AUTONOMOUS-FOX
LABORATORIES
About us
What we do....
We’re a newly established research lab dedicated to advancing machine learning for systematic trading systems. Innovative, independent, and focused, our work centres on developing generative and predictive models that power a wide range of trading strategies . built to infer structure, adapt to changing market conditions, and uncover predictive signals on a vast scale.
Our objective is simple: to build a new breed of neural intelligence for financial markets — the first generation of foundation models designed to power systematic trading systems
Some are bulls, others bears.
We are foxes, we craft intelligent systems to discover opportunities in all markets.
Building the next generation of trading systems, powered by our proprietary neural arbitrage engine
Embracing Complexity
Markets are not just a collection of independent prices; they are adaptive webs of interaction. Our models capture interdependencies and transient relationships, uncovering mispricings that emerge when complex equilibria are temporarily disrupted.
Going Deeper Than Ever Thought Possible
Over the past decade, deep learning has revolutionised entire industries — while finance sat on the sidelines watching and waiting. AI has transformed vision, language, and biology, however financial modelling was left behind. The reason is simple: markets pose a much harder problem. Data is messy, relationships unstable, and structure always changing. Deep learning wasn’t built for that world — not then. But now that’s changing. Advances in machine learning and neural methods more generally, are finally giving us tools that can understand markets on their own terms, allowing us to build systems that can learn meaning, not just basic patterns. In 2025, the gap between deep learning capability and market reality is closing fast, and a new generation of quantitative trading models is about to emerge. At AF Labs, we intend to be right at the front of that renaissance.
Behaviours Over Statistics
Our approach is centered on behavioral modeling. We view markets as a collection of assets exhibiting quantifiable behaviours. Traditional statistics cling to assumptions of stability and order that markets rarely honour. They describe what has already happened and infer that it will happen again. Strip away the assumptions, and you’re left with noise — not foresight. Instead, we believe that behaviors constitute the very language of the market, and how those behaviours play off one another over time is the story. Behavioural modelling represents the next paradigm for understanding complex systems — and deep learning is the mechanism through which we can learn to interpret that language.
A Model for All Markets
We hesitate to use the F-word --we're not quite there yet, but our design philosophy of behavioural modelling is deliberately agnostic to any single asset or market.
Rather than fitting to surface patterns, our models seek the latent structures that govern how systems evolve and adapt — a framework capable, in principle, of generalising across the entire market ecology.
In this view, behaviors form the vocabulary of the market's language, and their interactions are the conversations through which structure emerges, followed by comprehension.
Dare we suggest, it is a first step toward a foundation model for financial markets.
Experience and Expertise
15+
Years of Experience in quantitative financial market modelling
11+
Years of Experience in Machine Learning
100s
Trading Models Developed
100%
of researchers are PhDs
1
Objective
Join the Team
We are looking for exceptional machine learning experts to join our small but growing team of research scientists at a founding level. In particular, we seek specialists in representation learning and probabilistic / generative modelling — in other words, wizards with the ability to bend neural architectures to their will.
If you hold a PhD in computer science or a related field (theorists included) and want to tackle some of the hardest problems humanity has ever faced, we’d love to hear from you.