Pulse is the quantitative research module inside Atlas: 18 years of exchange-sourced market data, an engineered feature library, and a validation pipeline every model must pass before deployment. Negative results are documented with the same rigor as positive ones.
Research effort concentrates on informative representations of market state — price structure, volatility regime, microstructure, time-of-day, trend state — each validated for incremental predictive value and monitored for decay as market conditions change. Admission to the library is itself gated: every candidate feature is tested against calibrated noise floors before use, and rejections are recorded alongside admissions. Model architectures are commodity components; the feature library and the validation infrastructure are the durable assets.
Candidate models are evaluated walk-forward on held-out data, against permutation-based significance floors, with explicit multiple-testing control. The process is symmetric about outcomes: when short-horizon direction prediction was tested across two feature generations and horizons from three to forty minutes, no statistically significant edge was found — the program was closed and the result documented. The model class that passed validation answers a narrower question: the probability of significant near-term movement, independent of direction.
The first production model estimates the probability of a significant index move within the next fifteen minutes. It was trained on 18 years of data and evaluated on a held-out period excluded from all training and tuning.
On the Terminal, the model surfaces as a single tile: the current probability, its confidence level, and the validation claim it is graded against. Scores carry their timestamps; a stale score is displayed as stale. The model is advisory — it does not place, size, or block orders.
Every published score is recorded at serving time. Realized outcomes are evaluated nightly against the claims made at validation — realized precision versus validated precision — and the resulting scorecards accumulate in the desk's reports. Promotion beyond observe-only mode requires sufficient forward evidence, a requirement enforced by the platform rather than by convention. Models whose forward performance decays are retired through the same registry process that deployed them.
Design principle: staged rollout constrains a model's authority, not its quality. The best validated model serves — monitored, graded, and subordinate to pre-trade risk checks on every order.
The architecture is designed for a portfolio of narrow, individually validated models — each answering one question, each monitored and replaceable — rather than a single general predictor. The registry, validation pipeline, and forward-grading machinery that govern the first model are built to govern many, across instruments and timeframes. The current expansion applies the same discipline beyond the intraday index tape: a daily cross-sectional panel spanning the full NSE equity universe, with delistings and symbol changes handled point-in-time.