Our client’s CPO, Marco Kuper (DIGITEC), provides an analysis in e-forex on how the adoption of RFRs (Risk Free Rates) have affected FX Swaps pricing, highlighting that demand for “more flexible, robust and configurable pricing technology” is rising as a result.

DIGITEC is a specialist FX Swaps technology and data provider with over 50% of their 40+ global bank clients being included in the top 50 FX trading firms. Here is a snippet of that analysis below:

RFRs have seen a large increase in adoption levels since the start of 2022. Whilst this trend tends to vary across currencies, two of the largest markets such as USD (SOFR) and GBP (SONIA) show high levels of usage. Tracking this progress can be accessed using the ISDA-Clarus RFR Adoption Indicator; showing exactly how much global trading activity is conducted in cleared OTC and exchange-traded interest rate derivatives that reference RFRs. This reached an all time high of 46.4% in June 2022, where it remains to date.

Consequently, this transition to RFRs have led to changes in the pricing models used for FX swaps. Therefore, LIBOR-based systems such as IRS and some STIR Futures could not continue to serve as the foundation anymore. DIGITEC identified that these changes in the pricing models vary according to the quality of the pre-existing pricing system in place, which can prove to be a costly challenge. This is especially true for systems with non-configurable defaults such as Excel-based systems which rely heavily on on hand-crafted formulas.

In the past we could expect the market to move slowly in small movements covered by the trader’s bid-offer spread, including time to react and adjust. This time has been almost completely eliminated due to the competitiveness, liquidity and volatility of the market created by central bank activity today, “this leads to a need for faster pricing models that quickly adjust when the market starts to move,” Marco Kuper writes, “models that solely rely on FX Swap prices published by brokers are particularly vulnerable, as these data points are not only among the last to update in times of movement, they also do not cover relevant points such as the central bank dates that show the largest effect.”

Read more of Marco Kuper’s analysis here