This paper studies the risk spreading ability of cryptocurrencies and their contribution to the systemic risk during the period from 2018 to 2022. Three different network centrality approaches are employed to measure the risk spreading ability of cryptocurrencies both in breadth and depth, and...

A novel approach of gravity strength centrality (GSC) model is proposed to identify the influential risk spreaders in cryptocurrency networks. We also validate the performance of GSC model in terms of discrimination and accuracy using methods such as individuation rate, imprecision function, and...

Using the non-parametric thermal optimal path method, we investigate the dynamic lead-lag relationship between carbon emission trading and stock markets in China, and further consider the impact of different types of exogenous shocks on the lead-lag relationship. The empirical results show that...

The immense attention on climate change has stimulated increasing interest in carbon market and their linkages to other markets. This study mainly investigates the dynamic risk spillover relationships between the Chinese carbon and international energy markets, and the impact of extreme weather...

This paper examines the evolution of industrial structure change of China in a long run from 2008 to 2020 based on the analysis of stock and sector networks. First, by analyzing the stock network of China, we find that stocks with great impact on the market usually belong to industries that are...