CQG Launches AI/Machine Learning Trading Toolkit For Predicting Futures Market Moves

CQG Launches AI/Machine Learning Trading Toolkit For Predicting Futures Market Moves

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Mar 11, 2024
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March 11, 2024 - Leading futures trading platform CQG has announced the successful deployment of its artificial intelligence (AI) predictive model for trading futures, what the firm believes to be a first-of-its kind predictive model for traders. The deployment comes after CQG has completed internal testing and proof of concept using live data. The announcement was made during the FIA Boca, the International Futures Industry Conference.

 

This AI initiative, derived from CQG's extensive expertise in market analysis and mathematical modelling, is aimed at offering both retail and institutional traders innovative tools for market prediction, trading strategy optimisation, and risk management. CQG's move into AI over the past year culminated in a live trading test that confirmed the model's 80% predictive accuracy rate, mirroring back-testing results.

 

CQG CEO Ryan Moroney shared, "Our venture into AI and machine learning represents a strategic pivot, utilizing our vast historical data to offer our clients a novel perspective on market prediction and trading. Kevin Darby, our VP of Execution Technologies, has spearheaded this project to remarkable success, far exceeding our initial expectations."

 

Kevin Darby, VP of Execution Technologies at CQG, detailed the technical challenges overcome by the team, "We first had to solve multiple real-world challenges, such as storing and curating terabytes of historical market data while retaining the ability to make decisions in microseconds in real-time environments. We built bridges between the current ML infrastructure, based on the Python language, and the reliance of the financial industry infrastructure on C++. We also needed to recast the traditional ML training pipeline to optimize for generative time series prediction to estimate conditional probability distributions in a mathematically satisfying and stable way." 

 

He said the firm's AI in a live environment was consistently able to predict with 80% accuracy whether the next movement in the E-mini S&P 500 futures contract would be up, down or unchanged.

 

Moroney said CQG has already identified multiple uses related to algorithms (algos), charting and research and is starting to explore other applications with key partners.

 

"What we've built is portable. We can give a firm a set of encrypted files, and they can see how our technology predicts moves in liquid futures contracts with a high rate of accuracy. They will be able to use our ML lab, apply cloud computing resources and create their own models, either leveraging our models as foundational or making their own from scratch using our historical data and ML toolkit. They can then use CQG for charting and trading with those models. We have extremely smart, creative clients. This is a truly innovative breakthrough, and we're looking forward to collaborating with them on the potential uses we haven't even considered yet."

 

"For the past 40 years CQG has built sophisticated, intuitive tools for customers to better visualize and analyze market data to make smarter trading decisions. We view our new ML offering as the next breakthrough for mission-critical trading tools delivered by CQG." Moroney concluded. 

 

In November last year, CQG underwent a management buyout from founder Tim Mather.

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