Margin-setting by Central Counterparties of over-the-counter derivatives
Chen Zhang
Abstract
Open-access reader
Chen Zhang
Abstract
Open-access reader
Regulation of the over-the-counter (OTC) derivatives market since the financial crisis of 2008 has had the objective of reducing risks within this marketplace. OTC derivatives are now cleared through central clearing counterparties (CCPs), and one tool of the CCPs is to set adequate margin requirements for their clearing members. In this thesis, I address the obligations of CCPs and the effect of risk management using margin requirements. I develop the methodology of margin setting using a historical simulation and evaluate the resulting risk-based margin requirements for interest rate swaps. I also address an important aspect of margin-setting which is margin procyclicality, under which margin requirements are increased in stressed markets resulting in an increased risk of default on margin calls as well as feedback effects on the underlying assets of clearing members.
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Regulation of the over-the-counter (OTC) derivatives market since the financial crisis of 2008 has had the objective of reducing risks within this marketplace. OTC derivatives are now cleared through central clearing counterparties (CCPs), and one tool of the CCPs is to set adequate margin requirements for their clearing members. In this thesis, I address the obligations of CCPs and the effect of risk management using margin requirements. I develop the methodology of margin setting using a historical simulation and evaluate the resulting risk-based margin requirements for interest rate swaps. I also address an important aspect of margin-setting which is margin procyclicality, under which margin requirements are increased in stressed markets resulting in an increased risk of default on margin calls as well as feedback effects on the underlying assets of clearing members.
Key concepts: Margin (machine learning), Clearing, Clearance, Derivatives market, Business, Collateral, Net interest margin, Actuarial science