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Elimination of systemic risk in financial networks by means of a systemic risk transaction tax

机译:通过系统性风险交易税消除金融网络中的系统性风险

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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 (ABM) (CRISIS macro-financial model), we demonstrate that the proposed 'Systemic Risk Tax' (SRT) leads to a self-organized 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.
机译:金融市场面临系统性风险(SR),即系统中大部分系统停止运行并崩溃的风险。最近,根据节点代表金融机构的基础金融网络来量化SR成为可能,并且链接捕获资产(贷款),负债和其他义务(例如衍生工具)的大小和期限。我们证明,有可能量化金融网络内单个负债对整体SR的SR份额。我们使用全国银行间负债的经验数据表明,在给定规模下,对负债整体SR的边际贡献变化了千倍。我们建议对单个交易征税,该税应与它们对整体SR的边际贡献成比例。如果交易不增加SR,则免税。使用基于代理的模型(ABM)(CRISIS宏观金融模型),我们证明了拟议的“系统风险税”(SRT)导致金融网络的自组织重组,而这些重组几乎没有SR。 SRT可以看作是防止因连锁故障而产生的费用的公众保险。结果表明,ABM预测与经验数据非常吻合,可用于理解信贷风险与SR的关系。

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