Evaluating the connectedness of commodity future markets via the cross-correlation network - Hou, Lei; Pan, Yueling (Frontiers in Physics, 2022)
Financial markets are widely believed to be complex systems where interdependencies exist among individual entities in the system enabling the risk spillover effect. The detrended cross-correlation analysis (DCCA) has found wide applications in examining the comovement of fluctuations among financial time series. However, to what extent can such cross-correlation represents the spillover effect is still unknown. This paper constructs DCCA network of commodity futures markets and explores its proximity to the volatility spillover network. Results show a moderate agreement between the two networks. Centrality measures applied to the DCCA networks are able to identify key commodity futures that are transmitting or receiving risk spillovers. The evolution of DCCA network reveals a significant change in the network structure during the COVID-19 pandemic in comparison to that of the pre- and post-pandemic period. The pandemic made the commodity futures markets more interconnected leading to a shorter diameter for the network. The intensified connections happen mostly between commodities from different categories. Accordingly, cross-category risk spillovers are more likely to happen during the pandemic. The analysis enriches the applications of DCCA approach and provides useful insights for understanding the risk dynamics in commodity futures markets.