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SPY/Oil Correlation

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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.

SPY/Oil Correlation

What it is

SPY/Oil Correlation — registry key corr_spy_oil.

Classifier metric. See the bands table below for the band-by-band reading.

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: 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

20-day rolling Pearson correlation of daily SPY returns vs daily USO returns (oil ETF proxy). From daily_signals.spy_close / uso_close. Computed inside capture via app/signals/correlations.py:compute_rolling_correlations (pair spy_oil).

Where it surfaces

Bands / thresholds

Classifier direction: range_is_better.

Range Label Dot Implication Points
-0.3 – 0.2 Normal favorable NEUTRAL —
-0.5 – -0.3 Elevated negative cautionary NEUTRAL —
0.2 – 0.5 Elevated positive cautionary NEUTRAL —
< -0.5 Extreme negative adverse BEARISH —
≥ 0.5 Extreme positive adverse BEARISH —

Health-score / alignment role

Release cadence

See also