Help Center

• Getting startedApply, accept your invitation, subscribe, and run a first strategy.
• Describing a strategyWhat to write so the backtest tests your rules, and why some numbers are confirmed before a run.
• Reading resultsThe metrics on a result, the Honesty Score and its caps, verdicts and warnings.
• Market dataWhich markets run, bar sizes, how far back a test reaches, and why prices are not shown.
• Prop-firm simulatorWhat /deploy models, where each firm’s rules come from, and what it cannot see.
• CommandsThe slash commands you can use, and what each one does.
• Your own codePasting Pine Script, running your own Python, and what happens to a rule that cannot be translated.
• Limits and billingUsage limits, what uses the AI budget, cancelling, and your right to withdraw.
• FAQAdvice, orders, charts, whole units, the starting account, and why TradingView differs.

You describe a trading strategy in plain English. The AI writes it as Python code for a backtesting.py strategy, and a sandboxed engine runs that code on historical market data. The result shows what the strategy did, an Honesty Score that marks down results that look better than the evidence allows, and warnings for anything that does not add up. From there you can validate it across many splits of its history, stress it with Monte Carlo, or simulate a prop-firm evaluation.

QuantWright is research software. It never places orders, and nothing it shows is investment advice.