Ice changing margin model for move into options
CCP aims for Q1 2019 roll-out of new Monte Carlo-based methodology as it plans launch of index swaptions
Ice Clear Credit has received regulatory approval to switch from its stress-based initial margin methodology to one based on Monte Carlo simulations – a step, the clearer says, that paves the way for it to launch clearing for options on credit default swaps (CDS) indexes.
The firm is planning to adopt the new method in the first quarter of 2019, having received approval from the US’s Commodities Futures Trading Commission, which regulates index-based over-the-counter derivatives, at the end of October this year. That followed approval from the Securities and Exchange Commission (SEC), which regulates single-name CDSs, earlier in the month.
Ice’s primary motivation for making the switch is its plan to launch CDS index swaptions clearing, Stanislav Ivanov, president of Ice Clear Credit, tells Risk.net. The central counterparty hopes to complete the roll-out next year, but does not have a fixed timetable for doing so.
“To properly capture the risk of more non-linear instruments, our margin methodology needs to change. We need to be able to better assess the scope of potential losses as the number of possible adverse scenarios increases, and to boost the scalability of our systems. Monte Carlo provides the ability to properly capture the risk when there are a lot of volatility structures, where the risk appears to be in the middle of the underlying distribution – so, not related to very extreme moves, just ordinary tightening or widening of the underlyings, but with significant implied volatility changes,” says Ivanov.
Monte Carlo engines run thousands of scenarios in order to calculate potential losses on a position or portfolio. The outputs are used to create a potential loss distribution, which is then used to estimate a portfolio’s value-at-risk. They are highly powerful tools for gauging the risk of loss on non-linear instruments, such as options or multi-legged trades, given their ability to simulate a wide range of potential profit and loss scenarios. Their workings are computationally intensive, however, generally requiring overnight runs to perform the necessary calculations across an entire portfolio.
Ice currently uses stress scenarios to set two critical components of its margin methodology: spread response, which measures changes in spreads on CDS contracts versus changes in the price of the debt of their reference entity; and recovery rate, which measures the amount of debt that can be recouped from a counterparty following a default.
As the SEC noted when issuing Ice approval to adopt the new methodology, its current stress-based approach “generates a limited number of stress scenarios that may not capture the risk of portfolios with more complex, non-linear instruments” – such as CDS swaptions.
Ice’s new methodology will replace the model’s spread response and recovery rate components with a combined “integrated spread response”, whose value would be derived from profit and loss distributions generated by a Monte Carlo approach.
Ice has, in fact, been running this methodology in parallel with its existing stress-based methodology for a number of years, as well as using Monte Carlo simulations to stress member portfolios on an ad hoc basis – for instance, when deciding whether to apply margin top-ups to portfolios that have become concentrated.
To properly capture the risk of more non-linear instruments, our margin methodology needs to change. We need to be able to better assess the scope of potential losses as the number of possible adverse scenarios increase
s, and to boost the scalability of our systemsStanislav Ivanov, Ice Clear Credit
But the pending launch of CDS swaptions clearing has served as the spur for Ice to make the switch, says Ivanov. The new methodology will also allow for more efficient margining of portfolios that benefit from broad diversification between the names included, it is understood.
“We’ve had the ambition to do this for 10 years. It took a little bit of market evolution, technology evolution, as well as gauging the need for more advanced portfolio-directed risk management techniques. We’ve been running it in parallel with our existing stress-based methodology for quite some time, and we decided at the start of this year that the time was right to go and switch to the Monte Carlo framework,” he tells Risk.net.
Ice’s rival clearer LCH previously employed a Monte Carlo-based methodology within its CDSClear subsidiary, though it switched to using a filtered historical VAR-based approach in 2016. CDSClear has offered clearing of iTraxx Europe index swaptions for almost a year – although the central counterparty has yet to enjoy significant traction in the products.
Pending regulatory change could help boost volumes for clearers. Some eight years after being handed the mandate to do so, the SEC has moved to institute rules governing minimum standards for dealers active in the single-name CDS market – a step that could finally presage a move towards a mandate for clearing of certain single-name CDS contracts. To date, clearers have been reliant on the voluntary clearing of trades, with around half of the market still not cleared.
Update, November 28: A previous version of this article stated LCH’s CDSClear unit used a Monte Carlo-based model to calculate initial margin requirements. In fact, CDSClear ceased using this approach in 2016, and switched to a filtered historical VAR-based approach instead.
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