What is BAC's forecasted revenue?

Bank of America Corporation is forecasted to generate $114.0B in next-four-quarter revenue, representing -5.9% year-over-year growth.

How accurate is the BAC revenue forecast model?

The model has 7.1% training MAPE (Mean Absolute Percentage Error). In a holdout test, it predicted $29B versus the actual $32B.

Bank of America Corporation BAC

Revenue Intelligence Report • 73 quarters of SEC filing data • Updated 2026-10-14 • Data through 2026-06-30

Bank of America Corporation's latest quarterly revenue is $31.6B for the period ending 2026-06-30. The model projects $114B across the next four quarters (-5.9% versus the preceding four quarters). The forecast uses Operating expense proxy data; model selection and estimation exclude the latest quarter, whose retrospective holdout error is 8.0%. These are statistical associations, not estimates of the causal effect of spending.

Investment Thesis

The ARDL forecast is based on reported revenue and Operating expense proxy data through 2026-06-30. Training MAPE measures fit to historical data; the separately reported holdout error measures a withheld quarter. Spending coefficients describe associations and do not establish causation.

Next 4 Quarters

$114.0B

-5.9% YoY

Operating expense proxy Elasticity

-0.75x

Training Fit

7.1% MAPE

Retrospective holdout (Q2 FY2026): The model predicted $29.04B vs the actual $31.56B — an error of 8.0%.
Retrospective one-quarter holdout: model fitting and selection exclude this quarter. Historical inputs use the latest available restatements, so this is not a preserved real-time forecast.

Note: The current filings use Operating expense proxy (NoninterestExpense). Spending estimates refer to this expense measure, not separately reported SG&A.

⚠ Model limitation: One or more estimated spending associations are negative. These observational coefficients do not establish a causal return on spending.

Note: Bank of America Corporation does not report R&D expenses separately. The model uses the available expense measure without a separate R&D term.

Revenue Forecast

Quarterly Detail

Quarter	Model Forecast	Actual	95% Range	YoY Growth	Status
Q2 FY2026 Period end 2026-06-30	$29.04B	$31.56B	$23.88B–$35.32B	+5.8%	✓ In range
Q3 FY2026 Period end 2026-09-30	$28.88B		$21.89B–$38.09B	+2.8%
Q4 FY2026 Period end 2026-12-31	$28.23B		$20.11B–$39.62B	-9.5%
Q1 FY2027 Period end 2027-03-31	$28.54B		$19.29B–$42.22B	-5.7%
Q2 FY2027 Period end 2027-06-30	$28.32B		$18.28B–$43.88B	-10.3%

Seasonal Factors

Multiplicative seasonal adjustment: These factors capture Bank of America Corporation's systematic quarterly revenue patterns relative to the trend model. A factor of 1.05 means that quarter typically runs 5% above the underlying trend; 0.95 means 5% below. Factors are computed as the median of (actual / fitted) across all available quarters.

Fiscal Quarter	Seasonal Factor	vs Trend	Interpretation	Obs.
FQ1 (Jan–Mar)	1.0238	+2.4%	In line with trend	17
FQ2 (Apr–Jun)	0.9739	-2.6%	In line with trend	17
FQ3 (Jul–Sep)	1.0153	+1.5%	In line with trend	17
FQ4 (Oct–Dec)	1.039	+3.9%	+3.9% above trend	17

Spending and Revenue

Reading this chart: Each line shows the cumulative revenue association with a 1% change in spending over subsequent quarters. These estimates describe historical associations and do not establish causation.

Time-Varying Spending Associations

Time-varying analysis: A penalized spline model (GAM) tracks the association between log spending and log revenue over 73 quarters. Its coefficients describe conditional historical associations, not causal returns on spending.
Current Operating expense proxy elasticity: -0.8427x
The model-term chart shows relative absolute term magnitudes. Its percentages are not shares of revenue or causal contributions to growth.

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