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Prime Rate

Linear model of Prime Rate at period t from the other tracked series and the LN_ / squared transforms described on the Regression Models index: Y(t) = Σ ai Xi(t−6).

Integrated series (S&P 500, Dow, Home Price Index, Commercial RE) are fit as ΔY. Quarterly series use one row per quarter.

Terms are added one at a time to minimize training AIC, at most min(5, n/8) predictors, one transform per driver, and only when the term’s p-value is at most 0.1 and |coefficient| is greater than 1.0e-10. A candidate correlated above 0.8 with Y or with an already selected X is skipped.

LN_ and squared predictors are clamped to their training range. Coefficients smaller than 0.001 are shown in scientific notation.

Each section is one quarter in a one-year walk (4 experiments). The newest label is the current quarter (3Q2026). The test window is the prior 6 quarters of Y; the train window is the five years (20 quarters) before that. Independents are two quarters (six months) older than Y. Dates on this page are quarter-end observations.

Charts start in January 2020 and plot published prints only (not carried-forward extra samples). Fitted (train), fitted (test), and forecast are joined at the window boundaries so the line is continuous through the label quarter. The OLS test/forecast is shown when its test MAE beats or matches a last-print (or zero-change) baseline.

An intercept-only heading (for example “Δ SP500 = 40.657”) means no lagged series improved training AIC by at least 2 after the intercept, so the model is the training-mean change (a random walk with drift).

Test MAE is omitted when every print in the test window is a CCAR extra sample rather than a published observation.

3Q2026: Prime Rate = -5.698 + 11.232 × LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations) − 0.061 × CPI Inflation Rate²

Train: 1Q2020 – 4Q2024 (20 observations). Test: 1Q2025 – 2Q2026 (6 observations). Independents are dated two quarters (six months) before each Y period.

Regression for Prime Rate
Dependent variable (+/- SE):
Prime Rate
Constant-5.698 (+/- 1.360)
p = 0.001***
LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations)11.232 (+/- 1.275)
p = 0.00000***
CPI Inflation Rate2-0.061 (+/- 0.010)
p = 0.00002***
Observations20
R20.823
Adjusted R20.803
Residual Std. Error1.045 (df = 17)
F Statistic39.607*** (df = 2; 17)
Note:*p<0.1; **p<0.05; ***p<0.01

Test period (1Q2025 – 2Q2026)

MAE0.562
Last-print MAE0.167
RMSE0.624
R2-2.718

Chart forecast uses the last-print baseline (OLS MAE is worse).

R2 impact

Train ΔR2 is the gain when the term was added. Test ΔR2 is the drop if that term is omitted from the frozen coefficients and the reduced model is scored on the test window.

Variable Train ΔR2 Test ΔR2
LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations) +0.4425 +1697.8101
CPI Inflation Rate² +0.3808 -1.4389

2Q2026: Prime Rate = -5.858 + 11.374 × LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations) − 0.061 × CPI Inflation Rate²

Train: 4Q2019 – 3Q2024 (20 observations). Test: 4Q2024 – 1Q2026 (6 observations). Independents are dated two quarters (six months) before each Y period.

Regression for Prime Rate
Dependent variable (+/- SE):
Prime Rate
Constant-5.858 (+/- 1.384)
p = 0.001***
LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations)11.374 (+/- 1.325)
p = 0.00000***
CPI Inflation Rate2-0.061 (+/- 0.010)
p = 0.00002***
Observations20
R20.814
Adjusted R20.792
Residual Std. Error1.049 (df = 17)
F Statistic37.213*** (df = 2; 17)
Note:*p<0.1; **p<0.05; ***p<0.01

Test period (4Q2024 – 1Q2026)

MAE0.535
Last-print MAE0.267
RMSE0.603
R2-2.140

Chart forecast uses the last-print baseline (OLS MAE is worse).

R2 impact

Train ΔR2 is the gain when the term was added. Test ΔR2 is the drop if that term is omitted from the frozen coefficients and the reduced model is scored on the test window.

Variable Train ΔR2 Test ΔR2
LN_US Avg Retail Gasoline Price ($-gal; all grades, all formulations) +0.4375 +1612.3179
CPI Inflation Rate² +0.3765 -0.0327

1Q2026: Prime Rate = -3.156 + 0.672 × LN_1-month Treasury Yield + 0.034 × Home Price Index

Train: 3Q2019 – 2Q2024 (20 observations). Test: 3Q2024 – 4Q2025 (6 observations). Independents are dated two quarters (six months) before each Y period.

Regression for Prime Rate
Dependent variable (+/- SE):
Prime Rate
Constant-3.156 (+/- 0.793)
p = 0.001***
LN_1-month Treasury Yield0.672 (+/- 0.057)
p = 0.000***
Home Price Index0.034 (+/- 0.003)
p = 0.000***
Observations20
R20.959
Adjusted R20.954
Residual Std. Error0.472 (df = 17)
F Statistic197.492*** (df = 2; 17)
Note:*p<0.1; **p<0.05; ***p<0.01

Test period (3Q2024 – 4Q2025)

MAE1.247
Last-print MAE0.25
RMSE1.328
R2-8.908

Chart forecast uses the last-print baseline (OLS MAE is worse).

R2 impact

Train ΔR2 is the gain when the term was added. Test ΔR2 is the drop if that term is omitted from the frozen coefficients and the reduced model is scored on the test window.

Variable Train ΔR2 Test ΔR2
LN_1-month Treasury Yield +0.6395 -8.2016
Home Price Index +0.3192 +520.9344

4Q2025: Prime Rate = 1.424 + 0.763 × LN_US Fed Reserve O-N Loan Rate + 6.237e-5 × Home Price Index²

Train: 2Q2019 – 1Q2024 (20 observations). Test: 2Q2024 – 3Q2025 (6 observations). Independents are dated two quarters (six months) before each Y period.

Regression for Prime Rate
Dependent variable (+/- SE):
Prime Rate
Constant1.424 (+/- 0.473)
p = 0.008***
LN_US Fed Reserve O-N Loan Rate0.763 (+/- 0.076)
p = 0.000***
Home Price Index20.0001 (+/- 0.00001)
p = 0.00000***
Observations20
R20.936
Adjusted R20.928
Residual Std. Error0.554 (df = 17)
F Statistic123.980*** (df = 2; 17)
Note:*p<0.1; **p<0.05; ***p<0.01

Test period (2Q2024 – 3Q2025)

MAE0.682
Last-print MAE0.167
RMSE0.782
R2-2.359

Chart forecast uses the last-print baseline (OLS MAE is worse).

R2 impact

Train ΔR2 is the gain when the term was added. Test ΔR2 is the drop if that term is omitted from the frozen coefficients and the reduced model is scored on the test window.

Variable Train ΔR2 Test ΔR2
LN_US Fed Reserve O-N Loan Rate +0.6192 -0.7536
Home Price Index² +0.3167 +146.9599