英文标题：
《Elimination of systemic risk in financial networks by means of a
systemic risk transaction tax》
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作者：
Sebastian Poledna and Stefan Thurner
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最新提交年份：
2016
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英文摘要：
Financial markets are exposed to systemic risk (SR), the risk that a major fraction of the system ceases to function, and collapses. It has recently become possible to quantify SR in terms of underlying financial networks where nodes represent financial institutions, and links capture the size and maturity of assets (loans), liabilities, and other obligations, such as derivatives. We demonstrate that it is possible to quantify the share of SR that individual liabilities within a financial network contribute to the overall SR. We use empirical data of nationwide interbank liabilities to show that the marginal contribution to overall SR of liabilities for a given size varies by a factor of a thousand. We propose a tax on individual transactions that is proportional to their marginal contribution to overall SR. If a transaction does not increase SR it is tax-free. With an agent-based model (CRISIS macro-financial model) we demonstrate that the proposed \"Systemic Risk Tax\" (SRT) leads to a self-organised restructuring of financial networks that are practically free of SR. The SRT can be seen as an insurance for the public against costs arising from cascading failure. ABM predictions are shown to be in remarkable agreement with the empirical data and can be used to understand the relation of credit risk and SR.
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中文摘要：
金融市场面临着系统性风险（SR），即系统的大部分停止运行并崩溃的风险。最近，可以根据基础金融网络对SR进行量化，其中节点代表金融机构，链接捕获资产（贷款）、负债和其他义务（如衍生工具）的规模和到期日。我们证明，可以量化金融网络中的个别负债对整体SR的贡献的SR份额。我们使用全国性银行间负债的经验数据表明，给定规模的负债对整体SR的边际贡献变化了1000倍。我们建议对单个交易征税，该税与其对总SR的边际贡献成比例。如果交易不增加SR，则免税。通过基于主体的模型（危机宏观金融模型），我们证明了拟议的“系统性风险税”（SRT）会导致金融网络的自组织重组，而这种重组实际上不受SR的影响。SRT可以被视为公众对级联故障产生的成本的保险。ABM预测结果与经验数据非常吻合，可以用来理解信用风险与SR的关系。
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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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