Markets & Trading Systems
Backtests that survive contact with live markets.
We model fees, slippage, partial fills, and execution constraints so your edge estimate is grounded in reality.
Primary buyer fit
Dominant persona: Quant funds
Quant funds validating signal stability before allocation decisions and capital allocation reviews.
Also relevant for
- -Prop desks testing strategy variants across regimes and liquidity conditions.
- -Discretionary teams codifying repeatable playbooks into testable systems.
Problems we solve
- -Backtests that ignore realistic execution friction and overstate edge.
- -Research outputs that cannot be reproduced or promoted safely to live.
- -No shared acceptance criteria for strategy go/no-go decisions.
What we deliver
- -Event-driven backtest framework with realistic slippage, fees, and fill logic.
- -Reusable experiment templates and versioned parameter tracking.
- -Promotion checklist from research to forward-test readiness.
Frequently asked questions
What outcomes should we expect from strategy backtesting?
We align strategy backtesting work to measurable outcomes such as cycle-time reduction, quality improvements, and conversion or retention gains depending on your use case.
How long does delivery usually take?
Focused scopes usually land in 2-4 weeks. Broader implementations run 8-12 week pod engagements with weekly demos and clear milestones.
Can you work with our existing team and stack?
Yes. We typically work inside your stack and repo, follow your review process, and leave your team with clean documentation and handoff clarity.
How do you manage risk and quality?
We define acceptance criteria up front, ship in small increments, and track quality with explicit checks, observability, and rollback-safe delivery habits.
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