Central Counterparties. A Numerical Implementation of the Default Waterfall

Abstract

This thesis studies so called Central Counterparties (CCP), nancial institutions which consist of clearing members, such as large banks. CCPs have the role of centralizing, mutualizing and reducing counterparty risk, by acting as an intermediate in nancial transactions. CCPs have existed for a while, however after the 2007-2009 nancial crisis regulators have pushed for all OTC-derivatives to be cleared by CCPs. In order to be risk mitigating, the CCPs must have su cient funds to be able to absorb losses from member defaults. To increase the resilience of the CCP, the loss-absorbing safety bu er exists in several layers, often denoted as the default waterfall. In this thesis we numerically implement the CCP model by Ghamami (2015). We use two di erent static credit models to quantify the various layers of the default waterfall. Our model is found to adjust to di erent default probabilities and default correlations by increasing the fund requirements in stressed scenarios in both settings. Finally, we perform a sensitivity analysis in which we change the number of clearing members, the time period considered and the interest rate setting. In each stress test the model reacts to extreme scenarios by increasing the layers accordingly.