Food CPI vs Energy CPI: Correlation Analysis
Pearson correlation of daily returns for CPI: Food and CPI: Energy. Rolling windows, yearly breakdown, regression beta, and divergence analysis. Data window spans to (56 aligned observations).
What the Number Means
With a correlation of 0.16, CPI: Food and CPI: Energy are essentially uncorrelated at daily frequency. Either the relationship operates at a different time horizon or the shared driver has been dominated by idiosyncratic noise during the observation window.
Recent vs Long-Run Behavior
Recent correlation tracks the long-run relationship closely. No meaningful divergence. The historical pattern between CPI: Food and CPI: Energy is intact and should continue to serve as a reasonable baseline for positioning.
Statistical Details (1-Year Window)
| Pearson Correlation (r) | +0.163 |
| R-Squared (r²) | 0.027 |
| Beta (CPI: Food vs CPI: Energy) | 0.017 |
| Daily Volatility σ(CPI: Food) | 0.31% |
| Daily Volatility σ(CPI: Energy) | 2.91% |
| 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: Food returns on CPI: Energy 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 | +0.014 | Essentially uncorrelated | 11 |
| 2024 | -0.259 | Weak negative | 12 |
| 2023 | +0.183 | Essentially uncorrelated | 12 |
| 2022 | +0.324 | Weak positive | 12 |
| 2021 | +0.653 | 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: Food and CPI: 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.