What is DLR's forecasted revenue?

Digital Realty Trust, Inc. is forecasted to generate $7.03B in next-four-quarter revenue, representing +10.9% year-over-year growth.

How accurate is the DLR revenue forecast model?

The model has 2.7% training MAPE (Mean Absolute Percentage Error). In a holdout test, it predicted $1.7B versus the actual $1.6B.

Digital Realty Trust, Inc. DLR

Revenue Intelligence Report • 64 quarters of SEC filing data • Updated 2026-10-14 • Data through 2026-03-31

Digital Realty Trust, Inc.'s latest quarterly revenue is $1.6B for the period ending 2026-03-31. The model projects $7.0B across the next four quarters (+10.9% versus the preceding four quarters). The forecast uses G&A data; model selection and estimation exclude the latest quarter, whose retrospective holdout error is 1.2%. These are statistical associations, not estimates of the causal effect of spending.

Investment Thesis

The ARDL forecast is based on reported revenue and G&A data through 2026-03-31. 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

$7.03B

+10.9% YoY

G&A Elasticity

0.66x

Training Fit

2.7% MAPE

Retrospective holdout (Q1 FY2026): The model predicted $1.65B vs the actual $1.64B — an error of 1.2%.
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 G&A (GeneralAndAdministrativeExpense). Spending estimates refer to this expense measure, not separately reported SG&A.

Note: Digital Realty Trust, Inc. 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
Q1 FY2026 Period end 2026-03-31	$1.65B	$1.64B	$1.54B–$1.78B	+17.6%	✓ In range
Q2 FY2026 Period end 2026-06-30	$1.69B		$1.52B–$1.87B	+13.1%
Q3 FY2026 Period end 2026-09-30	$1.73B		$1.52B–$1.96B	+9.5%
Q4 FY2026 Period end 2026-12-31	$1.79B		$1.55B–$2.07B	+9.7%
Q1 FY2027 Period end 2027-03-31	$1.82B		$1.55B–$2.14B	+11.5%

Seasonal Factors

Multiplicative seasonal adjustment: These factors capture Digital Realty Trust, Inc.'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)	0.9854	-1.5%	In line with trend	15
FQ2 (Apr–Jun)	0.9986	-0.1%	In line with trend	15
FQ3 (Jul–Sep)	1.0172	+1.7%	In line with trend	15
FQ4 (Oct–Dec)	0.9845	-1.5%	In line with trend	16

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 G&A elasticity: 0.4367x
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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