Murex Wins Best Technology Provider for FX Options at Euromoney’s Foreign Exchange Awards

Solution used by over 130 banks and financial institutions around the world

PARIS, September 30, 2024—Murex is pleased to announce it has been named Best Technology Provider for FX Options at Euromoney’s Foreign Exchange Awards.

The competition, also known as the Euromoney FX Awards, represents a deep survey of the wholesale FX market. It is judged by a global panel that includes banks, providers and buy-side corporations and recognizes “excellence and innovation in the market.”

Murex has a very large, diverse and active client base on FX options that includes global and regional banks, brokers, hedge funds, asset managers, corporates and central banks.

“Over 130 financial institutions utilize MX.3 for trading FX options,” said Solene Khy, head of product management for commodities, equity, FX and digital assets at Murex. “Since its inception, Murex has provided FX options traders and risk managers with a market-leading solution. Our platform adds value at every stage, from pricing and volatility management to structuring, sales, risk analysis and reporting, and covers a large scope of payoffs and analytics. Our advanced risk management solution allows MX.3 users to monitor in real time their positions and advanced greeks, as well as to run flexible what-if scenarios to estimate the impact of market data changes. It also provides the P&L attribution for the daily activity, and a real-time barrier monitoring tool to anticipate discontinuities.”

Murex is dedicated to continuing its investments to remain at the forefront of FX market evolution, while ensuring client needs are addressed and the latest technologies are leveraged.

Recently, Murex quant experts developed a novel approach for pricing complex FX barrier options using neural networks that provides high speed with accuracy on prices and sensitivities.

By using machine learning to replicate the pricing model of the most sophisticated derivatives, Murex sharply reduced the compute time and hardware cost usually seen for such heavy calculations. Read a white paper that details the results of this research.