Asymmetric Network Connectedness of Fears

• 成果类型: Article
• 署名作者: Barunik, Jozef; Bevilacqua, Mattia; Tunaru, Radu
• 署名单位: Czech Academy of Sciences; Institute of Information Theory & Automation of the Czech Academy of Sciences; Charles University Prague; University of London; London School Economics & Political Science; University of Sussex
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_01003
• 发表日期: 2022-11
• 页码: 1304-1316
• 关键词: systemic risk; volatility; STOCK; uncertainty; return; MODEL; bad

摘要

This paper introduces forward-looking measures of the network connectedness of fears in the financial system arising due to the good and bad beliefs of market participants about uncertainty that spreads unequally across a network of banks. We argue that this asymmetric network structure extracted from call and put traded option prices of the main U.S. banks contains valuable information for predicting macroeconomic conditions and economic uncertainty, and it can serve as a tool for forward-looking systemic risk monitoring.