We are a leading technology- and research-driven trading firm. Our teams of scientists, engineers, mathematicians and traders push the boundaries of machine learning and quantitative methods to drive trading performance across markets, products and time zones. Powered by a global platform built for rapid iteration, we turn insights into alpha at the speed of your ideas.
Markets are high-speed, competitive and dynamic. We bring teams into one performance loop to build the models, systems and strategies that win in global markets.
Engineers build the platforms behind every trade and every outcome. From low-latency C++ and FPGA hardware to large-scale data platforms and AI-first workflows, we build for scale, resilience and speed of innovation.
Our researchers use deep learning, LLMs, statistical modelling and reinforcement learning to identify patterns across vast, dynamic market and alternative datasets. Infrastructure designed for rapid experimentation gives ideas a fast path to production.
Trading teams apply probabilistic reasoning to order flow, volatility, risk and dynamic market structure. They set prices, manage exposure and work close to research and engineering to extract predictive signal and turn it into actionable trading decisions.
At this volume, a 1% improvement is large enough to measure and fast enough to act on. A change to a pricing model, risk signal or execution path can show up across millions of live decisions, turning market feedback into the next iteration.
Petabytes of market data processed daily
40 years of compounding experience
Since 1986, we have continuously adapted as markets evolve, from a local trading operation into a leading global liquidity provider. Four decades of historical market data, broker relationships and market knowledge give today’s teams a stronger foundation for what comes next.
Each venue brings its own protocols, rules and market structure. Building across that landscape demands systems that stay reliable under different constraints, while giving teams a consistent view of how strategies perform globally.
We price across a broad universe of instruments, from options and ETFs to equities, bonds and currencies. The challenge is breadth with precision: modelling relationships across products, venues and conditions as they change.
Shared incentives, open context and flat structures keep the distance between a strong idea and a live result short. Traders, researchers and engineers work in one performance loop, so what proves itself can be reused, improved and scaled.
For the past several years, US stock investors have hedged their portfolios largely by looking at their calendars. Fed meetings, CPI prints, elections – whenever an event appeared on the horizon, investors would look to short-dated options to protect against the possibility of volatility.
While Brazil’s securities borrowing and lending framework has its strengths, it still trails global peers. In this paper, we propose steps to modernize the country’s SBL system, without compromising safety.
The United States Department of Agriculture (USDA), trading exchanges and other agricultural-related publications have published several articles recently regarding the Mississippi River’s water levels.[1] In this paper, we join them in highlighting the tremendous importance of the Mississippi to the US economy, as well as exploring the relationship between its water levels and agricultural derivatives markets.
