Correlation Breakdowns, Spread Positions, and CCP Margin Models

The default of a participant at Nasdaq Clearing in 2018 and the recent COVID-19 events brought to the attention of risk managers at CCPs the importance of appropriately measuring correlation breakdowns. The sizable price dislocations registered on these occasions suggested that traditional risk models may not be fully equipped to capture the breakdowns. Because correlations are directly impacted by the statistical properties of each variable, any model that lacks the capacity to deal with non-stationarity may inappropriately represent correlation or its alterations. Using a GARCH-DCC approach to accommodate such properties, the objective of the paper is to study the correlation behaviour during adverse market conditions, and the potential subsequent impact to CCP margins. A study case for energy commodities is proposed, with the specific focus on spread positions for the electricity market. The analysis suggests that the correlation breakdowns are more frequent than traditionally expected. When different types of shocks are considered (i.e. September 2018 and March-May 2020), it becomes evident that while the magnitude of the breakdown may differ, its cycle presents a number of similarities. While elevated margin due to correlation breakdown may reduce breaching amount and improve margin coverage rate, this paper also recognizes the potentially increased margin procyclicality, and highlights the challenge of balancing margin responsiveness and stability during correlation breakdown for spread positions, and calls for further study in this area.