Headline CPI vs Headline PCE: Correlation Analysis
Pearson correlation of daily returns for CPI (All Urban) and PCE Price Index. Rolling windows, yearly breakdown, regression beta, and divergence analysis. Data window spans to (56 aligned observations).
What the Number Means
With a correlation of 0.92, CPI (All Urban) and PCE Price Index move together with remarkable consistency. A daily move in one is a reliable predictor of the direction of the other. This tight coupling usually reflects a common driver or a direct mechanical relationship.
Recent vs Long-Run Behavior
Recent correlation tracks the long-run relationship closely. No meaningful divergence. The historical pattern between CPI (All Urban) and PCE Price Index is intact and should continue to serve as a reasonable baseline for positioning.
Statistical Details (1-Year Window)
| Pearson Correlation (r) | +0.922 |
| R-Squared (r²) | 0.850 |
| Beta (CPI (All Urban) vs PCE Price Index) | 1.241 |
| Daily Volatility σ(CPI (All Urban)) | 0.28% |
| Daily Volatility σ(PCE Price Index) | 0.21% |
| Observations | 56 |
Correlation measures directional co-movement; R² quantifies the fraction of variance explained by the linear relationship. Beta is the slope coefficient from regressing CPI (All Urban) returns on PCE Price Index returns. A beta above 1 means the first asset amplifies moves of the second.
Year-by-Year Correlation
| Year | Correlation | Strength | Observations |
|---|---|---|---|
| 2026 | — | Insufficient data | 3 |
| 2025 | +0.697 | Strong positive | 11 |
| 2024 | +0.699 | Strong positive | 12 |
| 2023 | +0.895 | Very strong positive | 12 |
| 2022 | +0.974 | Very strong positive | 12 |
| 2021 | +0.913 | Very strong positive | 6 |
Year-by-year correlation reveals how the relationship has held up across different macro regimes. Sharp year-over-year swings in correlation often mark the transition between stress and calm periods.
Methodology
Correlations are computed on daily log-adjacent returns for CPI (All Urban) and PCE Price Index, aligned on shared trading dates. We use the Pearson product-moment coefficient, which measures the linear relationship between two return series.
Windows are the most recent N observations for 30D, 90D, and 1Y (252 trading days); the 5Y figure uses all aligned data up to 1,260 observations. Beta is the OLS slope from regressing the first series on the second. Data updates daily with a 24-hour revalidation cadence.
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Get daily macro analysis on shifting correlations, regime transitions, and cross-asset signals.
Correlation is not causation and backward-looking statistics can fail when regimes shift. Positions sized on historical correlation assumptions should be stress-tested against scenarios where the relationship breaks. For informational purposes only.