Skip to content

KB/signal

Re-entry / oversold triggers

Last verified

Auto-generated. This article is rebuilt from app/signals/config/signal_definitions.json by scripts/build_signals_kb.py. Edit the registry entry and re-run the script — do not edit this file directly.

Re-entry / oversold triggers

What it is

Re-entry / oversold triggers — registry key reentry_triggers.

Companion column to reentry_score; carries the active-trigger summary string. See app/signals/reentry.py.

Data-pyramid tier

T3 — Lens. This metric sits at the lens layer of the platform’s six-tier data pyramid (T0 raw inputs → T5 actionable read). The tier reflects how far the value is from a raw measurement — not how strongly it is validated. Abstraction and validation are separate axes: a higher tier is not a claim of stronger evidence.

Horizon & validation

No validated skill horizon is on file for this metric — read it as context / a data carrier, not a validated edge. Stamps are added only when a gated research verdict lands.

Source

Source module: capture
Data source: computed

Derived metric — produced inside the platform (app/signals/capture.py or equivalent) rather than fetched as a raw upstream value. See the How it's computed section below for the formula.

How it’s computed

Active-count prefix plus a semicolon-separated list of which re-entry triggers fired with each trigger’s value embedded (e.g. ‘4/4 triggers · SPY 6.0% below 50d SMA (deep flush, >5%); breadth 22% (capitulation); VIX 28.0 (fear spike); squeeze setup primed (bounce fuel)’). See app/signals/reentry.py:format_triggers.

Where it surfaces

Health-score / alignment role

Data carrier — no implication, no health-score contribution.

Persisted for downstream consumers (sparklines, base-rate matcher, calibration substrate) but does not classify into BULLISH / NEUTRAL / BEARISH and does not contribute to the 0-100 health score.

Release cadence

See also