Foreign Exchange Rates

Interpretation

The charts above show the exchange rates of various currencies against the US Dollar (USD). An upward trend represents an appreciation of the currency against the US Dollar, signaling either a strengthening of that currency or a weakening of the USD. Conversely, a downward trend indicates a depreciation of the currency against the USD. These fluctuations in exchange rates play a critical role in the global financial landscape, impacting international trade, investment strategies, and economic policies. They serve as a barometer of a nation's economic health and are closely monitored by investors, economists, and government officials for making informed decisions.

Interpretation

This heatmap reveals how major currency pairs (quoted against the USD) move in relation to each other. Red squares show a positive correlation (currencies moving in the same direction against the dollar), while blue indicates a negative correlation. Notice how currencies from the same economic region, like the Euro and Swiss Franc, often cluster together, while safe-haven currencies like the Japanese Yen may move differently.

For forex traders and international investors, understanding these correlations is vital for managing risk. A portfolio of long positions in highly correlated currencies (e.g., AUD and NZD) is not well-diversified. Combining assets with low or negative correlations, as Ray Dalio suggests in his “Holy Grail of Investing” principle, can create a more balanced exposure.

To create this chart, weekly changes in the exchange rates are calculated, and the Pearson correlation is computed for every pair. The heatmap is then organized using hierarchical clustering to group the most similar currency pairs together, making market patterns easier to see.

Interpretation

The Minimum Spanning Tree (MST) simplifies the correlation matrix by showing only the strongest connections between currency pairs. If two currency pairs 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 currency pairs 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.