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Correlation Deep Dive

Consumer Sentiment vs S&P 500: Correlation Analysis

Pearson correlation of daily returns for Consumer Sentiment (Michigan) and S&P 500 ETF (SPY). Rolling windows, yearly breakdown, regression beta, and divergence analysis. Data window spans to (36 aligned observations).

30-Day
+0.620
Strong positive
90-Day
+0.528
Moderate positive
1-Year
+0.528
Moderate positive
5-Year
+0.528
Moderate positive

What the Number Means

The 0.53 correlation indicates that Consumer Sentiment (Michigan) and S&P 500 ETF (SPY) have a moderate tendency to move together. The relationship is real but noisy, with frequent days where they disagree. Regime context matters: the correlation often strengthens during stress and weakens during calm periods.

Recent vs Long-Run Behavior

Last 90 Days
+0.528
5-Year Baseline
+0.528

Recent correlation tracks the long-run relationship closely. No meaningful divergence. The historical pattern between Consumer Sentiment (Michigan) and S&P 500 ETF (SPY) is intact and should continue to serve as a reasonable baseline for positioning.

Statistical Details (1-Year Window)

Pearson Correlation (r)+0.528
R-Squared (r²)0.279
Beta (Consumer Sentiment (Michigan) vs S&P 500 ETF (SPY))0.999
Daily Volatility σ(Consumer Sentiment (Michigan))9.66%
Daily Volatility σ(S&P 500 ETF (SPY))5.11%
Observations36

Correlation measures directional co-movement; R² quantifies the fraction of variance explained by the linear relationship. Beta is the slope coefficient from regressing Consumer Sentiment (Michigan) returns on S&P 500 ETF (SPY) returns. A beta above 1 means the first asset amplifies moves of the second.

Year-by-Year Correlation

YearCorrelationStrengthObservations
2025+0.693Strong positive6
2024+0.501Moderate positive8
2023+0.690Strong positive8
2022+0.740Strong positive9
2021-0.786Strong negative5

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 Consumer Sentiment (Michigan) and S&P 500 ETF (SPY), 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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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.