A Dynamic Contagion Risk Model With Recovery Features

H. Amini, Andreea Minca, A. Sulem
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引用次数: 6

Abstract

We introduce threshold growth in the classical threshold contagion model, or equivalently a network of Cramér-Lundberg processes in which nodes have downward jumps when there is a failure of a neighboring node. Choosing the configuration model as underlying graph, we prove fluid limits for the baseline model, as well as extensions to the directed case, state-dependent interarrival times and the case of growth driven by upward jumps. We obtain explicit ruin probabilities for the nodes according to their characteristics: initial threshold and in- (and out-) degree. We then allow nodes to choose their connectivity by trading off link benefits and contagion risk. We define a rational equilibrium concept in which nodes choose their connectivity according to an expected failure probability of any given link and then impose condition that the expected failure probability coincides with the actual failure probability under the optimal connectivity. We show existence of an asymptotic equilibrium and convergence of the sequence of equilibria on the finite networks. In particular, our results show that systems with higher overall growth may have higher failure probability in equilibrium.
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具有恢复特征的动态传染风险模型
我们在经典的阈值传染模型中引入了阈值增长,或者等效的cram - lundberg过程网络,其中当相邻节点出现故障时,节点会向下跳跃。选择配置模型作为基础图,我们证明了基线模型的流体极限,以及对有向情况、状态依赖的到达间隔时间和由向上跳跃驱动的增长情况的扩展。根据节点的初始阈值和入(出)度特征,得到节点的显式破产概率。然后,我们允许节点通过权衡链接收益和传染风险来选择它们的连接性。我们定义了一个合理的平衡概念,节点根据任意给定链路的期望失效概率选择其连通性,并在最优连通性下设定期望失效概率与实际失效概率重合的条件。证明了有限网络上平衡点序列的收敛性和渐近平衡点的存在性。特别是,我们的研究结果表明,系统的总体增长率越高,在平衡状态下的失效概率就越高。
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