Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    Common volatility in clean energy stocks
    (Elsevier B V, 2025-08-01) Pham L; Pham S; Do H; Bissoondoyal-Bheenick E; Brooks R
    This study investigates common volatility (COVOL) within the clean energy sector, motivated by the sector's growing importance and its susceptibility to external shocks. For this purpose, we use the COVOL measure developed by Engle and Campos-Martins (2023) to explore sector-wide and sub-sector common volatility, in a range of sub-sectors including renewable energy, energy storage, energy conversion, power conservation, and greener utilities. Our analysis highlights the major events that significantly impact the volatility of clean energy stocks. These include global economic disruptions, geopolitical tension, policy changes and climate-related events. Other key findings reveal the heterogeneous association of sub-sectors’ COVOL to different economic and financial factors, alongside superior explanatory power of COVOL on clean energy risk and return compared to alternative news-based uncertainty measures. These insights emphasize the importance for investors to integrate thorough risk management strategies and for policymakers to create a stable, supportive environment for the clean energy market. The study's implications extend to enhancing sector resilience and informing strategic investment and policy decisions, contributing to the sustainable growth of clean energy amidst global economic and environmental uncertainties.
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    Dynamic connectedness in the higher moments between clean energy and oil prices
    (Elsevier B.V., 2024-10-31) Hao W; Pham L
    Focusing on clean energy stocks and oil prices, we find that connectedness between these assets not only exists in volatility, but also at higher-order moments, such as skewness and kurtosis, which have been largely under studied in the existing literature. Estimating the connectedness using intra-day data, our initial static analyses suggest that the connectedness between the clean energy and oil markets is heterogenous across the moments and the shock transmitter/recipient role played by each market varies across moments. Further dynamic analyses indicate that higher-order moment connectedness is also time varying and appears to be stronger during uncertain market conditions. In addition, we identify day-of-the-week patterns of higher-order moment connectedness during high uncertainty periods, but these patterns appear to be reversed during low uncertainty periods. The employment of Markov switching regression models further corroborates the market uncertainties as the determinants of higher-order moment connectedness. As an important extension, we provide empirical evidence that including clean energy stocks in the investment portfolio can effectively hedge oil price risks and considering higher-order moments in constructing investment strategies adds extra value to investors. Our utility-based hedging strategy and minimum connectedness portfolio can offer higher utility gains and better risk-return trade-offs to those investors who are not infinitely risk-averse.
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    The impact of climate policy on U.S. environmentally friendly firms: A firm-level examination of stock return, volatility, volume, and connectedness
    (Elsevier B V, 2023-03) Pham L; Hao W; Truong H; Trinh HH
    This paper investigates the green stock market reaction to climate policy events associated with the Paris Agreement and the U.S. presidential elections. We document abnormal returns, volatility and volume reactions to climate policy events among green stocks. However, the magnitude of the reactions varies between the tightening and loosening of climate policy and across subgroups of the green stock markets. Our connectedness analysis further investigates the spillover patterns among individual green stocks and confirms their heterogeneous natures when responding to the occurrence of these climate policy events. By constructing a minimum connectedness portfolio based on the estimated connectedness among these green stocks, we find that investors can substantially reduce their risks. Our findings have strong implications for policy makers in designing policies to effectively promote green investments and mitigate climate change.