AI Stock Forecast Accuracy & Validation — Probabli.AI
How to evaluate Probabli.AI forecast accuracy using timestamped, horizon-matched, supportable measurements without guaranteed-return claims.
Probabli.AI does not publish a verified platform-wide accuracy rate today. A supportable score requires timestamped forecasts, fixed rules, completed horizons, and all eligible results rather than selected examples.
Measurable validation criteria
- Point error: compare the P50 estimate with the observed price at the matching horizon.
- Range coverage: measure how often the observed price falls between P10 and P90.
- Scenario calibration: compare stated scenario weights with later outcomes under a published outcome rule.
- Direction accuracy: compare forecast direction with the security's later return from the same start date.
Rules for supportable claims
Freeze the forecast, model, input timestamp, starting price, and horizon before the outcome. Include misses and delisted securities; adjust for splits; report sample size, dates, metrics, exclusions, fees, and taxes; and keep different horizons separate.
Current status
Stock pages expose the saved analysis date, but a timestamp alone does not establish accuracy or calibration. No audited or statistically validated accuracy percentage is claimed. Until enough forecasts reach their stated horizons, outputs should be treated as research scenarios rather than evidence of a repeatable return advantage.
Read the forecast methodology for definitions, data provenance, model handling, update frequency, and limitations.
The information on this page is for educational and informational purposes only and does not constitute professional financial advice.