{'fraction_non_alphanumeric': 0.018083182640144666, 'fraction_numerical': 0.0216998191681736, 'mean_word_length': 5.219101123595506, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Measuring the Systemic Risk of China’s Banking Sector: An Application of Differential Debtrank

This paper investigates the systemic risk of China’s banking sector via network analysis and differential DebtRank from 2007 to 2016. The interbank network of each year is constructed by means of the yearly interbank assets and liabilities of twenty-eight Chinese banks. The results show that the twenty-eight banks in China are closely connected through interbank networks. We compute the risk contribution of each bank and the expected systemic losses by using the differential DebtRank method. We find that the interconnectedness of a bank is highly significant to its systemic risk: banks with high eigenvector centrality contribute more systemic risk. Banks with high returns on assets and low liquidity also contribute more systemic risk. The overall systemic risk changes over time and reaches high levels in 2007, 2008, 2011 and 2012. In high-risk years, the risk contribution of small-scale banks significantly increases. Our results offer novel insights with reference to macroprudential supervision.