Multi-asset trading technology provider Quod Financial has entered into a strategic partnership with QuantHouse, a division of Iress, to enhance its AI-driven trading algorithms.
Trading firms will be able to carry out real-time transaction cost analysis (TCA) at the point of execution thanks to these enhancements, Quod Financial said, with QuantHouse’s low-latency and historical market data used within backtesting and to achieve algorithm refinement.
Commenting on the partnership, Rob Kirby, head of EMEA sales and business development, said: “In today’s trading environment, financial institutions are actively exploring and adopting the latest advances in AI and machine learning (ML) to enhance trading outcomes. The key challenge with deploying these latest innovations into the trading environment is that AI-driven algorithms can only be as accurate as the data on which AI systems are trained.
“QuantHouse’s historical data is now being used to train QuodFinancial’s AI/ML models to adapt to, and even anticipate, market movements. Traders no longer need to adjust their TCA assumptions or trading strategies manually when unexpected market events happen. 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.”
Medan Gabbay, chief revenue officer at Quod Financial, added: “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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