Proprietary capital only
We trade our own balance sheet. No outside money, no investment products, no customers. Ever.
Proprietary Principal Trading
We test ideas early, expose weak assumptions, and learn from every miss. That cycle turns small, controlled failures into sharper research, stronger systems, and better decisions before our own capital is at risk.
We are engineers who trade and traders who build, risking only our own capital. That structure keeps incentives clean, decisions fast, and discipline absolute.
Every strategy we run begins as a research question and ends as production software. Researchers and engineers work side by side, so the distance between an idea and a live, risk-controlled position is measured in weeks, not quarters.
Because we have no clients and accept no outside investment, we are accountable only to our own risk standards, and we hold them deliberately high. Capital preservation is not a department here. It is the operating system.
We trade our own balance sheet. No outside money, no investment products, no customers. Ever.
We challenge ideas early and often. Every failed test gives us evidence to learn from, improve, and test again.
Limits are enforced in software, not by exception. No strategy outranks the controls that govern it.
We run systematic strategies across global markets, with infrastructure tuned to the microstructure of each venue we trade.
Global single-name and index equities, with smart order routing across lit and dark venues.
Index, rate, and commodity futures traded over co-located connections to CME, ICE, and Eurex.
Volatility and directional strategies executed as multi-leg structures with automated hedging.
Institutional liquidity across major, minor, and emerging-market pairs, through every session.
Spot and derivatives on the largest tokens: markets that never close, and infrastructure that doesn't either.
Our edge is engineered. Research, execution, risk: every system in the stack is proprietary and purpose-built.
Petabyte-scale market data, high-fidelity simulation, and transaction-cost models calibrated to live conditions.
Low-latency pipelines with sub-millisecond decision paths and intelligent order routing across venues.
Real-time exposure monitoring, hard limits enforced in code, and automated kill switches at every layer.
Quantitative researchers turn market observations into clear, testable hypotheses.
We pressure-test assumptions early with rigorous simulation, realistic costs, and strict out-of-sample testing.
Every result, especially a failed test, becomes evidence we use to refine the idea or move on quickly.
Only validated strategies reach production, with comprehensive monitoring, hard risk controls, and continuous review.
Bars and Code is fully remote and deliberately small. We look for exceptional engineers, researchers, and traders who test boldly, learn openly, and improve quickly. Here, a failed experiment is useful when it produces a better answer.
Introduce YourselfDistributed systems, low-latency execution, market data infrastructure.
Statistical modeling, machine learning, strategy development.
Systematic execution, market microstructure, risk management.
We welcome serious inquiries from candidates and counterparties. Every message is read by someone who can act on it.