TT and OpenGamma: Bringing Margin Optimization to the Forefront of Trading
As margin requirements grow in both scale and complexity, firms across the derivatives market face increasing pressure on capital efficiency. This was one of the driving factors behind Trading Technologies’s acquisition of OpenGamma last December.
Recent volatility has further illustrated this challenge. As market stress increases, margin requirements rise, placing a strain on liquidity and, in some extreme cases, forcing firms to close out positions to meet margin calls.
I joined TT through the OpenGamma acquisition. Now, as the head of TT’s margin analytics business, I have a clear view on how capital efficiency has evolved since the 2008 financial crisis and how TT’s acquisition of OpenGamma will accelerate the move of margin optimization to the front office.
OpenGamma has operated for more than a decade as a leader in margin analytics. Everything we do is focused on enabling more capital-efficient derivatives trading for our clients.
This challenge gained prominence with the post-2008 regulatory reforms that required market participants to post initial margin on their derivatives positions. This reduced the available leverage and increased the cost of trading derivatives for many firms. Our role has been to help firms understand and reduce that cost.
We work with everyone from hedge funds and asset managers to commodity firms and the sell side, and, while the nature of their derivatives activity varies, the common focus remains on deploying capital more efficiently.
Market Volatility and Margin Impact
Although there has been a long-term trend towards increased margin requirements, recent periods of volatility have accelerated the trajectory. During periods of market stress, firms that hold derivatives positions need to post significantly more cash to maintain them. That creates demand for cash at exactly the wrong time, and it also means that, when opportunities appear, firms may not have the available capital to trade.
This was evident in the fixed income market during the initial COVID-19 shock in 2020, when rising margin and funding requirements forced leveraged participants to unwind positions, and again in commodities following Russia’s full-scale invasion of Ukraine in 2022, where sharp increases in gas prices were accompanied by an even larger increase in margin.
A key issue is that, even when volatility subsides, margin does not fully revert to prior levels for an extended period. This comes as a result of clearinghouse models, where historical stress remains embedded in margin calculations, delaying the return to lower requirements. In gas markets, for instance, margin levels remain materially higher today than before 2022.
Drivers of Margin Complexity
The main factor is the fragmentation of margin models. Each clearinghouse or counterparty defines its own methodology. The models measure similar risks but differ in implementation and methodology in areas such as lookback periods. That creates complexity for firms that operate across venues and counterparties. However, there is an opportunity for active margin management—treating margin not as a fixed cost, but as something that can be optimized.
This is where margin analytics become critical. Once you can independently calculate margin, you can compare alternative trade structures and identify strategies that will attract lower margin while keeping the same market position.
At OpenGamma, we replicate the margin models used across the derivatives market. Using these models, we can simulate different ways to structure portfolios. The goal is to find the most capital-efficient approach without changing the underlying exposures.
This is difficult to achieve in house. Each model requires significant effort to replicate and maintain. In addition, they are not static models, and methodologies are continuously evolving—for example, CME is currently moving from standard portfolio analysis of risk (SPAN) to SPAN 2. We can mutualize the cost of building and maintaining the wide range of models across clients.
Consequences of SPAN 2
For market participants, the biggest impact of this transition is a loss of transparency. The original SPAN framework allowed traders to understand margin in relatively intuitive terms. It was much easier to understand how the margin was calculated and what factors drove it.
With SPAN 2, the industry is moving toward a VAR-based approach that relies on historical VaR and stress scenarios. It is a familiar concept to risk teams but far less intuitive for traders at a portfolio level, making it incredibly hard to understand the margin offsets that are being generated between their positions and their peers’. This is a key driver behind demand for our services—as methodologies become more complex, firms need better visibility and control.
The Impact of Mandatory Clearing
Mandatory clearing of U.S. Treasuries will have a significant impact on margin and trading strategies, particularly in repo markets. The changes introduce dynamic and regulatory minimum margins into strategies that have historically benefitted from stable and simple margin approaches, such as trade-level haircuts.
These new margin regimes change the economics of fixed income relative-value strategies.
Treasury clearing—and later repo clearing—will therefore change how much leverage firms can access and which strategies remain viable. For us though, it extends the same core problem into a new area. Firms will need to understand and optimize margin across an even broader set of products.
How “OpenGamma + TT” Unlocks Capital Efficiency
Historically, we operated in the middle and back office. We provided recommendations to treasury and/or operations teams. The opportunity with TT is to connect that insight directly to the front office.
Instead of identifying savings and leaving it to operations teams to act, we can move toward automated execution. That allows firms to capture savings more consistently and with less manual intervention. It also brings margin awareness into the front office. Traders and portfolio managers ultimately bear the cost of margin, so giving them direct visibility is critical.
Our priority is to unlock the potential savings for our clients. When it comes to margin optimization, that means embedding the calculations into trading workflows and automating the execution of capital-efficient strategies.
By combining TT’s execution capabilities with our analytics, we can deliver a more complete workflow—from trade initiation to execution to post-trade optimization.
To learn more about OpenGamma and our margin optimization solutions, visit our website.