论文标题
因果图案和有指导网络中内源性级联的存在，并应用于公司默认值
Causal motifs and existence of endogenous cascades in directed networks with application to company defaults
论文作者
论文摘要
由于经济中级联的检测，我们开发了一个基于本文中定义的因果主题的内源性传播的检测框架。我们假设可以通过内源性或外源性事件触发顶点状态的变化，即基础网络是指向基础网络的，而当顶点改变状态的时间可用。除了公司默认值的数据外，我们还模拟了由不同合成网络上不同随机过程驱动的级联反应。我们表明，一些最小的基序可以牢固地检测到内源性扩散事件。最后，我们将方法应用于克罗地亚公司默认数据的数据，并观察可能发生内源性级联的时间窗口。
Motivated by the detection of cascades of defaults in economy, we developed a detection framework for an endogenous spreading based on causal motifs we define in this paper. We assume that the change of state of a vertex can be triggered by an endogenous or an exogenous event, that the underlying network is directed and that times when vertices changed their states are available. In addition to the data of company defaults, we also simulate cascades driven by different stochastic processes on different synthetic networks. We show that some of the smallest motifs can robustly detect endogenous spreading events. Finally, we apply the method to the data of defaults of Croatian companies and observe the time window in which an endogenous cascade was likely happening.
