We start with a clear hypothesis: a research-driven idea about perps, market microstructure or CEX/DEX/OTC dislocations that we can express in data.
We close the loop by feeding live results, P&L decomposition and anomaly cases back into research, refining models, infrastructure and team practices for the next iteration.
We turn that idea into models and simulations, build systems that stress-test thin books and define how our strategies should behave.
Once deployed, our routing and execution systems run continuously, monitoring venue conditions, latency and fill quality while staying within predefined risk and exposure boundaries.
When dislocations appear, our systems act in real time, but every decision path is observable and attributable, so post-trade analysis is built in rather than bolted on.
Before anything touches the market, we challenge the design as a team — engineers and traders review edge cases, failure modes, latency-sensitive execution paths and risk limits together.