Stability Analysis of Financial Contagion Due to Overlapping Portfolios
Stability Analysis of Financial Contagion Due to Overlapping Portfolios
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DOI：
10.2139/ssrn.2176080
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发表时间：
2012-10
期刊：
影响因子：
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通讯作者：
F. Caccioli;Munik Shrestha;Cristopher Moore;J. Farmer
中科院分区：
文献类型：
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作者：
F. Caccioli;Munik Shrestha;Cristopher Moore;J. Farmer
人们普遍认为，共同资产持有是最近金融危机蔓延的主要媒介。我们开发了一个网络的方法来放大的金融传染，由于重叠的投资组合和杠杆的组合，我们展示了如何可以理解的广义分支过程。这可以用来计算任何特定投资组合配置的稳定性。通过研究一个程式化的模型，我们估计的情况下，系统的不稳定性可能发生的参数，如杠杆，市场拥挤，多元化，市场影响的函数。尽管多样化可能对个别机构有利，但它可能产生危险的系统性影响，结果是，金融传染病随着过度多样化而变得更糟。杠杆率有一个临界阈值;低于这个阈值的金融网络总是稳定的，高于这个阈值的不稳定区域随着杠杆率的增加而增长。请注意，我们的模型假设在危机期间进行被动的投资组合管理;然而，我们表明，危机期间的动态去杠杆化会放大不稳定性。金融系统表现出“稳健但脆弱”的行为，在参数空间的某些区域，传染是罕见的，但无论何时发生，都是灾难性的。我们的模型和分析方法可以根据真实的数据进行校准，并为宏观审慎压力测试提供简单而强大的工具。
Common asset holdings are widely believed to have been the primary vector of contagion in the recent financial crisis. We develop a network approach to the amplification of financial contagion due to the combination of overlapping portfolios and leverage, and we show how it can be understood in terms of a generalized branching process. This can be used to compute the stability for any particular configuration of portfolios. By studying a stylized model we estimate the circumstances under which systemic instabilities are likely to occur as a function of parameters such as leverage, market crowding, diversification, and market impact. Although diversification may be good for individual institutions, it can create dangerous systemic effects, and as a result financial contagion gets worse with too much diversification. There is a critical threshold for leverage; below it financial networks are always stable, and above it the unstable region grows as leverage increases. Note that our model assumes passive portfolio management during a crisis; however, we show that dynamic deleveraging during a crisis can amplify instabilities. The financial system exhibits “robust yet fragile” behavior, with regions of the parameter space where contagion is rare but catastrophic whenever it occurs. Our model and methods of analysis can be calibrated to real data and provide simple yet powerful tools for macroprudential stress testing.