An optimization-based approach to central counterparty collateral determination

In financial markets, central counterparties (CCP) play a crucial role by managing counterparty risk through collateral requirements. This study proposes a framework for modeling a CCP’s optimization problem to describe observed collateral requirements. Two models are developed: the profit-maximizing model, wherein the CCP operates as a profit-maximizing firm; and member club model, wherein it acts as members’ profit maximizing entity by minimizing cost. The resulting optimal collateral formulae indicate that the collateral requirement depends on the clearing fees in the profit-maximizing model, while it depends on members’ funding costs for posting collateral in the member club model. Model parameters are calibrated using data on actual collateral requirements from the world’s representative clearing houses over the period from 2013 to 2023 divided by the CCP’s ownership structure. The results show that the proposed optimization framework successfully explains observed collateral requirements. The findings are consistent across clearing houses and robust over time, showing that the member club model better describes the actual CCP collateral setting behavior than the profit-maximizing model. • Model collateral decisions using alternative behavioral assumptions for central counterparties. • Analyze how fee and cost incentives shape optimal collateral determination. • Compare shareholder- and member-oriented models of clearing behavior using real data. • Validate the predictive performance of collateral models through calibration and model prediction. • Highlight how clearing incentives influence market design and participant decisions.