MIDAS model, with Climate Policy Uncertainty (CPU) serving as the predictive variable. The outcomes of our investigation reveal a consistently positive and statistically significant relationship between CPU and the selected commodities. This implies that CPU effectively serves as a robust predictor of volatility in commodity returns. The implications drawn from our results suggest that climate change policies play a pivotal role in influencing economic activities within the commodity market. This underscores the substantial impact of climate change considerations on investment decisions and further emphasizes the integral role of climate change in shaping economic choices.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
