Fig. 4: Dynamic evolution of the net pairwise information spillover after the shocks of extreme weather events for the event window [−15, 15].
From: Dynamic information spillover between Chinese carbon and stock markets under extreme weather shocks
a, c, e, g present the results of the net pairwise return spillovers after the shocks of events E1–E4, respectively. b, d, f, h present the results of the net pairwise extreme risk spillovers after the shocks of events E1–E4, respectively. \(Ns_{H - EA}^{Ret}\), \(Ns_{M - EA}^{Ret}\), and \(Ns_{L - EA}^{Ret}\) denote the sum of the net return spillovers from high-, medium-, and low-polluting sectors to the Guangdong, Hubei, and Shenzhen carbon markets, respectively. \(Ns_{H - EA}^{VaR}\), \(Ns_{M - EA}^{VaR}\), and \(Ns_{L - EA}^{VaR}\) denote the net extreme risk spillovers from high-, medium-, and low-polluting sectors to the three markets, respectively. E1 represents the 2016 heavy rainfall; E2 represents the 2018 extreme heat; E3 represents the 2021 Henan catastrophic flood; and E4 represents the 2022 extreme heat.
