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Risk spillover networks in financial system based on information theory

机译:基于信息理论的金融系统风险溢出网络

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Since the financial system has illustrated an increasingly prominent characteristic of inextricable connections, information theory is gradually utilized to study the financial system. By collecting the daily data of industry index (2005-2020) and region index (2012-2020) listed in China as samples, this paper applies an innovative measure named partial mutual information on mixed embedding to generate directed networks. Based on the analysis of nonlinear relationships among sectors, this paper realizes the accurate construction of “time-varying” financial network from the perspective of risk spillover. The results are presented as follow: (1) interactions can be better understood through the nonlinear networks among distinct sectors, and sectors in the networks could be classified into different types according to their topological properties connected to risk spillover; (2) in the rising stage, information is transmitted rapidly in the network, so the risk is fast diffused and absorbed; (3) in the declining stage, the network topology is more complex and panic sentiments have long term impact leading to more connections; (4) The US market, Japan market and Hongkong market have significant affect on China’s market. The results suggest that this nonlinear measure is an effective approach to develop financial networks and explore the mechanism of risk spillover.
机译:由于金融体系已经说明了不可明确的联系的越来越突出的特征,因此逐渐利用信息理论来研究金融系统。通过收集中国作为样品中列出的产业指数(2005-2020)和地区指数(2012-2020)的日常数据,本文适用于混合嵌入的部分互信息的创新措施,以生成导向网络。基于部门之间非线性关系的分析,本文从风险溢出的角度意识到“时变”金融网络的准确构建。结果呈现如下:(1)通过非线性网络之间的非线性网络可以更好地理解相互作用,并且网络中的扇区可以根据与风险溢出的拓扑特性分类为不同的类型; (2)在上升阶段,信息在网络中快速传输,因此风险快速扩散和吸收; (3)在下降阶段,网络拓扑更复杂,恐慌情绪长期影响导致更多的联系; (4)美国市场,日本市场和香港市场对中国市场有重大影响。结果表明,这种非线性措施是开发金融网络的有效方法,探索风险溢出机制。

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