Vertical exchange silos are an oft-maligned feature of the financial markets. Critics argue such models, where an exchange controls both trade execution and clearing, can be anti-competitive and result in higher costs for end-users. Nodal Exchange is proving that vertical integration has plenty of benefits for customers, too.
In 2015, the bourse – the sole independent player in the fiercely competitive US power trading market – decided to bring clearing in house from LCH, its partner from launch in 2009.
Nodal wasn't unhappy with LCH's service, stresses Paul Cusenza, chairman and chief executive of the Tysons Corner, Virginia-based firm – but it was pretty obvious electricity clearing was little more than a fringe business for the over-the-counter markets behemoth (see Clearing house of the year).
A little over a year later, with its market share burgeoning and a host of new products in the offing, Cusenza is delighted with the switch. "When you want to introduce new products, and have a single integrated view of your market, clearing for yourself obviously offers strong benefits," he says.
The transition of client positions from LCH, comprising contracts worth a notional $24 billion for 340 million megawatt-hours of power, had to be managed extremely carefully, as did the transfer of a $100 million default fund. But the biggest challenge Nodal Clear faced was designing an initial margin model to safely and accurately measure risk across that portfolio, while also allowing members to recognise the benefits of margin offsets where appropriate.
Expected shortfall has worked out extremely effectively so far. We're very happy with the way it's performed. It's a true risk-based measure; it dynamically adjusts based on the risks that are there
Paul Cusenza, Nodal Exchange
At first, the CCP considered simply replicating LCH's historical value-at-risk methodology. But it ultimately plumped for the expected shortfall (ES) variant, because of the refinements it offers in mapping the expected distribution of losses during extreme-but-plausible scenarios – which makes it well-suited for modelling the idiosyncratic risks of the power market.
"Losses in our market don't follow a normal curve. VAR assumes normality, but ES offers a mechanism to handle those fat-tail events more effectively. It's worked out extremely effectively so far. We're very happy with the way it's performed. It's a true risk-based measure; it dynamically adjusts based on the risks that are there," says Cusenza.
When the model was tested and implemented, Nodal's clients saw a broad rise in initial margin requirements compared with LCH's methodology. But far from lamenting this conservatism, dealers laud it: "Whenever another exchange launches a new contract, the first thing we ask is, ‘what's their margin versus Nodal's?'," says a senior futures risk manager at a large US bank.
By the numbers, Nodal's strategy is working: its share of the US power market rose from around 21% at the start of 2016 to 26.4% through year-end, as measured by open interest – taking a chunk out of long-time market-leader Ice's share – with its trading volumes virtually doubling during that time. The next step, Cusenza says, will be to add functionality for power options, followed by a move into natural gas – where there are obvious synergies and opportunities for portfolio offsets – later this year.
Cusenza pins all of this on the CCP's decision to plump for ES, rather than VAR.
"The accuracy of the model makes it effective; it's conservative, but efficient. We can hold the right amount [of margin] because we have an excellent model. If you don't have an accurate model, you frequently end up holding more margin – and you could be holding it in the wrong places; a model that demands more margin across a portfolio could still be risky, because you could be under-pricing some risks. We're not using a dull wooden sword to perform surgery here; we're using a scalpel."
One thing we really value is their portfolio margin analysis tool. It allows us to predict, with reasonable accuracy, our margin requirements out to six months, taking into account the weather, supply patterns and other variables
Jared Fein, Goldman Sachs
Nodal's margin model has been a revelation in the commodity markets, where many contracts are still margined using the decades-old Standard portfolio analysis of risk (Span) methodology. Though tried and tested, Span is simplistic compared with VAR modelling, subjecting portfolios to price moves during different stress scenarios with the use of historical data and levying margin accordingly.
Some have long-argued Span is unsuitable for clearing electricity markets, which are subject to not only the whims of demand and supply like other commodities but also more idiosyncratic risks, such as prolonged and unexpected bouts of severe weather, changes to grid capacity, and suppliers going offline with little or no warning.
"Span can't handle a widely diverse portfolio appropriately, because it can't handle all those different risk factors simultaneously. It's not suited for our markets," says Cusenza.
The futures risk manager agrees: "A Span calculator is essentially a dumb instrument. If you program it to tell you 2+2=5, it will keep telling you that it is, without knowing otherwise."
VAR-based models aren't infallible either – certainly where they are inappropriately fine-tuned. During the severe polar vortex of January 2014, when power prices spiked and margins went haywire, LCH sought to apply ad hoc add-ons to its existing methodology. This attracted criticism from some quarters, with dealers complaining that the sizing of the margin add-ons wasn't made clear, making for uncomfortable discussions with clients.
Cusenza insists Nodal's approach strikes the right balance between prudence and capital efficiency. "Our model is conservative, and we're proud of that; we're here to manage risk, and I always want that to be the case. That is a badge of pride. But by the same token, we want to offer clients maximum capital efficiency, and we can do that because we're confident in our risk-based methodology," he says.
Clients also praise Nodal's portfolio margin prediction tool, which it rolled out last year: "One thing we really value is their portfolio margin analysis tool, which they make available to all clients. It allows us to predict, with reasonable accuracy, our margin requirements out to six months, taking into account the weather, supply patterns and other variables. I don't know of anyone else who offers something like this," says Jared Fein, a senior clearing risk manager at Goldman Sachs in New York.
The week on Risk.net, July 14–20, 2017Receive this by email