Extreme risk spillover between chinese and global crude oil futures

Abstract

Highlights The risk spillover between chinese and the global crude oil futures is studied. VaR connectedness networks are built to measure upside and downside risk spillover. China's crude oil futures behave as a net risk receiver in the global crude oil system. Brent and WTI play the leading roles in risk transmission in the system. Risk spillover presents time-varying feature and rises sharply by the COVID-19 pandemic.

Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak

“…Along a similar research line, Yang et al (2021) considered risk spillover between China's crude oil futures and international crude oil futures by constructing VaR connectedness networks. They discovered that the risk spillover between Chinese and international crude oil futures possessed clear time-varying characteristics and has risen sharply since the beginning of 2020, intensifying during the COVID-19 pandemic.…”

Intra-day co-movements of crude oil futures: China and the international benchmarks

“…Moreover, the INE's regulators suspended the night trading session during the first outbreak of the pandemic in order to avoid a catastrophic spillover effect from the global crude oil market. Despite the regulation, Yang et al (2020) indicated a sharp increase in the risk spillover between Chinese and international crude oil futures, and similar findings are also evidenced by Lu et al (2020). Under a context of high-risk fluctuations and strict market regulation, below we evaluate the robustness of pairs trading strategy based on the intra-day co-movement patterns over day trading sessions from January 2 to April 30, 2020.…”

Tail Risk Connectedness in the Refined Petroleum Market: A First Look at the Impact of the COVID Pandemic

“…More recently Antonakakis et al (2020) showed that dynamic connectedness measures based upon TVP-VARs are more accurate than rolling-window VAR retrieved results. With these methodological milestones in mind, in this present study we follow the above mentioned line of existing empirical research and we further extend the applications of said literature by considering tail risk connectedness (see, for example, Yang et al, 2020;Ji et al, 2018;Zhu et al, 2020;Peng et al, 2018;Du and He, 2015). In particular, our methodological approach of tail risk spillover is closely related to Zhang et al (2020) who examine the systemic risk spillovers and connectedness in the sectoral tail risk network of Chinese stock market; Hanif et al (2021) who evaluate tail dependence risk and spillovers between oil prices and food prices and Xu et al (2021) who investigate the tail risk interconnectedness among cryptocurrencies.…”