This week's screen returned five companies whose EBITDA has compounded faster than revenue over five years: ServiceNow, Comfort Systems USA, Howmet Aerospace, Deckers and Quanta Services. The spread between the two rates runs from 21.89 percentage points down to 1.93, and that range is the useful part. A wide gap and a narrow one are not the same finding, and neither tells you where the margin came from.
The analysis uses FMP's Income Statement API to compare five-year revenue and EBITDA growth across the group. This article works through what produced each spread, and how to build the same CAGR screen without letting a distorted base year manufacture a signal that is not there.
Key Takeaways
- The five spreads range from 21.89 points at ServiceNow to 1.93 at Quanta, where EBITDA margin moved only from 8.2% to 8.9% across the full period.
- Howmet has the slowest revenue growth in the group at 9.43% and the largest margin expansion, which is the cleanest expression of the signal the screen is looking for.
- ServiceNow's most recent quarter shows the mechanism partially reversing, with subscription gross margin down 250 basis points as AI workloads introduce a variable cost the historical record never carried.
- Three of the five are exposed to the same underlying demand source through completely different industries, so the sector spread in this screen is less diversified than it appears.
Five Names Where the Margin Moved Faster Than the Top Line
ServiceNow, Inc. (NOW)
5-Year Revenue CAGR: 24.05%
5-Year EBITDA CAGR: 45.94%
ServiceNow produced the widest spread in the screen, with EBITDA compounding at nearly twice the rate of revenue and EBITDA margin rising from about 10% to roughly 23% across the period. That is the textbook enterprise software pattern: once the platform exists, incremental subscription revenue arrives with very little incremental cost attached, so profit grows faster than sales almost mechanically. Five years of that arithmetic produces exactly the shape this screen is built to find.
The most recent quarter is worth reading closely, because part of that mechanism is now moving the other way. Subscription revenue of $3,877 million grew 24.5%, roughly 150 basis points above guidance, and the customer base continued to deepen: accounts worth more than $5 million in annual contract value rose to 658 from 533, with average contract value climbing to $15.2 million. Current remaining performance obligations reached $13.20 billion, up 21.5% in constant currency. On every demand measure the business is compounding as it has been.
Margin behaved differently. Non-GAAP subscription gross margin fell 250 basis points to 80.5% from 83.0%, which management attributed to greater use of hyperscaler partnerships and accelerating customer AI adoption. That matters more than the 50 basis point decline at the operating line, because it appears above it. AI inference consumes compute that the company rents, which reintroduces a variable cost into a revenue stream that historically had almost none. FMP's Financial Ratios API is the right place to watch this, since the distinction between a gross margin that is compressing and an operating margin absorbing discretionary spend is the difference between a structural change and a spending decision.
Comfort Systems USA, Inc. (FIX)
5-Year Revenue CAGR: 26.08%
5-Year EBITDA CAGR: 41.00%
Comfort Systems has EBITDA margin rising from roughly 9% to 16% over five years, which is an unusual result for a mechanical and electrical contractor. Construction services businesses are typically price takers with limited scope to expand margin, since the work is bid, labour intensive and executed on someone else's site. A spread of nearly 15 points suggests something changed in what the company sells rather than simply how much of it.
The latest quarter identifies both changes. Revenue grew 50% to $3.3 billion, gross margin expanded to 25.9% from 23.5%, and net income nearly doubled to $442 million. Underneath that, technology and hyperscaler customers now account for 58% of revenue against 40% a year earlier, and the electrical segment grew 81% against 40% for mechanical. Modular bookings reached a record $510 million, with total backlog of $14.1 billion up 73%. Modular is the more important detail: prefabricating in a factory rather than assembling on a job site moves the work into a controlled environment where productivity, and therefore margin, is a manufacturing variable rather than a field one. Capacity is being expanded from 3.5 million square feet toward 5 million by late summer 2027, backed by customer volume commitments.
One figure deserves care. Free cash flow of $999 million was driven substantially by advanced customer payments, which is a working capital timing benefit rather than earnings converted to cash. It leaves the company with net cash above $1.8 billion, which is genuinely useful for funding the capacity build and bolt-on acquisitions, but it is not a run rate. FMP's Cash Flow Statement API is where that distinction resolves over the next few quarters, because the question is whether operating cash flow keeps pace with EBITDA once the advance payments cycle through.
Howmet Aerospace Inc. (HWM)
5-Year Revenue CAGR: 9.43%
5-Year EBITDA CAGR: 22.30%
Howmet has the slowest revenue growth in this group and the largest margin expansion, moving from roughly 16% EBITDA margin to nearly 28%. That combination is the purest version of what the screen is designed to detect. Where a fast-growing company can widen the spread simply by holding fixed costs steady, Howmet more than doubled its earnings margin on revenue growing at single digits, which means the improvement came from price, mix and productivity rather than from scale absorbing overhead.
The current quarter shows both the level and the direction. Revenue rose 24% with organic growth of 21%, and adjusted EBITDA margin expanded 340 basis points to 32.1%. Engine Products, the core division, grew 32% with segment EBITDA margin up 470 basis points to 37.7%, achieved while adding roughly 500 employees, so the margin gain was not a headcount reduction. Management raised full-year targets to $10.05 billion of revenue and $3.23 billion of EBITDA, and supported the balance sheet at the same time with $479 million of quarterly free cash flow, $500 million of repurchases, a 17% dividend increase and a $1.8 billion acquisition.
The composition is what makes this interesting beyond aerospace. Gas turbine revenue grew 38%, with management describing demand as extraordinary and citing data centre customers requiring generation capacity, in a product line where the company holds more than half the global market. Commercial aerospace grew 37% alongside it. So a supplier of engineered castings is now capturing pricing from a demand source that has nothing to do with aviation, and capacity expansions are planned into the 2028 to 2030 window. FMP's Revenue Product Segmentation API is the dataset that keeps these separable, since a consolidated line will blend an aerospace recovery with an industrial power cycle that could turn independently.
Deckers Outdoor Corporation (DECK)
5-Year Revenue CAGR: 16.54%
5-Year EBITDA CAGR: 20.71%
Deckers clears the screen with a spread of just over four points, EBITDA margin having moved from roughly 22% to 26%. The measurement window runs across fiscal years ending in March, so this is the fiscal 2021 to fiscal 2026 period rather than calendar 2020 to 2025, which is worth noting when comparing it against the others in the group. Within that window the source of the improvement is different from anything else here: this is pricing power on a brand, not operating leverage on a cost base.
The most recent quarter makes the mechanism visible. Revenue of $1.02 billion crossed $1 billion for the first time, but grew only 5.7%, well below the five-year compound rate. Gross margin expanded to 56.4% from 55.8%, with management attributing 110 basis points to full-price selling and 60 basis points to closeout management that the finance chief described as unique to the quarter. HOKA at $704 million now represents 68% of company revenue, with direct-to-consumer growing 17% against 3% at wholesale, and UGG grew 5% to $278 million while extending its men's business and its year-round assortment.
Two things temper the read. Revenue growth has decelerated to roughly a third of the historical compound rate, which means the denominator in this spread is no longer expanding the way it did across the measurement period. And margin faces an identified headwind: tariff duties cost 150 basis points in the quarter, the assumed go-forward rate was raised to 12.5%, and management expects the following quarter's margin to decline year over year on tariffs and freight. Full-year earnings guidance still moved up. FMP's Income Statement Growth API is the useful reference here, because it shows period-over-period changes rather than an endpoint-to-endpoint rate, and the recent trajectory is doing something different from the five-year average.
Quanta Services, Inc. (PWR)
5-Year Revenue CAGR: 20.41%
5-Year EBITDA CAGR: 22.34%
Quanta is the edge case in this screen, and it is included deliberately. The spread of 1.93 points reflects EBITDA margin moving from about 8.2% to 8.9% across five years, which is 70 basis points on a business whose revenue more than doubled. The screen's criterion is met, but almost nothing about the margin structure changed. This is what the floor of the signal looks like, and it is a useful calibration against ServiceNow's 21.89 points at the other end.
The business itself is performing strongly by every other measure. Second-quarter revenue reached $9.6 billion, up 42%, with adjusted earnings per share of $4.24 and a record backlog of $53 billion. Management raised full-year guidance to $39.3 billion to $39.7 billion of revenue and $4.1 billion to $4.2 billion of adjusted EBITDA, with free cash flow conversion tracking at the high end of the 55% to 60% target. The electric segment reported margin improvement approaching 10%, and technology and data centre work now represents 15% to 20% of revenue. More than 7,000 employees were added in the first half.
That last figure explains the narrow spread. This is a labour-intensive, self-perform model covering 80% to 85% of the work, so growth requires hiring in proportion, and margin does not expand the way it does in a business where the incremental unit is cheap to produce. Four acquisitions completed during the period, expected to contribute $1.2 billion to $1.4 billion of annual revenue, also mean some of the revenue growth was purchased rather than generated, which further dilutes any read of organic operating leverage. FMP's Balance Sheet Statement API is worth pairing with the income statement here, since goodwill and intangible additions indicate how much of the five-year revenue expansion came from acquisition rather than from the existing base.
Where the Leverage Actually Came From
The spread between EBITDA and revenue growth identifies that margin changed. It says nothing about why, and across these five the why has almost no overlap. ServiceNow's gap is software incremental margin, the cheapest form of leverage and the one currently under pressure as AI inference introduces a variable cost. Comfort Systems earned its margin by changing what it sells and where the work happens, moving from field assembly toward factory prefabrication for a customer base that shifted from 40% to 58% hyperscaler. Howmet's came from pricing and mix on a constrained supply base, which is why the slowest revenue growth in the group produced the largest margin move. Deckers earned its through brand pricing rather than scale. Quanta effectively did not earn one at all: it grew, and the margin came along for the ride.
The methodology carries a specific hazard worth naming, because a five-year window measured today begins in 2020. Any company whose base year was depressed will show a wide spread that reflects a recovery rather than a structural improvement. The check is cheap: look at the starting margin before looking at the growth rate, and treat any base below a normal operating level as a disqualification rather than a discovery.
The second observation is about the screen's apparent diversification. On sector labels this group spans enterprise software, building services, aerospace components, footwear and infrastructure construction. On demand, Comfort Systems, Quanta and Howmet are all levered to data centre buildout and the electricity generation it requires, arriving at it from mechanical contracting, grid construction and industrial gas turbines respectively. A screen that surfaces three exposures to the same capital cycle through three different industry classifications is producing correlation the sector tags conceal, which is exactly the kind of thing worth catching before the group is treated as five independent findings.
Testing whether any of this converts is the next step, and it is answerable from reported data. Pairing the Income Statement Bulk API with the Cash Flow Statement API establishes whether EBITDA growth is reaching operating and free cash flow or being absorbed by working capital and capital expenditure, which is the specific check Comfort Systems' advance-payment-driven cash flow requires. Key Metrics TTM then normalises returns and leverage across business models with nothing structurally in common. Within the broader financial and market datasets available through the FMP platform, those pulls resolve against the same reporting periods as the CAGR calculation itself, which is what keeps the comparison honest as the universe widens. The Price Target Summary API and Financial Estimates API close the loop by showing whether the margin improvement is already embedded in published expectations, since a real operating inflection that consensus has fully absorbed is a different proposition from one it has not.
Building a Consistent CAGR Screening Framework
Building a useful CAGR screen is less about the formula itself and more about maintaining discipline in the underlying dataset. The calculation is straightforward; what determines whether the result is meaningful is data consistency. Every company needs to be evaluated using the same reporting periods, identical financial line items, and the same time horizon. Once those inputs are standardized, growth rates become comparable across industries, capital structures, and business models. The workflow below shows how to structure that process using FMP's Income Statement data — starting with a single company and then scaling the exact same logic across a broader universe.
Step 1: Pull Income Statement Data
Begin with a single symbol to establish the baseline. Query the standard Income Statement API to retrieve the full set of historical reporting periods needed for the calculation.
As long as your API key is active, one request gives you the raw time series you'll be working with. For example:
Endpoint:
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https://financialmodelingprep.com/stable/income-statement?symbol=AAPL&apikey=YOUR_API_KEY |
Step 2: Gather Historical Figures
From the JSON output, select the specific metric you want to analyze — revenue, EBITDA, EPS, or another line item. Arrange the values in proper chronological order before doing any math. This step is easy to overlook, but it's critical: CAGR only makes sense when the starting and ending points are clearly defined and consistently ordered.
Step 3: Calculate CAGR
Once the first and last data points are set, calculate CAGR using the standard formula:
CAGR = (Ending Value / Beginning Value)^(1 / Years) - 1
This reduces several years of performance into a single annualized figure, making it easier to compare growth profiles across companies without getting lost in interim volatility.
Step 4: Scale Screening with Bulk API
After validating the method on one symbol, broaden the workflow using the Income Statement Bulk API:
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https://financialmodelingprep.com/stable/income-statement-bulk?year=2025&period=FY&apikey=YOUR_API_KEY |
Running the same calculation at scale lets you build filters — for instance, highlighting companies that clear a five-year revenue CAGR threshold — while ensuring every ticker is processed under the same ruleset. Once the bulk pull is in place, updating or rerunning the screen is effectively a single action.
Scaling the Framework Without Changing the Methodology
The strength of this type of screen comes from consistency, not complexity. Once the formula, reporting periods, and financial line items are defined, the objective is to keep the methodology fixed while gradually widening the universe being tested. Expanding coverage should not require changing the framework itself — only the number of companies moving through it.
That's why the workflow is easiest to validate in a smaller environment first. Within the Basic plan, the Income Statement endpoints provide enough historical coverage to align reporting periods properly, normalize the selected metrics, and verify that the CAGR calculations are producing comparable outputs across companies. At this stage, the emphasis is less about scale and more about making sure inconsistencies in filings or missing data are not distorting the screen.
From there, expanding into the Starter plan simply broadens the sample size. The screening logic remains identical, but the larger universe makes sector-level comparisons more useful. Patterns that initially appear company-specific can then be evaluated against peers, industries, or market-cap cohorts to determine whether the operating leverage signal is isolated or part of a broader trend developing within a segment of the market.
The Premium plan extends that same structure further by increasing historical depth and geographic coverage. The underlying process still does not change. What changes is the scope of observation — allowing the same framework to be applied across wider datasets without introducing new assumptions or altering the screening criteria midstream. That continuity is what makes the process repeatable over time rather than dependent on one-off observations or isolated market conditions.
Reading the Spread Rather Than Ranking It
What these five show is that the same arithmetic result can describe a business that fundamentally re-rated its margin structure and one that simply got larger, and the ordering by spread is a reasonable place to start looking rather than a ranking of quality. Running the Income Statement API and Income Statement Bulk API on a fixed set of periods keeps the comparison stable from quarter to quarter, which is what makes it possible to see a margin structure changing rather than a base year flattering it.
If you found this useful, you might also like: Weekly Signals Desk | Five Dividend Increases Flagged by the FMP API (July 27-31)
Disclosure: Signals Desk content is provided for informational and analytical purposes only and does not constitute investment advice or trade recommendations. The analysis reflects interpretation of market data and publicly disclosed or third-party information, including data accessed via Financial Modeling Prep APIs, at the time of publication. Signals discussed are probabilistic, can be wrong, and may change as market conditions and consensus data evolve. This content should be considered alongside broader research, individual objectives, and risk assessment.
