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The Role of Curve Analytics in Navigating Market Volatility in 2023
High market volatility due to ongoing economic turbulence and market challenges related to inflation and interest rate hikes are set to continue in 2023. This confluence of market events creates challenges for curve trading analytics. In a Q&A, Didier Loiseau, global head of trading and financial engineering at Murex, sheds light on how technology (data and analytics) can help financial institutions better navigate these market challenges.
Q: What are the most significant market challenges that will impact curve spread trading in the coming months?
A: The most significant event that is going to happen is the discontinuation of the final tranche of LIBOR settings, namely the USD LIBOR. The industry has been preparing for three or four years now and this is the final sprint before the June deadline. This is the challenge with the most certainty and people know what to expect thanks to experience from the first waves. One exception might be in Asia-Pacific, where the Thai bhat and Singapore dollar markets are entering a sort of double transition. That’s where people are still working hard and figuring out how they will address this challenge.
In the main global economies, people are looking at how high the interest rates and inflation are going to go and how this is going to evolve.
Q: How are the market challenges or changes impacting curve analytics specifically?
A: We are just out of a 10-year period where rates were extremely low or even negative—which was a challenge in itself—and the curve was extremely flat. Ten years is a long time. There are many people in the market who started their professional working careers during that period and have not known anything else. Now, suddenly rates are climbing, and we are seeing rate curve shapes that are much steeper, particularly on the short end. This can be stressful in terms of how firms interpret rates or predict rates in between the quoted points.
Aside from inexperienced staff, firms might have invested in insufficient systems during the long period of low rates. If a bank invested in analytics designed to cope with low rates, the curve construction techniques they have might now fail and lead to bogus forwards, leading to mispricing, wrong risk management, problems in P&L reporting and so on. The bigger institutions have model validation processes that make them ready for such scenarios, but smaller institutions and non-bank institutions might not.
Murex has spent a lot of time with bank and non-bank customers unpicking simplistic assumptions they had been making on curves and beefing up construction techniques so they can cope with these sorts of steep curves in the proper way. It has been a very active year in that regard.
“Firms should never assume things are going to stay the same. In terms of investment, it is important to always keep some buffer to handle the unexpected, because changes always come.”
Q: At a high level, how can curve analytics assist firms as they look to mitigate the risks and manage the challenges due to market-wide volatility?
A: The first phase is to urgently fix the problems. In some cases, firms are complaining their swaps prices are completely wrong and it turns out it is because they were using very basic curve construction techniques. They need to look at what has worked elsewhere and implement solutions rapidly to the most urgent problems.
The second phase is more strategic. The first step here would be to work on centralising curve analytics in the institution. Rate curves are used in most business processes in a financial institution. It is not just one desk or one team—it is at the core of the business in general. However, institutions often have several curve analytics systems in different teams and departments, which makes it hard to fix everything at the same time while preserving a certain level of consistency. The first thing to do, therefore, is look at the systems and analytics architecture and decide what should be the central source of truth. Firms need to figure out how to ensure consistency across the organisation so that whenever there is a change, they only have to change it once. When it comes to curves, disruption is the norm and change is the only constant.
The second aspect is model validation. Firms need to be able to validate these analytics on the curve on the day and also make sure the strategies they put in place are viable for foreseeable market moves, including if the curve gets even steeper than now or if it gets flat again, or if it twists. The maturity of this process depends on the firm and part of Murex’s role is to help firms think strategically about model validation.
Firms should never assume things are going to stay the same. In terms of investment, it is important to always keep some buffer to handle the unexpected, because changes always come.
Q: Can you give me some examples of how market data analytics and technology can assist in the implementation of the strategy to address market challenges?
A: Centralising curve analytics means putting a REST API (an interface used by two computer systems to exchange information securely) on top of the Murex rate curve module. This exposes all the curve analytics in a very simple yet complete API that any system within the organisation can use. This enables firms to minimise reconciliation costs and to adapt quickly to the next market change that is inevitable. This single source of truth can be plugged into any other system and avoids the redundancy of multiple similar programs doing the same calculation.
When it comes to model validation, whether they are using a vendor or in-house system, firms need to make sure they invest in having the right people who can understand the curve and the right processes in place. On the technology side, they typically need some APIs to retrieve historical data, and to be able to manipulate data to build confidence that the firms’ analytics models will hold up in any foreseeable world of potential future market scenarios.
Technology should be a part of firm’s ongoing investment, so they stay up to date and don’t compromise on the tools they are using. Some firms use workarounds to solve tactical problems, but over time, these pile up and make it much more painful to upgrade than if [firms] were continuously investing in upgrading tools, little by little.
Q: What are the benefits a firm can achieve if they utilise technology and services to support their trading strategies to better navigate the changes in the markets?
A: The most important benefit is the impact on trading performance. Firms get the right analytics at the right time, and the prices and risk management are reliable.
But there are also cost benefits. Reconciliations costs are causing a lot of pain for organisations and investing in a centralised curve analytics process and technology will help them reduce these costs significantly. Another benefit is that it creates a habit of adapting to change and validating the model.
Q: What final piece of advice would you give our readers who are keen to prepare their curve analytics this year?
A: Revisit your curve construction techniques. It is very important to review this given the LIBOR discontinuation, inflation and high rates. Fix the problems you have using available information. Firms like Murex are here to help and share expertise.
Also, assume you will have to fix curve constructions again every year and invest constantly in change implementation. Finally, assume there will be a disrupting event every year and put plans in place on the basis of this assumption.
To learn more listen to Julien Martinez, head of Murex’ market data analytics in this video, where he describes how Murex clients can build accurate rate curves in an inflationary context.
Source: Didier Loiseau was interviewed by Julia Schieffer for derivsource.com.
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