Legal & Data

AI & Backtest Disclosures

Disclosures for generated scans, AI analysis, hypothetical backtests, and why simulated outcomes must not be treated as expected live results.

Back to legal hub/Updated April 12, 2026

AI output limitations

AI-generated content may be incomplete, misleading, stale, overconfident, or simply wrong.

Generated formulas, scan drafts, explanations, and summaries must be reviewed by the user before use.

Backtest limitations

Backtests, simulations, hypothetical rankings, and model outputs are hypothetical and have material limitations.

They may omit or simplify slippage, liquidity constraints, borrow availability, market impact, execution quality, halts, session behavior, partial fills, stale data, survivorship effects, and operational failure modes.

No performance promise

A backtest or AI explanation does not represent actual trading and should not be treated as a promise, forecast, or expected outcome.

Live performance can differ materially from historical or simulated results.

Best use

  • Use AI and backtests to generate ideas, test assumptions, and accelerate workflow.
  • Do not rely on them as a substitute for independent review, risk controls, and execution discipline.