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Correlation Matrix

See at a glance which assets move together and which offset each other.

What is a correlation matrix?

A correlation matrix is a grid showing the pairwise correlation between every combination of assets in a set. Each cell holds a number from −1 to +1: +1 means two series move perfectly together, −1 means perfectly opposite, and 0 means no linear relationship. Rendered as a colour-coded heatmap, it lets you scan an entire portfolio's co-movement structure in one image and spot genuine diversifiers instantly.

Cross-Asset Correlation Matrixheatmap

Illustrative correlation matrix across five macro assets. Values are for demonstration only.

Diversification lives or dies on correlation. Two assets that both fall together in a crisis provide far less protection than their individual volatilities suggest. This tool renders a correlation matrix across five macro assets as a heatmap so you can read which pairs hedge each other and which merely double up on the same risk.

Reading the grid

The matrix is symmetric — the correlation of A with B equals that of B with A — and its diagonal is always 1, since every series is perfectly correlated with itself. Deep positive cells flag assets that rise and fall in unison; deep negative cells flag natural hedges. The value of the whole view is peripheral: your eye catches clusters of similarly coloured cells that reveal which holdings are really the same bet in disguise.

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Colour scaling is what makes the matrix legible. A diverging palette centred on zero — cool for negative, warm for positive — lets you separate diversifiers from redundant exposures without reading a single number. Sorting the rows and columns so correlated assets sit adjacent turns scattered relationships into visible blocks, a technique borrowed from clustered heatmaps.

Why correlations are not constant

The dangerous property of correlation is that it moves, and it tends to move at the worst time. In calm markets a portfolio may look well diversified, with many low or negative pairwise correlations. In a crisis those correlations often spike toward 1 as investors sell everything at once, and the diversification you counted on evaporates. Any correlation matrix is a snapshot of one period, not a permanent structural truth.

How Quadesto computes it

Quadesto takes your set of return series, computes the Pearson correlation for every pair, and renders the result as a heatmap with a diverging colour scale centred on zero. You choose the lookback window, so you can compare a calm-period matrix against a stress-period one. The heatmap above is built from a table of x, y and value triples, and the matrix embeds into risk and allocation reports.

Build this with your own data

Upload a CSV or connect a live source, and Quadesto renders this exact chart — styled, computed, and embeddable in your reports and newsletters. Free to start.

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Frequently asked questions

What does a correlation of −1 mean?
A correlation of −1 means two series move perfectly in opposite directions — when one rises a set amount, the other falls proportionally. Such pairs are ideal hedges. In practice perfect −1 is rare; strongly negative values like −0.5 already provide meaningful diversification within a portfolio.
Why is the diagonal always 1?
The diagonal holds each asset's correlation with itself, which is always exactly 1 because a series moves in perfect lockstep with its own values. It serves as a reference line; the informative cells are off-diagonal, showing how different assets relate to one another.
Do correlations change over time?
Yes, substantially. Correlations shift with market regime and often spike toward 1 during crises, when investors sell many assets at once. A matrix computed over calm periods can badly understate how correlated a portfolio becomes under stress, so it is wise to examine multiple windows.
What is the difference between correlation and beta?
Correlation measures the strength and direction of a linear relationship on a −1 to +1 scale, independent of scale. Beta measures the slope — how much one series moves per unit move in another. Two pairs can share a correlation yet have very different betas, so they answer different questions.
Can I build a correlation matrix from my own data?
Yes. Upload several return series to Quadesto, pick a lookback window, and the engine computes every pairwise correlation and renders a colour-coded heatmap. Compare calm and stressed periods and embed the matrix in diversification and risk reports.