What is FN's forecasted revenue?

Fabrinet is forecasted to generate $5.63B in next-four-quarter revenue, representing +21.4% year-over-year growth.

How accurate is the FN revenue forecast model?

The model has 5.8% training MAPE (Mean Absolute Percentage Error). In a holdout test, it predicted $1.2B versus the actual $1.3B.

Fabrinet FN

Revenue Intelligence Report • 64 quarters of SEC filing data • Updated 2026-10-14 • Data through 2026-06-26

Fabrinet's latest quarterly revenue is $1.3B for the period ending 2026-06-26. The model projects $5.6B across the next four quarters (+21.4% versus the preceding four quarters). The forecast uses SG&A data; model selection and estimation exclude the latest quarter, whose retrospective holdout error is 8.4%. These are statistical associations, not estimates of the causal effect of spending.

Investment Thesis

The GAM forecast is based on reported revenue and SG&A data through 2026-06-26. 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

$5.63B

+21.4% YoY

SG&A Elasticity

1.29x

Training Fit

5.8% MAPE

Retrospective holdout (Q4 FY2026): The model predicted $1.21B vs the actual $1.32B — an error of 8.4%.
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: Fabrinet 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
Q4 FY2026 Period end 2026-06-26	$1.21B	$1.32B	$968.6M–$1.50B	+32.5%	✓ In range
Q1 FY2027 Period end 2026-09-26	$1.28B		$1.01B–$1.63B	+31.0%
Q2 FY2027 Period end 2026-12-26	$1.36B		$1.05B–$1.77B	+20.3%
Q3 FY2027 Period end 2027-03-26	$1.45B		$1.09B–$1.93B	+19.3%
Q4 FY2027 Period end 2027-06-26	$1.54B		$1.12B–$2.11B	+17.0%

Seasonal Factors

Multiplicative seasonal adjustment: These factors capture Fabrinet'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 (Jul–Sep)	1.0176	+1.8%	In line with trend	16
FQ2 (Oct–Dec)	1.0272	+2.7%	In line with trend	16
FQ3 (Jan–Mar)	0.9786	-2.1%	In line with trend	16
FQ4 (Apr–Jun)	1.008	+0.8%	In line with trend	15

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 64 quarters. Its coefficients describe conditional historical associations, not causal returns on spending.
Current SG&A elasticity: 0.0135x
The model-term chart shows relative absolute term magnitudes. Its percentages are not shares of revenue or causal contributions to growth.

Enhanced forecast: The time-varying model (GAM) was selected using training fit, before evaluating the withheld quarter. Its holdout error is -8.4%.

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