A cost–benefit analysis of anti-procyclicality: analyzing approaches to procyclicality reduction in central counterparty initial margin models

Following a period of relative calm, many derivative users received large margin calls as financial market volatility spiked amidst the onset of the Covid-19 global pandemic in March 2020. This reinvigorated the policy debate about dampening such “procyclicality” of margin requirements. In this paper, we suggest how margin setters and policy makers might measure procyclicality and target particular levels of it by recalibrating parameters in a margin model to reduce its procyclicality or by applying an anti-procyclicality tool. The different options reduce procyclicality by varying amounts, and do so at different costs, which we measure using the average additional margin required over the cycle. This allows us to perform a cost–benefit analysis of the options. We illustrate this using a commonly used type of initial margin model, called filtered historical simulation value at risk. We present the costs and benefits of varying a key model parameter and applying a number of different antiprocyclicality tools to this model, including those in EU legislation. Once margin setters have settled on a model design that manages procyclicality at an acceptable cost, we suggest that they should disclose to their counterparties the behavior of their preferred models, including the potential margin calls they generate in stress, as an aid to liquidity planning.