QubeAlgo, which has been live with a select group of clients, is now being rolled out to the broader market, providing highly customizable solutions that empower quants and developers to build bespoke, multi-asset, electronic trading applications, often with minimal code.
QubeAlgo’s asset-agnostic software (Qube) is designed to significantly speed up development of complex e-trading applications, making it much easier and more cost-effective to develop, test, and deploy sophisticated e-trading models and algorithms.
Co-founders Martin Zinkin and Jeff Leal have spent their careers building award-winning quantitative and algorithmic trading frameworks inside top-tier investment banks, laying the foundation for the launch of QubeAlgo. Zinkin has led electronic trading businesses at Deutsche Bank, BNP, Nomura, and Lehman Brothers, among others, while Leal headed quantitative electronic trading teams at BNY Mellon, Nomura, Lehman, and digital assets investment firm, Monochrome Asset Management.
Now they’re leveraging their expertise to make the building blocks for algo trading available to the broader market. “We’ve built similar solutions to Qube at our previous firms, and now in its 5th generation, it is evenmore powerful than its predecessors,” says Zinkin. “We’ve spent a lot of time over the years on low level technology, on build and deployment issues, data and environment, and cumbersome testing processes. We had a vision of a system that would allow quants and developers to be much more productive and allow them to focus instead on models and business logic.”
Build vs Buy no longer a debate
Qube offers a solution to the build vs buy dilemma by combining the concepts - clients can completely own the code, freeing themselves from vendor release cycles and reducing internal development costs, with the added bonus of being able to effortlessly add proprietary functionality without leaking this to technology providers.
“Qube allows quants and developers to iterate rapidly and with high confidence - this is where the uniquereplay and back-testing framework comes into play,” says Leal. “Qube helps reduce some of the uncertainties naturally introduced in the software development lifecycle (SDLC) of electronic trading builds. This is extremely powerful in providing assurances that the deployed applications will perform as expected.”
Qube excels in environments where a small-to-medium team of quants or quant/developers are able to collaborate and produce fast and iterative enhancements to the e-trading stack, including smaller banks, quant funds, market makers, and asset managers looking for more automated solutions across both traditional and digital assets.