Central Clearing and Systemic Risk

Abstract

The G20's push towards central clearing changed the shape of the world's financial system: all standardized derivative contracts must now be cleared through central counterparties (CCPs). Despite considerable debate, the impact of central clearing nonetheless remains ambiguous and hard to measure as clearing regulations have been implemented alongside many other changes. In the present paper, we isolate the impact of CCPs by first representing all trade and risk relations of a financial system in a graph model. We then formalize clearing as an operator on those graphs and obtain sharp a priori bounds of its effect on total risk levels. Using numerical simulation, we then show how clearing alters the credit risk exposures of each bank depending on the netting structure of its trades. Further, we demonstrate how CCPs only reduce the total levels of risk in the system if their credit quality is substantially higher than that of the banks. We show, paradoxically, how the CCPs expose the system to substantial concentration risk and thereby undermine their initial purpose.

Keywords: Central Clearing, Systemic Risk, Financial Regulation, Graph Model, Simulation, Data Science, Credit Risk

JEL Classification: G01, G18, G28