清理
抵押品
边距(机器学习)
衍生品市场
业务
系统性风险
理论(学习稳定性)
违约概率
外部性
精算学
计算机科学
计量经济学
信用风险
经济
财务
微观经济学
期货合约
金融危机
机器学习
宏观经济学
作者
Jorge Cruz Lopez,Jeffrey H. Harris,Christophe Hurlin,Christophe Pérignon
标识
DOI:10.1017/s0022109017000709
摘要
We present CoMargin, a new methodology to estimate collateral requirements in derivatives central counterparties (CCPs). CoMargin depends on both the tail risk of a given market participant and its interdependence with other participants. Our approach internalizes trading externalities and enhances the stability of CCPs, thus reducing systemic risk concerns. We assess our methodology using proprietary data from the Canadian Derivatives Clearing Corporation that include daily observations of the actual trading positions of all of its members from 2003 to 2011. We show that CoMargin outperforms existing margining systems by stabilizing the probability and minimizing the shortfall of simultaneous margin-exceeding losses.
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