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A1 post-earnings triggers

What it is

A1 post-earnings triggers — registry key a1_post_earnings_triggers.

Human-readable list of fired conditions from the A1 scorer (e.g. [‘gap -11.2%’, ‘EPS surprise +4%’, ‘RSI 31->38’, ‘quality:pass’]). Serialized as a JSON array string in the candidates table. Mirrors the squeeze_setup_triggers convention.

Data-pyramid tier

T1 — Signal. This metric sits at the signal 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: screener
Data source: computed

Derived metric — produced inside the platform (app/sources/screener.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

List of triggered condition strings assembled in evaluate_post_earnings_overreaction. Each string describes one fired predicate with its observed value. See app/screener/archetypes.py.

Where it surfaces

• API field: screener.candidates.a1.triggers on GET /api/v1/signals/latest

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

• Publishes: daily