Individual skill
correlation-regime
Correlation-regime detection and crisis attribution — edge-density regime states with hysteresis, causal (no look-ahead) smoothing, regime-aware exposure context, first-mover crisis attribution with honest NAME / MACRO / AMBIGUOUS / ABSTAIN verdicts, and a correlation-rewiring leaderboard that catches slow bleed-outs
agent/src/skills/correlation-regime/SKILL.md
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- Last checked
- Nov 9, 2026
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- Repository last updated
- Nov 8, 2026
- License
- MIT
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- backtesting Repository topic
- multi-agent Repository topic
- quantitative-finance Repository topic
- trading Repository topic
- ai-agent Repository topic
- algorithmic-trading Repository topic
- fintech Repository topic
- llm Repository topic
- mcp Repository topic
- python Repository topic
- engineering Derived category
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# Correlation-Regime Detection and Crisis Attribution
## Overview
The `correlation-analysis` skill answers *"how correlated are these assets?"* — a snapshot.
This skill answers the temporal questions a snapshot cannot:
1. **When** did the market fuse into one highly-correlated bloc, and when did it release?
(Mode 1 — regime detection)
2. **What** does a fused regime mean for position sizing? (Mode 2 — risk context)
3. **Who** moved first when a crisis broke — is there a nameable trigger asset?
(Mode 3 — first-mover attribution)
4. **Who** quietly rewired their relationship to the rest of the market, even without a
violent move? (Mode 4 — rewiring leaderboard)