How to use Correlation Matrix Visualizer
Paste a multi-asset returns CSV. The page renders the Pearson correlation heatmap, computes condition number, average absolute correlation, and eigenvalue concentration — the diagnostics that flag undiversified portfolios.
What It Does
Use the calculator with intent
Paste a multi-asset returns CSV. The page renders the Pearson correlation heatmap, computes condition number, average absolute correlation, and eigenvalue concentration — the diagnostics that flag undiversified portfolios.
PMs and risk engineers who suspect the portfolio is less diversified than the holding count suggests and want the matrix-level evidence.
Interpreting Results
High condition number (>30) means one factor dominates — the portfolio is effectively a one-bet position. Average absolute correlation above 0.5 means most diversification benefit is gone. The eigenvalue plot tells you how many independent risk dimensions you actually have.
Input Steps
Field by field
- 1
Upload data
Upload return series for the asset universe (rows = time periods, columns = assets).
- 2
Pick option
Pick correlation type: Pearson (linear), Spearman (rank-based, robust to outliers).
- 3
Toggle setting
Toggle Ledoit-Wolf shrinkage if the asset count approaches or exceeds the observation count.
- 4
Read outputs
Read the heatmap. Hierarchical clustering reorders assets so related groups appear as visible blocks.
- 5
Identify
Identify diversification gaps: clusters with low cross-correlation are diversification candidates; clusters with high mutual correlation are concentration risk.
Common Scenarios
Use realistic starting points
Equity-heavy book
Assets
10 large-cap equities
Period
1 year daily
Condition number typically 5–10x; one large eigenvalue captures market beta. The 'diversified' equity book is a single market-beta bet in disguise.
Multi-asset book
Assets
stocks + bonds + commodities + FX
Period
3 years daily
Condition number lower, eigenvalues more spread. Genuine diversification shows up here, not in equity-only baskets.
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FAQ
Questions people ask next
The short answers readers usually want after the first pass.
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