Abstract: We provide a framework for modelling risk and quantifying payment shortfalls in cleared markets with multiple central counterparties (CCPs). Building on the stylised fact that clearing membership is shared among CCPs, we develop a modelling framework that captures the interconnectedness of CCPs and clearing members. We illustrate stress transmission mechanisms using simple examples as well as empirical evidence based on calibrated data. Furthermore, we show how stress mitigation tools such as variation margin gains haircutting by one CCP can have spillover effects on other CCPs. The framework can be used to enhance CCP stress-testing, which currently relies on the ``Cover 2'' standard requiring CCPs to be able to withstand the default of their two largest clearing members. We show that who these two clearing members are can be significantly affected if one considers higher-order effects arising from interconnectedness through shared clearing membership. Looking at the full network of CCPs and shared clearing members is therefore important from a financial stability perspective.
This is joint work with Inaki Aldasoro (BIS).
 
Bio: 
Luitgard Veraart is a Professor in the Department of Mathematics at the London School of Economics and Political Science. Her research interests are in financial mathematics and statistics in finance. One special focus of her research is on problems related to risk management in financial markets and systemic risk.
She is the co-winner of the 2019 Adams Prize for achievement in the field of Mathematics of Networks. From 01/2022-12/2023, she serves as the Vice Chair of the SIAM Activity Group on Financial Mathematics and Engineering. 
Prior to joining LSE in 2010, she has been an Assistant Professor of Financial Mathematics at the Karlsruhe Institute of Technology and a Postdoctoral Research Associate at the Bendheim Centre for Finance, Princeton University. She has a PhD in Mathematics from the University of Cambridge.

Zoom：
https://zoom.us/j/87190189710?pwd=UkJsTXZWWGFFaGhjSnpWcndFVVljUT09
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