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TraditionDATA and Numerix expand foreign exchange data coverage and analytics

TraditionDATA, the market data and information services division of Tradition, has partnered with Numerix, a provider of technology solutions and real-time intelligence capabilities for trading and risk management. The move will allow TraditionDATA to leverage Numerix's deep analytics expertise and create derived data for more than 130 volatility surfaces across more than 130 currency pairs.

Conforming to industry standard 'cut' times, this data service includes tenors ranging from one week to 30Y, and volatility points including at the money (ATM), 5D, 10D, 15D, 25D and 35D in risk reversals and butterflies. 

Clients can now source information from Tradition in a wide range of FX products, including spot data from the ParFX trading platform, forwards, swaps and NDF data from Tradition’s global broking business and options data from the Volbroker trading platform. This data coverage includes intra-day pricing, granular historic data derived volatility surfaces and end-of-day data.

The data will be available directly from INTEGRATE, Tradition’s in-house market data distribution platform, Bloomberg’s Market Data Feed (B-PIPE) and via a selection of Numerix applications and products.

Scott Fitzpatrick, global head of TraditionDATA, commented: “We are always looking to increase our product range and improve the quality and quantity of the data we provide to clients. Numerix was the ideal partner for this initiative; they have cutting-edge technology and analytics capabilities, and are recognised and renowned across the industry for their advanced modelling and coverage of OTC derivatives, including the most complex exotic products. This partnership gives our clients access to accurate and comprehensive coverage of the FX spot and derivatives markets globally.”

Steve O’Hanlon, CEO of Numerix, added: “We are proud to be the analytics partner to help TraditionDATA provide the data needed to support its clients. Its flexible model is shaking up the status quo in terms of data consumption, and avoids the complex process of unbundling, analysing and extracting valuable data points."

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