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.

A2 sympathy selloff borrowed-drop score

What it is

A2 sympathy selloff borrowed-drop score — registry key a2_sympathy_score.

Raw dislocation score for A2 oversold sympathy selloff: abs(borrowed_drop_pct) = abs(own_ret_pct - beta_60d * sector_ret_pct). Larger absolute value = more of the drop is unexplained by sector beta. Computed only when state is partial or primed; 0.0 otherwise.

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: 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

borrowed_drop_pct = own_ret_pct - (beta_60d * sector_ret_pct). score = abs(borrowed_drop_pct) when core conditions pass, else 0.0.

Where it surfaces

• API field: screener.candidates.a2.score 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