Li Ailing, Zhong Bingmao
School of Finance, Harbin University of Commerce, Harbin, China.
Postdoctoral Research Station of Northeast Asia Service Outsourcing Research Centre, Harbin University of Commerce, Harbin, China.
PLoS One. 2025 Mar 31;20(3):e0316171. doi: 10.1371/journal.pone.0316171. eCollection 2025.
As the global climate crisis intensifies, clean energy is becoming increasingly important, and the intrinsic link between industry and energy highlights the connectedness between the industrial stock market and the clean energy market, and examining this connectedness can reveal risk spillovers between these markets. We categorise the clean energy market into hydro, wind and solar markets, and the industrial stock market into low-carbon portfolios, high-carbon portfolios and ordinary portfolios, and use the network connectedness methodology to investigate the connectedness of returns between the clean energy submarkets and the industrial stock submarkets in the time and frequency domains. The returns are categorised into positive and negative returns in order to investigate the asymmetry in the connectedness of the markets. Finally, we explore the effects of EPU, GPU, and CPU in terms of network connectedness. It is revealed that clean energy submarkets are net receivers of risk, industrial stock submarkets are risk transmitters. The hydropower market is the main risk receiver, while the low-carbon portfolio is the main risk transmitter. Risk spillovers are mainly driven by short-term spillovers and do not have persistent spillover transmission. Bad news has a greater impact on network connectedness, leading to higher levels of connectedness between markets. EPU and CPU have significant effects on network connectedness. Our findings are informative for both investors and policymakers.
随着全球气候危机加剧，清洁能源变得越发重要，产业与能源之间的内在联系凸显了工业股票市场与清洁能源市场之间的关联性，而审视这种关联性能够揭示这些市场之间的风险溢出效应。我们将清洁能源市场分为水电、风能和太阳能市场，将工业股票市场分为低碳投资组合、高碳投资组合和普通投资组合，并运用网络关联性方法在时域和频域中研究清洁能源子市场与工业股票子市场之间回报的关联性。为了研究市场关联性中的不对称性，回报被分为正回报和负回报。最后，我们从网络关联性方面探究经济政策不确定性（EPU）、绿色政策不确定性（GPU）和碳政策不确定性（CPU）的影响。研究发现，清洁能源子市场是风险的净接受者，工业股票子市场是风险传播者。水电市场是主要的风险接受者，而低碳投资组合是主要的风险传播者。风险溢出主要由短期溢出驱动，且不存在持续性的溢出传导。坏消息对网络关联性有更大影响，导致市场之间的关联性更高。EPU和CPU对网络关联性有显著影响。我们的研究结果对投资者和政策制定者都具有参考价值。
