英文标题：
《Double Cascade Model of Financial Crises》
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作者：
Thomas R. Hurd, Davide Cellai, Sergey Melnik, Quentin Shao
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最新提交年份：
2016
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英文摘要：
The scope of financial systemic risk research encompasses a wide range of interbank channels and effects, including asset correlation shocks, default contagion, illiquidity contagion, and asset fire sales. This paper introduces a financial network model that combines the default and liquidity stress mechanisms into a \"double cascade mapping\". The progress and eventual result of the crisis is obtained by iterating this mapping to its fixed point. Unlike simpler models, this model can therefore quantify how illiquidity or default of one bank influences the overall level of liquidity stress and default in the system. Large-network asymptotic cascade mapping formulas are derived that can be used for efficient network computations of the double cascade. Numerical experiments then demonstrate that these asymptotic formulas agree qualitatively with Monte Carlo results for large finite networks, and quantitatively except when the initial system is placed in an exceptional \"knife-edge\" configuration. The experiments clearly support the main conclusion that when banks respond to liquidity stress by hoarding liquidity, then in the absence of asset fire sales, the level of defaults in a financial network is negatively related to the strength of bank liquidity hoarding and the eventual level of stress in the network.
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中文摘要：
金融系统风险研究的范围包括广泛的银行间渠道和影响，包括资产相关性冲击、违约传染、流动性不足传染和资产抛售。本文介绍了一个金融网络模型，该模型将违约和流动性压力机制结合成一个“双级联映射”。通过将该映射迭代到其固定点，可以获得危机的进展和最终结果。与更简单的模型不同，该模型因此可以量化一家银行的流动性不足或违约如何影响系统中流动性压力和违约的总体水平。导出了大网络渐近级联映射公式，可用于双级联的高效网络计算。数值实验表明，这些渐近公式在定性上与大型有限网络的蒙特卡罗结果一致，在定量上与蒙特卡罗结果一致，除非初始系统处于特殊的“刀口”配置。这些实验清楚地支持了一个主要结论，即当银行通过囤积流动性来应对流动性压力时，在没有资产抛售的情况下，金融网络中的违约水平与银行流动性囤积的强度以及网络中的最终压力水平呈负相关。
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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
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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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