Documentation
VeriRun Lab documentation
Everything you need to take a futures-strategy idea from a plain-English sentence to an honestly graded backtest — and to keep your research organized along the way. Every guide is written end-to-end: follow one top to bottom and you will have done the real thing in the app.
The research loop at a glance
VeriRun Lab is built around one loop, and the docs follow it in order:
- Describe or write a strategy — with the AI Strategy Builder or by hand in the workspace IDE.
- Test it. A required suite of tests proves the code does what the strategy says. Nothing runs on data until the tests are green.
- Preview it. A fast, idealized run over a few sessions shows you what the strategy actually does on a chart.
- Backtest it. A conservative, research-grade run produces an A–F scorecard with a pre-committed GO / NO-GO verdict.
- Keep the evidence. Every run lands in your library — pin it, annotate it, compare it, export it.
Getting started
Create your account, sign in, make your first project and workspace. Ten minutes, start to finish.
AI Strategy Builder
Describe an idea in plain English, answer clarifying questions, review the Brief and the generated code — and stay in control of every change.
AI coding agent
Change existing code conversationally: the agent reads, proposes a diff, runs the checks, and applies nothing until you accept — plus how to switch models on the fly.
Writing strategies by hand
The workspace IDE: what every file does, the strategy contract, the market data available to your code, and snapshots you can always roll back to.
Indicators & features
The full reference: around 48 technical indicators, pivot systems, and a deep order-flow suite (footprint, delta, value area, absorption) your strategies can read.
Testing your strategy
The twelve required test cases, how to run them, and why Preview and Backtest stay locked until they are green.
Preview & Backtest
Idealized teaching fills versus conservative realistic fills, how to read the chart, and what the debug trace tells you.
The scorecard
What A–F measures, why a NO-GO caps the grade, and why an honest NO-GO means the system is working.
The run library
Pin, annotate, compare and export runs — and read the regime, stress and price-path robustness views correctly.
Optimization
Search your strategy's parameters with a study — scored on the train window only, the test window shown but never scored, and a multiple-testing verdict on every rank.
Screener
Fan one approved strategy across many instruments and timeframes in a single run, then rank the results — with correlated markets counted once.
Notebooks
Free-form research code next to your strategy, including a research backtest call — and the limits it runs under.
Meta-labeling
Train a secondary model to gate your signals, then read it out-of-sample: precision, recall, lift, ROC-AUC, feature importance, and a precision-vs-coverage sweep.
Journal & firm tools
Log trades, import fills, attach screenshots, build playbooks and goals, track prop-firm rules and evaluations, and replay real trades through a firm's payout math.
External agents (MCP)
Drive the platform from your own AI coding agent over MCP: a read-first research surface with scoped machine tokens and human-accepted draft edits.
Data & credits
What the data is, how usage and credits are shown, and how to read the cost estimate before you launch a run.
One thing to know before you start
VeriRun Lab is deliberately conservative. Backtests fill your orders under pessimistic rules, the grading gates are fixed before a run, and a strategy that fails them gets a NO-GO — clearly, and on purpose. If you are used to backtesting tools that flatter you, some verdicts here will feel harsh. That is the product working as designed: a result you can trust is worth more than a result you like.
Research tooling, not trading advice
Everything the platform produces is a research result — probabilities, not promises. Nothing in the app or these docs is a recommendation to buy or sell any instrument.