Iress’s QuantHouse division has formed a strategic global partnership with multi-asset trading technology provider QUOD Financial. Under the agreement, QuantHouse will supply low-latency and historical market data to QUOD, which will be utilised for back-testing and optimisation of QUOD’s AI-driven trading algorithms, and to facilitate real-time, highly accurate transaction cost analysis (TCA) at the point of execution.
“For organisations such as QUOD, obtaining consistent and comprehensive data is crucial,” QuantHouse’s Head of EMEA Sales and Business Development, Rob Kirby, tells TradingTech Insight. “By partnering with Quant House, QUOD can now receive both real-time low-latency market data and historical market data with the same symbology. They can leverage our historical data to train and back-test their AI trading models, before transitioning to production using the same format with low-latency real-time market data. This data can feed into their smart order router and algorithmic technologies, creating a seamless process.”
Across electronic trading, financial institutions are increasingly adopting AI and machine learning (ML) to improve trading and execution outcomes, says Kirby. “A significant challenge in implementing these technologies is ensuring the accuracy of the data on which AI systems are trained,” he says. “QuantHouse’s high-quality, extensive historical data is now being employed to train QUOD’s AI/ML models, enabling them to adapt to and anticipate market movements. They can also utilise our real-time data to optimise the timing, price, and quantity of trade executions, thereby minimising transaction costs and market impact.”
Traders no longer need to adjust their TCA assumptions or trading strategies manually when unexpected market events happen, suggests Kirby. “They can now analyse the cost associated with each trade, optimise trading strategies and ultimately improve trade executions right at the point where it is needed most: as part of the trade execution.”
Kirby is optimistic about AI’s role in the trading environment. “Looking ahead, it will be interesting to observe the uptake and success rates of clients using traditional methods to execute in markets compared to those utilising AI trading models. This is something we will only fully understand over time. And although risk management is crucial for anyone executing in markets, whether due to human errors or unexpected machine behaviour, I’m confident that AI will save both time and money by processing vast amounts of data rapidly, allowing traders to concentrate on their core strengths.”
Commenting on the partnership, Quod Financial’s Chief Revenue Officer, Medan Gabbay, said: “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. QuantHouse has proven to be an exceptional partner in this data journey.”
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