Mean-Reversion & Order-Book-Adaptive Execution Platform

Customer

Challenge

• From quotes to decisions: Convert market-depth information into a robust central-price indicator to improve queue placement and reduce adverse selection.
• Data/venue constraints: Depth access varies by venue/provider; the platform must operate under connection and entitlement constraints.
• Operational realities: Opening/closing auctions, partial data, and roaming access can disrupt trading; guardrails are needed for reliability.
• Unified data hygiene: Maintain continuous futures and corporate-action-aware equities in the same environment for cross-asset visibility—without exposing instrument lists or roll rules.

Solution

Approach: A cross-functional squad—Quant/Tech Lead, Execution Engineer, Data/Infra Engineer, QA/Ops Analyst—delivered iteratively on cloud infrastructure.

Architecture & runtime

Hardened cloud nodes with secure remote access and entitlement management; centralized configuration + relational DB to manage instruments, parameters, and audit logs.

Order-book-adaptive execution

Built a depth-aware central price, standardized execution policy templates, and per-symbol depth acquisition modes to manage data constraints.

Cross-asset data hygiene

Integrated continuous futures series and dividend/corporate action updates into the runtime for consistent, cross-asset analytics.

Technologies & tools

Process

1. Kickoff & node prep — Cloud access, entitlements, parity checks with the existing research codebase.
2. Book-model prototype — Implement depth-aware central price; calibrate parameters on a pilot symbol set.
3. Execution refinements — Apply policy templates for placement/pacing; enable lot-sizing and visibility controls; add depth modes.
4. Auction/edge-case guards — Introduce auction-aware protections and self-order filtering; stabilize behavior across venues.
5. Data hygiene — Unify continuous-contract and dividend updates in the operational data plane; schedule quality checks.
6. Go-live & iterate — Deploy, monitor, and refine based on diagnostics and operator feedback.

Results

• Order-book awareness: Execution decisions incorporate depth conditions, improving consistency of queue placement and reducing avoidable adverse fills.
• Operational resilience: Depth-mode controls, auction protections, and hardened access support day-to-day reliability under data-plan constraints.
• Unified data plane: The same runtime maintains continuous futures and dividend updates for cross-asset oversight without exposing proprietary roll/adjustment rules.

Sanitization note: All indicator values, decay/weighting formulas, subscription counts, venue-specific behaviors, timing windows, symbol lists, and capital/lot rules have been intentionally generalized or removed.