ABSTRACT
The extant literature has explored the linkages between the onshore (CNY) and offshore (CNH) Renminbi (RMB) markets, as well as the potential factors affecting their dynamic inter-relationship. However, these efforts were made on a stand-alone basis in terms of dimensions and perspectives. This paper hence adopts the wavelet methodology to comprehensively examine the CNY-CNH interactions over 2010–2022. We find information spillovers across the two RMB markets to be bi-directional and asymmetric, with the exact pattern depending upon the particular sample period and the focal data frequency. Moreover, major macroeconomic events such as China's exchange rate reform, US-China trade tensions, COVID-19 pandemic, and more recent global uncertainty can exert distinct impacts on the flow pattern of information. We further show that the CNY-CNH exchange rate difference alone serves as a key indicator for the complex relationship between the two markets. As expected, the CNH market is more sensitive to exchange rate difference fluctuations, indicating a powerful market mechanism in the offshore RMB market, or equivalently, a substantial policy impact of the counter-cyclical adjustment by China's central bank in stabilizing the RMB rate. © 2023 Elsevier Ltd
ABSTRACT
Jumps in commodity prices can make asset risk management challenging. This study explores the influence feature of the COVID-19 epidemic on China's commodity price jumps, using 5-min intraday high-frequency futures data of three China's commodity markets (energy, chemical, and metal) from January 23, 2020 to June 10, 2022. We find that firstly the information spillover from the COVID-19 spread situation to China's energy price jumps is relatively weak, and the COVID-19 epidemic shows the most substantial jump information spillover pattern to China's chemical price. The information spillover pattern is time-varying across the COVID-19 spread situation phase. Secondly, there are co-movement patterns between China's commodity price and China/global COVID-19 confirmed cases. This co-movement feature mainly occurs at the medium- or long-run time scales, and varies across commodities. Thirdly, the demand elasticity for China's commodities and its dependence on imports and exports are the main factors influencing the sensitivity of its price jumps to the COVID-19 outbreak.
ABSTRACT
Applying the TVP-VAR model, we creatively construct multilayer information spillover networks containing return spillover layer, volatility spillover layer and extreme risk spillover layer among 23 countries in the G20 to explore international sovereign risk spillovers. From the perspective of system-level and country-level measures, this article explores the topological structures of static and dynamic multilayer networks. We observe that (i) at the system-level, multilayer measures containing uniqueness edge ratio and average edge overlap show each layer has unique network structures and spillover evolution behavior, especially for dynamic networks. Average connectedness strength shows volatility and extreme risk spillover layers are more sensitive to extreme events. Meanwhile, three layers have highly intertwined and interrelated relations. Notably, their spillovers all show a great upsurge during the crisis (financial and European debt crisis) and the COVID-19 pandemic period. (ii) At the country-level, average overlapping net-strength shows that countries’ roles are different during distinct periods. Multiplex participation coefficient on out-strength indicates we’ll focus on countries with highly heterogeneous connectedness among three layers during the stable period since their underestimated spillovers soar in extreme events or crises. Multilayer networks supply comprehensive information that cannot obtain by single-layer.
ABSTRACT
This paper examines the relationship between world crude oil markets following the introduction of Shanghai crude oil futures from the perspective of network connectedness based on the vector autoregressive model. The connectedness measurement method proposed by Diebold and Yilmaz (Econ J 119(534):158-171, 2009, Int J Forecast 28(1):57-66, 2012. 10.1016/j.ijforecast.2011.02.006, J Econom 182(1):119-134, 2014. 10.1016/j.jeconom.2014.04.012) is adopted to study a time-varying interdependence relationship. The empirical results show that the world crude oil markets exhibit a high degree of integration from both returns and volatility; however, the direction and magnitude contributed by each market varies significantly. Specifically, the West Texas Intermediate futures and Brent spot and futures markets were found to have the highest contributions to the world oil market over the entire sample period and take leading roles, whereas Dubai futures market was found to be the most important receiver, and has received the most spillover from other markets and passed it throughout the system. Shanghai crude oil futures is not yet highly connected with other markets. Moreover, heterogeneous changes in the direction, intensity, and persistence of the spillover were observed across markets after the outbreak of the COVID-19 pandemic in 2020. This study reveals the integration level of Shanghai crude oil futures and the dynamics of linkages between regional crude oil markets, which is of great significance for market participants, policymakers, and future researchers. Supplementary Information: The online version contains supplementary material available at 10.1007/s12076-021-00288-z.