Correlation Matrix shows how major crypto assets move together using Pearson correlation of daily log returns.
High average correlation means the book is synchronized; low correlation means more idiosyncratic moves.
What it measures
Universe: majors on Binance USDT spot (BTC, ETH, SOL, and peers).
Method: Pearson correlation on daily log returns for 7d / 30d / 90d windows.
Heatmap cells, top/bottom pairs, and average off-diagonal correlation summarize the regime.
How to read it
Red cells = strong positive co-movement; blue cells = negative or inverse moves.
Synced / elevated regimes often appear in risk-on or risk-off sweeps.
Dispersed / decoupled regimes can favor relative-value or single-name trades.
Compare 7d vs 90d — short windows catch shocks; long windows show structural ties.
Using Correlation Matrix on PEPS Crypto
Pick 7D / 30D / 90D, read the average regime, then scan the heatmap.
Click a cell or pair row for the exact coefficient.
Use highest pairs to spot clusters; lowest pairs for potential diversifiers.
Combine with BTC dominance and market breadth tools for macro context.
How it works
- Data refreshes about hourly from Binance daily candles via ccxt.
- Returns are log(close_t / close_t−1); diagonal is always 1.
- Regimes: Synced ≥0.75, Elevated ≥0.55, Moderate ≥0.35, Dispersed ≥0.15, else Decoupled.
- Delta compares average correlation to the previous PEPS snapshot for that window.
- Missing cells appear when a symbol lacks enough overlapping observations.
What to consider
- A crash can push most pairs toward +1 even if narratives differ.
- Stable or idiosyncratic names can look “low corr” without being hedges.
- Always confirm with volume and flow tools before acting on pair ideas.
- Highest/lowest lists are descriptive, not trade recommendations.
- Pair with Market Stress when average correlation spikes.
Frequently asked questions
- What does a high average correlation mean?
- Assets in the matrix are moving together. Diversification inside crypto is weaker in that window — beta and factor risk dominate.
- Why Pearson on log returns?
- Log returns are standard for multi-asset co-movement and are additive over time. Pearson is the common linear correlation coefficient.
- Why only ~15 majors?
- Focus stays on liquid USDT pairs with reliable daily history so the heatmap stays readable and statistically meaningful.
Conclusion
Correlation Matrix answers how synchronized major crypto returns are right now.
Use it to judge cluster risk, then confirm with breadth, narrative, and flow tools.