What is TPL's forecasted revenue?

Texas Pacific Land Corporation is forecasted to generate $967.4M in next-four-quarter revenue, representing +7.8% year-over-year growth.

How accurate is the TPL revenue forecast model?

The model has 6.7% training MAPE (Mean Absolute Percentage Error). In a holdout test, it predicted $237M versus the actual $246M.

Texas Pacific Land Corporation TPL

Revenue Intelligence Report • 26 quarters of SEC filing data • Updated 2026-10-14 • Data through 2026-06-30

Texas Pacific Land Corporation's latest quarterly revenue is $246M for the period ending 2026-06-30. The model projects $967M across the next four quarters (+7.8% versus the preceding four quarters). The forecast uses G&A data; model selection and estimation exclude the latest quarter, whose retrospective holdout error is 3.5%. 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 2026-06-30. 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

$967.4M

+7.8% YoY

G&A Elasticity

-0.23x

Training Fit

6.7% MAPE

Retrospective holdout (Q2 FY2026): The model predicted $237.4M vs the actual $246.1M — an error of 3.5%.
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.

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

Note: Texas Pacific Land 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	$237.4M	$246.1M	$201.0M–$280.3M	+26.6%	✓ In range
Q3 FY2026 Period end 2026-09-30	$240.3M		$190.0M–$304.1M	+18.3%
Q4 FY2026 Period end 2026-12-31	$241.7M		$181.2M–$322.4M	+14.2%
Q1 FY2027 Period end 2027-03-31	$240.7M		$172.6M–$335.7M	+1.6%
Q2 FY2027 Period end 2027-06-30	$244.7M		$168.7M–$355.0M	-0.5%

Seasonal Factors

Multiplicative seasonal adjustment: These factors capture Texas Pacific Land 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)	0.9968	-0.3%	In line with trend	6
FQ2 (Apr–Jun)	1.0033	+0.3%	In line with trend	5
FQ3 (Jul–Sep)	1.0316	+3.2%	+3.2% above trend	6
FQ4 (Oct–Dec)	1.0325	+3.2%	+3.2% above trend	6

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 26 quarters. Its coefficients describe conditional historical associations, not causal returns on spending.
Current G&A elasticity: -0.4828x
The model-term chart shows relative absolute term magnitudes. Its percentages are not shares of revenue or causal contributions to growth.

Want this analysis for your portfolio?

I build custom revenue intelligence reports for investors and companies using SEC filing data, econometric modeling, and AI-powered insights.

Get in Touch