在多层金融网络中隐藏社区溢出检测:对多层网络的层次集群的概括
Jamshid Ardalankia1,2, Ali Habibnia1,2, Marcel Ausloos3,4,5,6
1Department of Economics, Virginia Tech, Blacksburg, Virginia, United States of America.
PloS one
|September 3, 2025
概括
相互依赖的网络通过结构性溢出揭示了隐藏的社区结构. 我们的模型揭示了多层网络中的隐藏联系和结构,
科学领域:
- 网络科学
- 金融数学
- 复杂的系统
背景情况:
- 相互依赖的网络表现出结构性的影响,其中一个网络 (源) 可以对另一个网络 (目标) 施加隐藏的社区结构.
- 传统的社区检测方法往往无法识别这些层间影响和隐藏的结构.
- 金融市场表现出层次之间的复杂,经常隐藏的不对称相互作用.
研究的目的:
- 为分析多层网络中隐藏的社区结构提出数学模型.
- 使用层间相似性函数对多层网络进行层次集群的概括.
- 研究源网络的结构性溢出如何在目标网络中产生隐藏的社区结构.
主要方法:
- 开发一个包含层间相似性函数的数学模型.
- 用于多层网络分析的层次聚类的一般化.
- 在多层金融网络上实施该模型,以交易价值变化为来源,价格回报为目标.
主要成果:
- 该模型成功地识别了源网络所强加的目标网络中的隐藏社区结构.
- 隐藏的层间互动在目标网络上产生隐藏的链接和独特的社区结构.
- 在金融市场,交易价值的逻辑变化给价格回报网络带来了隐藏的社区结构.
结论:
- 增加相关层面,比如交易价值, 提供有关价格回报网络系统行为的关键信息.
- 忽视这些层可能会导致低估由于未被发现的结构足迹的系统性风险.
- 通过揭示隐藏的层间影响,该方法为投资组合多样化提供了新的视角.
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