Quod Financial is set to use market data from QuantHouse to refine its AI-driven trading algorithms to optimise trading strategies and improve trade execution.
Speaking to The TRADE, Rob Kirby, head of EMEA sales and business development at QuantHouse, explains: “Quod are a great partner of ours and have been for a number of years. We work closely with them, and also with other OMS/EMS providers as well. We are data agnostic and those types of partners are absolutely critical for QuantHouse.
“Quod has integrated all of the historical market data now, which gives us and them, the opportunity to onboard more and more clients within that space even more efficiently.”
Specifically, through the strategic partnership, QuantHouse’s low-latency and historical data will be used to train QuodFinancial’s AI/machine learning models to adapt to and anticipate market movements.
The AI-driven trading algorithms will enable trading firms to carry out real-time, highly accurate transaction cost analysis (TCA) at the point of execution. As a result, traders will not need to manually adjust their TCA assumptions or trading strategies in the event of unexpected market events.
“QuantHouse has got a reputation in the marketplace for low latency, high performance normalised market data which is critical to exchange-type customers. We have MTFs as long-standing customers but we also have a decent proportion of OMS, EMS partners as well. They like using our data because of the reliability and the speed of it,” asserts Kirby.
Read more – Buy-side set to leverage newly combined real time and historical BMLL and Quanthouse offering
Across the trading ecosystem, market participants are highly cognisant of the importance of avoiding a “garbage in, garbage out” situation when it comes to data and technology, in particular when coupled with the theme of AI. Subsequent algorithms are only as effective as the data which powers them.
Speaking in an announcement on Tuesday, Medan Gabbay, chief revenue officer at Quod Financial asserted the importance of solid technological infrastructure when it comes to data automation: “In financial services, the performance of your technology is defined by the quality and speed of the data that powers your systems. This has never been more true or more important than now, as we go through a transition of data automation and AI/ML.”
As AI gains traction across the industry, there has understandably been some trepidation about what the incorporation of this technology could entail.
Read more – The buy-side on AI: ‘The fear is real, but the rewards are there’
Speaking to this, Kirby highlights that though market participants are cautious, particularly in such a highly regulated industry, the increasing use of AI is an inevitable development.
“Clients are always looking for optimal ways to cut costs and increase the efficiency of what they’re doing. If you look at the way AI and machine learning looks at data, and the huge amounts of data sets which are only becoming larger, AI is a clear answer. There are ways of providing risk mitigation, which will allay some of the fears that are in the marketplace today.
“AI is not just a big buzz word, it’s being deployed in ways which are completely changing the industry. It is bringing in huge cost efficiencies and is allowing some of these traders to be able to focus on exactly what they should be focusing on – the execution part of the strategy. That’s, I think, the most exciting thing.”