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The chart above gives a different view of the same data from the ratios above. Presented below are brief sector descriptions along with some example companies.

This heatmap shows how different sectors of the US stock market—like Technology, Health Care, and Energy—move in relation to each other. Red squares indicate a positive correlation (sectors moving together), while blue shows a negative correlation. As expected, most sectors are positively correlated, as they are all part of the broader US economy.
Understanding these relationships is useful for sector rotation and diversification. Sectors with lower correlations, such as Utilities or Energy, can help balance a portfolio that is heavily weighted in more cyclical areas like Technology or Financials. This is a domestic application of Ray Dalio's principle of using uncorrelated assets to reduce risk.
To create this chart, weekly returns are calculated for each sector index, and the Pearson correlation is computed for every pair. The heatmap is then organized using hierarchical clustering to group sectors with the most similar performance, revealing the underlying structure of the US market.

The Minimum Spanning Tree (MST) simplifies the correlation matrix by showing only the strongest connections between sectors. If two sectors are linked, they have a strong positive correlation and tend to move in tandem. This helps identify clusters of related assets and is useful for portfolio diversification.
The tree is constructed by converting the correlations into distances and then finding the set of connections that links all sectors with the minimum total distance. As noted by Marti, Gautier, et al. (2017), the optimal Markowitz portfolio is often found at the tree's outskirts, and the tree tends to shrink during a financial crisis.
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