CONVEX
Correlation Deep Dive

Core CPI vs Core PCE: Correlation Analysis

Pearson correlation of daily returns for Core CPI (ex Food/Energy) and Core PCE (ex Food/Energy). Rolling windows, yearly breakdown, regression beta, and divergence analysis. Data window spans to (56 aligned observations).

30-Day
+0.379
Weak positive
90-Day
+0.722
Strong positive
1-Year
+0.722
Strong positive
5-Year
+0.722
Strong positive

What the Number Means

At 0.72, Core CPI (ex Food/Energy) and Core PCE (ex Food/Energy) have a strong tendency to move together. Most daily moves align, though divergences are common enough that the relationship should not be treated as deterministic. A shared regime or macro factor is likely driving both.

Recent vs Long-Run Behavior

Last 90 Days
+0.722
5-Year Baseline
+0.722

Recent correlation tracks the long-run relationship closely. No meaningful divergence. The historical pattern between Core CPI (ex Food/Energy) and Core PCE (ex Food/Energy) is intact and should continue to serve as a reasonable baseline for positioning.

Statistical Details (1-Year Window)

Pearson Correlation (r)+0.722
R-Squared (r²)0.522
Beta (Core CPI (ex Food/Energy) vs Core PCE (ex Food/Energy))0.813
Daily Volatility σ(Core CPI (ex Food/Energy))0.15%
Daily Volatility σ(Core PCE (ex Food/Energy))0.13%
Observations56

Correlation measures directional co-movement; R² quantifies the fraction of variance explained by the linear relationship. Beta is the slope coefficient from regressing Core CPI (ex Food/Energy) returns on Core PCE (ex Food/Energy) returns. A beta above 1 means the first asset amplifies moves of the second.

Year-by-Year Correlation

YearCorrelationStrengthObservations
2026Insufficient data3
2025+0.360Weak positive11
2024+0.610Strong positive12
2023+0.770Strong positive12
2022+0.690Strong positive12
2021+0.855Very strong positive6

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 Core CPI (ex Food/Energy) and Core PCE (ex Food/Energy), 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.