部门间的相互依赖导致带符号金融网络中结构平衡的丧失
Sectoral inter-dependencies drive the loss of structural balance in signed financial networks
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中文总结 AI 辅助
本研究基于标普500指数数据，采用结构平衡理论框架，揭示系统性风险时期带符号金融网络的结构失衡主要源于部门间相互作用，且全球极化方差可由宏观经济变量解释，为理解危机期金融网络结构不稳定提供定量框架。
中文摘要 AI 辅助
带符号图为描绘合作与冲突共存的系统提供了有效架构，该概念源于心理科学中的平衡概念，已在多个领域得到应用，金融市场便是其中一例，可通过带符号网络建模，其中资产价格变动存在相关性。在系统性风险时期，这类带符号金融网络会出现平衡丧失的现象，这一点已得到一致证实。本文探究这种结构失衡如何在金融网络的不同尺度上分布，揭示其介观起源。采用结构平衡理论框架，我们基于三元 motif 构建极化度量，以研究不同部门尺度下结构失衡的分布情况。利用来自标普500指数的纵向数据，分析全球极化及其部门构成的时间演化。通过将全球极化分解为部门内和部门间构成部分，我们表明，在系统性风险时期，结构失衡主要源于部门间的相互作用，而非部门内部。我们采用随机化协议证实，观测到的失衡配置具有统计显著性，并非低阶相互作用的人为产物。我们推导了一个回归方程，表明宏观经济变量能很好地解释全球极化的方差，说明经济危机期间较低的全球极化水平是由供应链中断和通胀不确定性的复合压力驱动的。总体而言，这些发现为理解局部部门冲突如何在金融网络中传播，并在经济危机时期促成大规模结构不稳定提供了定量框架。
英文摘要
Signed graphs provide an effective architecture for portraying a system in which cooperation and conflict coexist. Emerging from the concept of balance in psychological sciences, they have found applications across several domains. Financial markets are one such example that can be modeled using signed networks, where assets exhibit correlations in price movements. During periods of systemic risk, such a signed financial network shows a loss of balance, which has been consistently demonstrated. Here, we explore how this structural imbalance is distributed across scales within the financial network, revealing its mesoscopic origin. Adopting the framework of structural balance theory, we use a measure of polarization based on triadic motifs to investigate the distribution of structural imbalance across varying sectoral scales. We analyze the temporal evolution of global polarization and its sectoral constituents using longitudinal data derived from the S&P 500 index. By decomposing global polarization into intra-sectoral and inter-sectoral constituents, we show that structural imbalance arises predominantly from interactions between sectors rather than within them during periods marked by systemic risk. We employ randomization protocols to confirm that observed imbalance configurations are statistically significant and not artifacts of lower-order interactions. We derive a regression equation demonstrating that the variance in global polarization is well explained by macroeconomic variables, indicating that low levels of global polarization during economic crises are driven by compounding pressures from supply chain disruptions and inflation uncertainty. Collectively, these findings provide a quantitative framework for understanding how localized sectoral conflicts propagate across the financial network and contribute to large-scale structural instability during periods of economic crisis.
