red_flag_check
Combines five overfitting measures into a GREEN, AMBER, or RED deployment verdict with a 0–100 severity score, blocking deployment on RED.
Instructions
Requires the Stochastly desktop app: this tool runs inside the app, which is not installed on this machine. Install it from https://stochastly.com/pricing, open it and activate a licence.
Combine five overfitting measures into one deployment verdict, GREEN, AMBER or RED, with a
score from 0 (no red flag) to 100 (severe); RED sets deploy_blocked. Also returns each component and its contribution,
reasons, violations (diagnostic codes with severity), which measures were missing, and the
coverage needed for GREEN.
Use it to decide whether a configuration or run is fit to deploy. Pass null for anything you
did not measure: missing evidence lowers coverage instead of being guessed. Explain a code
from violations with diagnostic_explain; to try to refute a finished run, use
adversarial_check. Needs Stochastly open with an Atelier or Portfolio licence.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dsr | Yes | Deflated Sharpe ratio of the result; null if not measured. | |
| selection_score | Yes | Multiple-testing adjusted p-value (Romano-Wolf) returned by every run in `selection.score`; lower is better. null if not measured. | |
| realization_ratio | Yes | Real PnL divided by theoretical PnL, after frictions; null if not measured. | |
| oos_is_sharpe_ratio | Yes | Out-of-sample Sharpe divided by in-sample Sharpe; null if not measured. | |
| slippage_sens_delta | Yes | Change in realization_ratio when frictions are multiplied by 1.5; null if not measured. |