Ryan Moroney

Following internal testing and proof-of-concept using live data, CQG has confirmed that the system has been successful in a live trading environment. 

“Following extensive machine learning (ML) training in a back-testing environment, the firm just started applying the technology to live data, with an extremely high level of predictive success in anticipating futures market moves,” said CQG in a statement. 

The new machine learning offering is aimed at retail traders and buy-side firms such as proprietary trading firms and hedge funds. 

Ryan Moroney, chief executive 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 analyse, predict and trade markets through a new lens.” 

During use in a live trading environment, the model achieved 80% predictive accuracy according to CQG, with the results attained matching those in the back-testing environment.   

Specifically, the AI was “consistently” able to predict whether the next movement in the E-mini S&P 500 futures contract would be up, down or unchanged.  

In addition, CQG claims to have already identified multiple uses related to algos, as well as charting and research. Expectations are for the firm to also start exploring other applications with key partners.  

Kevin Darby, vice president of execution technologies at the company, explained that the firm had had to solve various real-world challenges during development which included “storing and curating terabytes of historical market data while retaining the ability to make decisions in microseconds in real-time environments”. 

Darby added: “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 optimise for generative time series prediction to estimate conditional probability distributions in a mathematically satisfying and stable way. 

“[…] 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.” 

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According to CQG, the new cloud-based platform, which was designed for professional traders and institutional investors, combines the ease of use associated with its retail-oriented desktop platform, with several features of its flagship professional trading platform.

The multi-asset, multi-broker platform will be available via traders’ futures commission merchants (FCMs) from April, with new functionality added throughout the remainder of the year.

“We’re excited to bring CQG One to market after gathering extensive input from our users on what features they most want in our new platform,” said Ryan Moroney, president of CQG.

“This will be as intuitive and easy to deploy, configure and use as CQG Desktop but with advanced charting, market analytics and trading functionality, along with the CQG depth and breadth of market data utilized by our largest and most sophisticated institutional clients.”

The new platform will include premium functionality such as single-click trade entry, advanced charting and analytics, portfolio sharing, window linking and drag-and-drop tabs, amongst other features. 

“CQG One is an ultra-fast, secure platform that traders will be able to access from anywhere to leverage technical analysis tools and execute transactions with a single click on markets all over the world,” said Marcus Kwan, vice president, product strategy & design at CQG.

“We will continuously update it through our HTML5 cloud infrastructure in a way that’s seamless to users.”

The move follows CQG’s launch of a comprehensive suite of execution technology last year, designed to to give market participants new tools to improve upon efficiencies and to achieve optimal trade execution.

The suite was built upon the infrastructure of software assets that CQG acquired from Blue Trading Systems in June 2020 as well as technology CQG has developed recently.

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The new suite focuses particularly on large and complex order types and builds upon the infrastructure of software assets that CQG acquired from Blue Trading Systems (BTS) in June 2020.

In addition, the suite leverages technology that CQG has recently developed, with the aim of providing smart trade execution opportunities for buy- and sell-side firms that can improve pricing, building visibility in aggregating different markets and allowing large firms to match client orders in a manner that meets regulatory requirements.

Kevin Darby, vice president of execution technologies at CQG and formerly co-founder of BTS, will lead the new Execution Technologies business unit, after joining CQG last year to lead the integration of the software.

“The Execution Technologies suite gives buy-side institutions such as hedge funds, large insurance companies, and commercial hedging operations that utilise the industry’s biggest banks and brokerage firms the ability to execute large, complex orders as efficiently as if they were trading a handful of contracts,” said Ryan Moroney, president of CQG.

“We have also further strengthened capabilities for the professional trading community reflecting the myriad sophisticated order types they want to employ.”

CQG’s new offering is available through multiple platforms including CQG Integrate Client, CQG Desktop and several other CQG-supported application programming interfaces (APIs).

All interested clients can now access several components available on the suite including CQG Algos, a set of pre-built algorithmic order types; Custom Algo, a software development kit that allows user to mix and match CQG Algos with their own custom C++ algorithms; and Algo API, a client-side interface used to control and compose server-side algorithms running inside of Custom Algo SDK.

In addition, clients can access AlgoAnalytics, Internalisation Engine and Server-side Aggregation, which are all components on the new suite.

CQG plans to introduce further components later this year and in 2022, including additional algorithmic order types for multi-leg futures trading and a suite of options algorithms.

Lastly, an updated version of the firm’s existing functionality, CQG Spreader 2.0, is expected to be added to the components list available to clients in the near future.

“Our core technology for CQG Algos facilitates ultra-low latency access to markets with an emphasis on strong, lightning-fast analytics, as well as flexible, reliable algorithms,” said Darby.

“Through novel implementation of order types, we’re able to deliver high-quality fills with the goal of reducing implicit trading costs and market impact involved in accumulating a listed derivatives position for buy-side firms. The SDK allows us to partner with long-time clients like proprietary trading groups for high-value trading strategies, while respecting the sanctity of their intellectual property.”

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Nasdaq’s fixed income business will use the web-based CQG Desktop platform as its official front-end for trading in the exchange’s US Treasury Benchmark products under the agreement.

“Our partners at Nasdaq were looking for a next generation front-end trading platform for their fixed income customers,” said Alli Brennan, chief of staff at CQG. “CQG Desktop provides easy-to-use trading tools, with added features including CQG’s best-in-class charting and data visualisation.”

Nasdaq inked a similar deal with CQG in March this year to use its Desktop trading platform for its futures exchange, providing direct trading access of Nasdaq Futures listed products to its clients and lower execution rates.

“Nasdaq is committed to building the futures market of tomorrow. That’s why we’ve partnered with CQG to create a solution for clients that offers best-in-class technology at a lower cost,” Rick Beaman, head of Nasdaq Futures, said at the time. “This partnership is a great example of how we’re reimagining the evolution of NFX and the opportunities for clients.”

CQG’s front-end trading technology was also chosen by Eris Exchange  to power its new cryptocurrency derivatives marketplace ErisX, which is being led by Citi’s former global head of quantitative execution.

ErisX has been established to provide a regulated, transparent and stable venue to the digital asset market with the reliability and infrastructure of a traditional centralised exchange, the company said earlier this month.

The crypto venture has been backed by major financial institutions including Virtu Financial, DRW, Cboe Global Markets and NEX Group.

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