Correlation matrix
See which countries moved together—and which moved differently. Compare USD ETF returns in an interactive correlation heatmap.
Germany and France have the highest correlation (0.88). France and China have the lowest (0.46) across the covered countries.
Countries · Correlation
1Y · Daily · 253 common observations
Hover, tap or focus a cell for details. Minimum 20 observations.
2025-10-15 to 2026-10-16 · USD · Daily · 253 observations
Methodology and proxy coverage
Pearson correlation measures how closely two periodic return series move together, from −1 (opposite) to +1 (together). Values near zero indicate a weak linear relationship, not independence. Low historical correlation does not guarantee diversification benefits.
Source: adjusted USD closing prices for US-listed ETFs. Country proxies represent investable equity markets; sector proxies represent US equity sectors. These are representative exposures, not exhaustive constituent indices. Prices refresh with the US-market job; rankings remain separate monthly snapshots.
Calculation, sampling and interpretation
Default sampling matches the platform: 3M, YTD, 1Y and 2Y are daily; 5Y is weekly; MAX is monthly. Sampling can be changed independently. Weekly observations end on Friday, monthly observations at month-end; incomplete periods are excluded. MAX uses common available history, where meaningful history beyond five years is available.
Peers use aligned return intervals and a common observation window. Missing returns are not filled with zero. We require 20 daily, 8 weekly or 6 monthly common observations; missing, insufficient and relatively stale histories are excluded and disclosed with the chart.
Pearson correlation equals covariance divided by the product of the two return standard deviations. It uses periodic returns, not prices or cumulative returns. Constant-return series have undefined correlation. Estimates change with the selected period and frequency.
Colour bands are fixed display conventions, not statistical significance tests: low/uncorrelated −0.25 to +0.25 (green); moderate 0.25 < |r| < 0.70 (grey); strong negative −1 to −0.70 (blue); strong positive +0.70 to +1 (coral). Self-correlations are subdued; missing values are shown as unavailable.
Adjusted prices include provider split and distribution adjustments. Full histories are reconciled monthly and can be revised. USD results reflect ETF fees, currency exposure and US trading hours; today’s proxy selection does not recreate historical constituent membership. Historical comparisons are descriptive, not investment recommendations.
Which proxies are included?
Asset classes
Equities (SPY) · Fixed income (AGG) · Real estate (VNQ) · Gold (GLD) · Broad commodities (DBC) · Cash (BIL)
Sectors
Technology (XLK) · Financials (XLF) · Health Care (XLV) · Consumer Discretionary (XLY) · Consumer Staples (XLP) · Energy (XLE) · Industrials (XLI) · Materials (XLB) · Utilities (XLU) · Real Estate (XLRE) · Communication Services (XLC)
Countries
United States (SPY) · Japan (EWJ) · United Kingdom (EWU) · Germany (EWG) · France (EWQ) · China (MCHI) · Hong Kong (EWH) · Singapore (EWS)
Volatility definition · Rankings methodology · Published 2026-10-17