About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Algorithm Framework Allows QuantConnect Community to Share Code Modules

Subscribe to our newsletter

QuantConnect, an open source, cloud-based algorithmic trading platform, is inviting its community of algo developers to share code modules through Algorithm Framework, a tool that provides a defined structure for developing algos and allows code modules to be reused.

The framework tool breaks down algos into five core features: universe selection, alpha creation, portfolio construction, execution, and risk management. The well-defined structure permits modules to be used interchangeably, allowing quants to quickly plug in to new models from the community. Quants can focus their time and effort on coding parts of a strategy where they excel, while borrowing modules from other community members to fill in the areas where they are not as proficient. Giving users the ability to share modules from existing strategies to use in newer strategies also eliminates the need for recoding, reducing the possibility of syntax errors and saving time.

Jared Broad, CEO at QuantConnect, says: “Algorithm Framework elevates the efficiency of algo trading strategies by providing a well-defined structure that presents a number of advantages over conventional design. The tool allows our quants to focus on their strengths and tap into the shared expertise of our open source community. As a result, every module of an algo can be top quality.”

Algorithm Framework is available at no cost to the QuantConnect community, which early this year reached a total of over 55,000 quants, computer scientists, engineers and professional traders who have designed and deployed more than 1.2 million strategies on the platform.

Late last year, QuantConnect introduced its Alpha Streams project, which enables the QuantConnect community to opt into licensing alpha-generating insights to quantitative funds, and has recently welcomed Tibra, a quantitative research and investment group, as its first client sourcing alpha.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

BLOG

TMX Agrees to Acquire Cboe Canada and Australia, Reshaping Canadian Market Structure

TMX Group has agreed to acquire Cboe Australia and Cboe Canada from Cboe Global Markets for US$300 million (C$409 million), in a transaction that removes TMX’s principal challenger in Canadian equities trading and listings and folds Cboe’s Australian venue into the Toronto-based operator’s growth ambitions. The Canadian component is by far the more consequential leg...

EVENT

AI in Capital Markets Summit London

Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...