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英文标题:
《Cascades in multiplex financial networks with debts of different seniority》 --- 作者: Charles D. Brummitt, Teruyoshi Kobayashi --- 最新提交年份: 2015 --- 英文摘要: The seniority of debt, which determines the order in which a bankrupt institution repays its debts, is an important and sometimes contentious feature of financial crises, yet its impact on system-wide stability is not well understood. We capture seniority of debt in a multiplex network, a graph of nodes connected by multiple types of edges. Here, an edge between banks denotes a debt contract of a certain level of seniority. Next we study cascading default. There exist multiple kinds of bankruptcy, indexed by the highest level of seniority at which a bank cannot repay all its debts. Self-interested banks would prefer that all their loans be made at the most senior level. However, mixing debts of different seniority levels makes the system more stable, in that it shrinks the set of network densities for which bankruptcies spread widely. We compute the optimal ratio of senior to junior debts, which we call the optimal seniority ratio, for two uncorrelated Erdos-Renyi networks. If institutions erode their buffer against insolvency, then this optimal seniority ratio rises; in other words, if default thresholds fall, then more loans should be senior. We generalize the analytical results to arbitrarily many levels of seniority and to heavy-tailed degree distributions. --- 中文摘要: 债务的优先级决定了破产机构偿还债务的顺序,这是金融危机的一个重要特征,有时也会引起争议,但它对全系统稳定的影响尚不清楚。我们在一个多重网络中捕捉债务的优先级,这是一个由多种类型的边连接的节点图。在这里,银行之间的优势表示具有一定资历的债务合同。接下来我们研究级联缺剩存在多种破产类型,以银行无法偿还所有债务的最高资历为指标。自私自利的银行更希望所有贷款都由最高层发放。然而,混合不同资历级别的债务可以使系统更加稳定,因为它缩小了破产广泛传播的网络密度。我们计算了两个不相关的鄂尔多斯-仁义网络的最优优先债务比率,我们称之为最优优先债务比率。如果机构削弱了它们对破产的缓冲,那么这个最佳资历比率就会上升;换句话说,如果违约门槛下降,那么更多的贷款应该优先。我们将分析结果推广到任意多个级别的资历和重尾度分布。 --- 分类信息: 一级分类:Quantitative Finance 数量金融学 二级分类:General Finance 一般财务 分类描述:Development of general quantitative methodologies with applications in finance 通用定量方法的发展及其在金融中的应用 -- 一级分类:Physics 物理学 二级分类:Physics and Society 物理学与社会 分类描述:Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks). 社会和团体(人类或其他)的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统(如能源网、运输网络)的物理和工程。 -- --- PDF下载: --> |
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