Financial institutions face market challenges due to steepened curves and changes in the interest rate dynamic. These changes create instability for trading, and financial institutions need to adopt new interpolation methods to overcome the hurdles of curve steepening scenarios. Firms must invest in technology, centralize curve analytics, and ensure consistency across the organization. Centralizing curve analytics can minimize reconciliation costs and adapt quickly to upcoming market changes. Additionally, model validation is crucial, and firms must invest in the right people to understand the curve and put best practices in place. Continually and gradually upgrading tools is a better approach to technology, and firms must avoid relying on workarounds to solve tactical problems in the short term.
UBS and Credit Suisse Confirm Takeover Following Swiss National Bank Intervention
UBS and Credit Suisse have confirmed a landmark takeover after the Swiss National Bank intervened to “protect the Swiss economy” in what has been an exceptional situation for the financial services industry. The developments have had a significant impact on trading desks and their supporting middle office risk teams, albeit in different ways.
USD Libor Displacement
The displacement of USD Libor has been a prolonged process, and market participants have been preparing for this change over the past three to four years. While many market participants are ready for the shift, the event is global, affecting desks from the US to Europe, Latin America, and APAC. Some markets, such as the Singapore dollar markets or Thai bhat, see teams still uncertain of how to navigate the process despite being only a few months away from the official end of the legacy USD rate. Even in regions such as the US, the act of shifting to a new rate has longer-term implications from a curve analytics perspective.
Rise in Interest Rates
In contrast, the rise in interest rates to tackle inflation has happened quickly in established developed financial centres. Interest rates have increased from close to zero percent or negative to over three percent in the EU and the UK, whereas they are flirting with five percent in the US. The impact has been positive, leading to more volatile markets, surging volumes, and greater opportunities for generating trading revenues. However, there are risks too.
Potential Hurdles
Institutions must overcome potential hurdles in the current climate, having just exited a 10-year period of very low or negative rates. The curve was extremely flat, and rates are now climbing, creating much steeper rate curve shapes, particularly on the short end. Firms are finding it challenging to interpret or predict rates in between quoted points. During the long period of low rates, the need to invest in curve analytics was not particularly tangible. However, this approach began to fail last year, leading to numerous challenges around bogus forwards and subsequent pricing and risk issues.
The recent example of Silicon Valley Bank illustrates how rapidly rising interest affects bond prices and interest rate curves. In this case, the valuation of the bank’s fixed duration bond portfolio significantly decreased, creating the conditions for the poor financial health of its balance sheet. Improper interest rate hedge proves are no longer seamless, and trading desks have seen the rate curves become unstable.
In summary, the changes in interest rates and the displacement of USD Libor are global events that have significant implications for trading desks and their supporting middle office risk teams. While the rise in interest rates has created more opportunities for generating trading revenues, it has also created risks, and institutions must overcome potential hurdles to navigate the current climate successfully.
Adjustments to Interest Rate Curves and their Impact on Trading Instability
The sudden series of shocks on policy rates has drastically redefined the properties of the interest rate curves, resulting in an inverted curve with expectations of it getting steeper in the short term. This creates additional constraints to the resulting curve, making trading unstable and challenging future rate predictions.
Hurdles in Curve Interpolation
The challenge for trading desks and middle office teams is that the steepened curve creates additional constraints to the resulting curve. Insufficient interpolation approaches will generate instabilities when part of the curve is highly steep and constrained. Some firms were using very basic curve construction techniques, which are becoming hazardous to accurately value their positions. Simple interpolation schemes can also dangerously affect risk figures with respect to the market quote inputs.
Murex Investment in Curve Construction Techniques
Murex has invested considerable effort in unpacking simplistic curve assumptions and strengthening construction techniques to manage steep curves.
Approach to Better Manage Volatile Rate Environment
To better manage the volatile rate environment, financial institutions must centralize their curve analytics internally. While technology can bring the necessary tools to better adjust curves and stabilize trading, the strategy for implementing the technology is equally important.
Consistency in Curve Analytics
Financial institutions use rate curves in most business processes, but they often have several curve analytics systems. Fixing everything at once and preserving consistency is a challenge. Smaller institutions and non-banks may have neglected this part and should rapidly shift into new interpolation methods to overcome the hurdles of curve steepening scenarios.
In summary, the adjustments to interest rate curves can increase instability for trading, challenging future rate predictions and making trading unstable. Financial institutions must invest in new interpolation methods, centralize their curve analytics internally, and ensure consistency in curve analytics to better manage the volatile rate environment.
Firms must look at their systems and analytics architecture and choose a single source of truth to ensure consistency across the organization. Disruption is the norm in the curve, and change is the only constant. To navigate these market challenges, technology can play a crucial role.
Centralizing Curve Analytics
Centralizing curve analytics can minimize reconciliation costs and adapt quickly to upcoming market changes. This entails putting a REST API on top of the Murex rate curve module, which exposes curve analytics in a deeply simple API that any organizational system can use. This single source of truth can be plugged into any other system and avoids the redundancy of multiple similar programs doing the same calculation.
Model Validation
Firms must invest in the right people to understand the curve and put best practices in place when it comes to model validation. Whether they use an in-house or vendor system, APIs are required on the tech side to retrieve historical data and manipulate data to build belief that analytics models will be solid.
Continual Technology Upgrades
Technology must be part of a firm’s ongoing investment. Continually and gradually upgrading tools is a better approach than relying on workarounds to solve tactical problems in the short term. In extreme market environments, such as the one we are seeing today, the workaround approach and technology set-up will be found lacking.
In summary, technology can help financial institutions navigate market challenges by centralizing curve analytics, investing in the right people for model validation, and continually upgrading tools. Firms can minimize reconciliation costs, adapt quickly to upcoming market changes, and avoid redundancy by having a single source of truth that can be plugged into any other system.
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