Central Counterparty Default Waterfalls and Systemic Loss

55 Pages Posted: 16 Jul 2020

See all articles by Mark E. Paddrik

Mark E. Paddrik

Government of the United States of America - Office of Financial Research

Simpson Zhang

Office of Financial Research; Government of the United States of America - Office of the Comptroller of the Currency (OCC)

Date Written: June 18, 2020

Abstract

Central counterparty default waterfalls act as a last line of defense in over-the-counter markets by managing and allocating resources to cover defaults of clearing members and clients. However, central counterparties face competing objectives in setting up their default waterfalls. In this paper we evaluate the trade-offs between default waterfall resiliency and central clearing, using a unique and comprehensive dataset containing all U.S. cleared and bilateral credit default swap positions. We evaluate the resiliency of different waterfall designs, accounting for the interconnectedness of payments in the system, the presence of client clearing obligations for members, and the distribution of losses among market participants.

Keywords: central counterparty, systemic risk, default waterfall, financial networks, credit default swaps

JEL Classification: G10, G23, G28, L14

Suggested Citation

Paddrik, Mark Endel and Zhang, Simpson, Central Counterparty Default Waterfalls and Systemic Loss (June 18, 2020). OFR WP 20-04, Available at SSRN: https://ssrn.com/abstract=3634656 or http://dx.doi.org/10.2139/ssrn.3634656

Mark Endel Paddrik (Contact Author)

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Simpson Zhang

Office of Financial Research ( email )

717 14th Street, NW
Washington, DC 20220
United States

Government of the United States of America - Office of the Comptroller of the Currency (OCC) ( email )

400 7th Street SW
Washington, DC 20219
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
115
Abstract Views
784
Rank
461,362
PlumX Metrics