CQG, a global provider of technology solutions for market makers, traders, brokers, commercial hedgers, and exchanges, has disclosed the successful completion of internal testing and proof-of-concept employing live data for what it asserts to be a pioneering artificial intelligence (AI) predictive model for traders. The announcement was made today (Monday).

Advanced AI Initiative Shows Promise in Live Trading Environments

Following machine learning (ML) training within a back-testing environment, the company has commenced the application of the technology to live data. CQG reports a notably high level of predictive success in anticipating movements in the futures market. Leveraging its expertise in analytics, mathematics, and market intelligence, the new ML initiative endeavors to furnish retail traders and buy-side firms, including proprietary trading firms and hedge funds, with tools for recognizing new trading and analytics opportunities, guiding trading strategies, and managing positions.

Ryan Moroney, the CEO of CQG said: "In early 2023, we decided we wanted to do something different in machine learning and AI that leveraged our unique position in the market, building off our comprehensive database of historical trade data and analytics in a way that could help our clients and prospects analyze, predict and trade markets through a new lens. We built a lab, and Kevin Darby, our Vice President of Execution Technologies, has done an extraordinary job of turning that effort into an exciting reality with results that have significantly surpassed our expectations.

CQG's AI Journey: From Exploration to Live Trading Success

CQG's exploration of AI over the past year has been focused on addressing its clients' challenges, with the technology tested in a cutting-edge multi-platform lab. Last week marked a milestone as the company conducted its inaugural test of the next-generation machine learning toolkit in a live trading environment, achieving an 80% predictive accuracy, commensurate with the results attained in the back-testing environment.