英文标题：
《Network versus portfolio structure in financial systems》
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作者：
Teruyoshi Kobayashi
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最新提交年份：
2013
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英文摘要：
The question of how to stabilize financial systems has attracted considerable attention since the global financial crisis of 2007-2009. Recently, Beale et al. (\"Individual versus systemic risk and the regulator\'s dilemma\", Proc Natl Acad Sci USA 108: 12647-12652, 2011) demonstrated that higher portfolio diversity among banks would reduce systemic risk by decreasing the risk of simultaneous defaults at the expense of a higher likelihood of individual defaults. In practice, however, a bank default has an externality in that it undermines other banks\' balance sheets. This paper explores how each of these different sources of risk, simultaneity risk and externality, contributes to systemic risk. The results show that the allocation of external assets that minimizes systemic risk varies with the topology of the financial network as long as asset returns have negative correlations. In the model, a well-known centrality measure, PageRank, reflects an appropriately defined \"infectiveness\" of a bank. An important result is that the most infective bank need not always be the safest bank. Under certain circumstances, the most infective node should act as a firewall to prevent large-scale collective defaults. The introduction of a counteractive portfolio structure will significantly reduce systemic risk.
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中文摘要：
自2007-2009年全球金融危机以来，如何稳定金融体系的问题引起了相当大的关注。最近，Beale等人（Proc Natl Acad Sci USA 108:12647-126522011《个人与系统风险与监管者的困境》）证明，银行间更高的投资组合多样性将通过降低同时违约的风险而降低系统风险，同时降低个人违约的可能性。然而，在实践中，银行违约具有外部性，因为它会破坏其他银行的资产负债表。本文探讨了这些不同的风险来源，即同时性风险和外部性，是如何导致系统性风险的。结果表明，只要资产收益率具有负相关性，将系统性风险降至最低的外部资产配置就会随着金融网络的拓扑结构而变化。在该模型中，一个著名的中心性度量PageRank反映了银行的一个恰当定义的“传染性”。一个重要的结果是，最具感染力的银行不一定总是最安全的银行。在某些情况下，最具感染力的节点应该充当防火墙，以防止大规模集体违约。引入抵消性投资组合结构将显著降低系统性风险。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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