🔗
Cross-Asset Correlation Scorecard
Rolling Pearson correlation between crypto assets and between crypto and macro indicators, computed from 1-minute OHLCV data.
Signal Quality
| Period | Accuracy | Samples | Significance |
|---|---|---|---|
| 7d | 67% | 168 | ⚠️ Low sample |
| 30d | 65% | 720 | ⚠️ Low sample |
| 90d | 63% | 2,160 | ✅ Significant |
Calibration: Regime transition prediction: % of time that de-correlation events (coherence < 0.7) preceded regime changes within 4h.
Current Reading
Current Value
99.4000
alpha_geo_coherence
Methodology Version
v1.1 (2025-12)
Current cross-asset coherence vs 30-day distribution.
24h History
301 data points · alpha_geo_coherence
Strengths & Weaknesses
✅ Strengths
- Leading indicator for regime changes
- Unique dual-citadel geo-coherence metric
- Good for portfolio hedging
Best regime: transition periods
⚠️ Weaknesses
- Slow update frequency
- Can give false signals during low-volume weekends
- Requires sufficient data history
Worst regime: stable trending markets
Methodology Changelog
| Date | Version | Change |
|---|---|---|
| 2025-12 | v1.1 | Added geo-coherence (EU vs NA node correlation) |
| 2025-07 | v1.0 | Initial launch with BTC-ETH rolling correlation |
Related
Don't just stare at the dashboard. Automate it.
Every metric on this page is available via our sub-millisecond API.
Build trading bots, backtest strategies, and power AI agents with institutional-grade data.