Signals Desk Weekly | Multi-Year CAGR Strength Taking Shape Across Five Names (Aug 17-21)

This week's screen surfaced five companies where EBITDA compounded faster than revenue across the five years to fiscal 2025: Fortinet, DexCom, Wabtec, Williams-Sonoma and Manhattan Associates. The spreads run from roughly six to eleven percentage points, and each one traces to a different mechanism: a subscription mix shift, a manufacturing cost curve, an acquired-margin overlay, a supply-chain and full-price discipline, and a cloud transition past its trough. The more useful observation is that a five-year CAGR is a rear-view measure, and in three of these five the most recent reported quarter points somewhere other than where the trailing spread does.

The analysis uses FMP's Income Statement API to compare multi-year revenue and EBITDA growth across the group. This article works through the five names, identifies what produced the margin in each case, and then tests each trailing spread against the direction of travel in the latest disclosure.

Key Takeaways

• All five cleared the screen on the five years to fiscal 2025, but Williams-Sonoma has since posted its first operating-margin contraction of the cycle and Fortinet's mix shift has temporarily inverted, so the trailing figure and the current trend disagree.
• Manhattan Associates is the cleanest continuation, with cloud revenue up 26% and remaining performance obligations up 23% against total revenue growth of 9.3%.
• DexCom's expansion is the most mechanically explainable of the five, resting on a longer-wear sensor that cuts cost of goods per day at broadly unchanged revenue per day.
• Wabtec's spread carries an acquired-margin component alongside its productivity programme, which is a different quality of leverage from organic operating gearing.

Five Names Where Profit Outran Sales

Fortinet, Inc. (FTNT)

5-Year Revenue CAGR: 21.26%
5-Year EBITDA CAGR: 32.18%

Fortinet has the widest spread in the group at roughly eleven percentage points, taking EBITDA margin from about 23.6% to 36.2% over the period. The mechanism is well documented and structural: the company moved the weight of its revenue from appliance sales toward recurring service, which now represents roughly 62% of the total, and layered secure access and security operations subscriptions onto an installed firewall base it had already sold. Recurring revenue lands on a largely fixed platform cost, which is what produces the gearing.

The most recent quarter is where the reading gets more interesting, because that mix shift has temporarily reversed. Second-quarter revenue grew 26%, but product revenue rose 52% against service revenue up 14%, meaning the current margin gain is coming from volume leverage rather than from mix. Non-GAAP operating margin still reached a second-quarter record near 38%, up close to 490 basis points, with free cash flow margin above 47% and guidance raised across revenue, billings, margin and earnings. Management attributes the product strength to unit growth plus higher average selling prices as customers move to higher-performance hardware, framing it as capacity preparation rather than a pull-forward, and points separately to AI-assisted support automation and deliberately slowed hiring as the levers now doing the work.

That distinction matters for how the five-year figure should be read forward. A margin built on mix shift is self-reinforcing while the shift continues; a margin built on hardware volume leverage is cyclical, and hardware cycles turn. FMP's Revenue Product Segmentation API is the direct instrument here, because it separates product from service revenue over time, which is the only way to see whether this quarter is a pause in the transition or the start of a reweighting. Secure access billings more than doubled year over year, though no subscription revenue figure for that business was disclosed, so the transition's own progress is partly inferred rather than reported.

DexCom, Inc. (DXCM)

5-Year Revenue CAGR: 19.33%
5-Year EBITDA CAGR: 29.23%

DexCom turned revenue growth of roughly 19% a year into EBITDA growth near 29%, lifting margin from about 19.6% to 29.2%. What makes this the most legible case on the screen is that the driver is close to arithmetic. The fifteen-day version of its G7 sensor roughly halves the number of sensor replacements a patient consumes in a year, which cuts cost of goods per day of wear while revenue per day of wear is broadly unchanged. Layer that onto manufacturing scale and the margin moves without requiring any pricing action at all.

The trend is continuing rather than flattening. Second-quarter revenue grew 13.1%, adjusted gross margin improved 400 basis points to 64.1%, and adjusted operating margin expanded 590 basis points to 25.1%, with the shares up sharply on the print and guidance raised on revenue, gross margin, operating margin and EBITDA margin. The company has stated a target of converting around half its US installed base to the longer-wear sensor by the end of this year, which sets a measurable checkpoint rather than an aspiration.

Geography is the second lever and it is currently the faster one. International revenue grew 19% against 11% in the US, helped by reimbursement expansion in additional markets, and a July authorisation in Canada extended the longer-wear sensor beyond the US for the first time. Alongside that, a paediatric over-the-counter clearance in June and a launch aimed at basal-insulin and non-insulin type 2 users in Germany widen the addressable base into cohorts with different usage economics. FMP's Revenue Geographic Segments API is the natural companion, because the margin question is increasingly about which geographies the incremental volume arrives in and what the reimbursement rate is there. Competitive activity in dual-analyte and implantable sensing is the variable the data suggests monitoring alongside the conversion rate.

Westinghouse Air Brake Technologies Corporation (WAB)

5-Year Revenue CAGR: 8.13%
5-Year EBITDA CAGR: 15.23%

Wabtec produced the smoothest series in the whole screen: revenue and EBITDA both rose in every one of the six years, taking margin from about 15.1% to 20.8% on revenue growth of only 8.1% a year. That combination of consistency and gearing is unusual in a capital-goods business exposed to locomotive order cycles, and it reflects a multi-year internal productivity programme running alongside manufacturing scale.

The most recent quarter extends it. Revenue grew 17.5%, GAAP operating margin improved 150 basis points to 18.9%, adjusted operating margin 80 basis points to 21.9%, and cash from operations more than doubled. Guidance was raised on both revenue and earnings. The forward book is the more striking disclosure: multi-year backlog reached $30.93 billion against $21.83 billion a year earlier, up nearly 42%, with the twelve-month component up 11.3%. Order flow behind that includes a roughly $1 billion Australian locomotive, services and digital contract and a Brazilian positive train control award.

The qualification worth stating plainly is that part of this leverage was purchased rather than generated. Digital Intelligence revenue rose 88.5% primarily on two acquired inspection and sensing businesses, and the transit segment's 18.9% growth and 250 basis point margin gain owe much to a coupler business acquired in February. Buying higher-margin revenue expands consolidated margin, but it is a different economic event from operating gearing on an existing asset base, and the two should not be read as the same signal. FMP's Latest Mergers and Acquisitions API is what keeps that boundary visible across a multi-year CAGR, since without it acquired margin and organic margin arrive in the same line.

Williams-Sonoma, Inc. (WSM)

5-Year Revenue CAGR: 2.85%
5-Year EBITDA CAGR: 8.91%

Williams-Sonoma is the purest margin story on the screen and the one where the trend has most clearly turned. Revenue compounded at under 3% a year while EBITDA compounded at 8.9%, lifting margin from roughly 16.2% to 21.6%. Almost none of that came from selling more. It came from declining to discount, from supply-chain scale across a delivery network running several thousand in-home deliveries a day that gave the company real leverage on ocean freight, from lower shrink, and from occupancy leverage on a shrinking store base.

The most recent reported quarter interrupted that sequence. In the quarter ended in early May, revenue grew 4.4% and comparable brand revenue 4.8%, with West Elm up 8.5%, but gross margin fell 30 basis points as merchandise margin gave up a full point to tariffs, and operating margin contracted 60 basis points to 16.2%. Full-year guidance was reiterated rather than raised. That is the first operating-margin contraction of this cycle, and its cause is external rather than executional: roughly $60 million of incremental tariff cost sits in inventory, and the guidance assumes current rates persist with no refunds.

Two things are worth holding onto. First, management has been explicit that it is not underwriting a housing recovery and attributes growth to brand execution, which means the demand side of the model carries no cyclical assumption to disappoint. Second, the next quarter reports on 26 August, days after this screen runs, making the trailing spread unusually close to being restated. FMP's Financial Ratios API is the appropriate check, because the question is narrow and quantitative: whether merchandise margin, gross margin and the SG&A ratio resume their prior direction once the front-loaded tariff cost works through, or whether a five-year run of margin expansion has met a cost it cannot absorb.

Manhattan Associates, Inc. (MANH)

5-Year Revenue CAGR: 13.03%
5-Year EBITDA CAGR: 18.88%

Manhattan Associates has the narrowest spread in the group at just under six percentage points, and the most convincing continuation. Margin moved from about 21.0% to 27.0% on revenue growth of 13% a year, and both series rose monotonically across the period. The driver is the perpetual-licence to cloud-subscription transition: subscription revenue is recognised ratably and accumulates in remaining performance obligations while legacy maintenance runs off, and past the trough of that transition each incremental cloud dollar lands on a largely fixed research and platform cost base.

The latest quarter shows the transition still doing the work rather than having finished it. Total revenue grew 9.3%, but cloud subscription revenue grew 26.2% and remaining performance obligations reached $2.47 billion, up 23%, while maintenance declined 12.9%. That is the signature of a mix shift mid-flight: the reported top line understates the growth of the recurring base because the declining line is still large enough to drag it. Adjusted operating margin ran around 35%, guidance was raised across revenue, cloud revenue and earnings, and the shares moved sharply higher on the print.

The analytical value here is that the forward indicator and the trailing indicator agree, which is not true of Fortinet or Williams-Sonoma. A backlog growing at more than twice the rate of reported revenue is a fairly direct statement about the next several years of the same spread, subject to conversion. Product activity supports the same reading, with an explainable-AI decision layer added to the planning suite in May and an agent workforce reaching general availability earlier in the year, both of which are being sold into the recurring base rather than as separate licences. FMP's Financial Statement Growth API is the right tool for a business mid-transition, because it exposes the growth rate of each line item separately and prevents a declining legacy component from being mistaken for a slowing business.

Where the Extra Margin Actually Came From

Five companies, and five genuinely different sources of the same arithmetic result. Fortinet shifted its revenue mix. DexCom changed its cost per unit of delivered service. Wabtec ran a productivity programme and bought higher-margin revenue on top of it. Williams-Sonoma held price and squeezed its supply chain. Manhattan Associates passed the trough of a recognition change. Only two of those are operating leverage in the textbook sense of fixed costs spread over more volume. The others are a unit-cost improvement, a portfolio effect and a pricing discipline, and they carry different durability.

That is why the direction of travel matters more than the size of the spread. Manhattan Associates and DexCom have current disclosures pointing the same way as their five-year figures, one through backlog growing at more than twice reported revenue and the other through simultaneous gross and operating margin expansion with guidance raised on both. Wabtec is continuing but with a purchased component that needs separating. Fortinet's driver has temporarily swapped from mix to volume. Williams-Sonoma has actually reversed. Ranked by trailing spread the order is Fortinet, DexCom, Wabtec, Williams-Sonoma, Manhattan Associates. Ranked by whether the mechanism is still operating, it comes close to inverting.

Testing that requires looking past the income statement the screen is built on. Within the broader financial and market datasets available through the FMP platform, FMP's Key Metrics API supplies returns on capital and free cash flow conversion, which is what distinguishes margin that reaches cash from margin that stops at the operating line: relevant for Wabtec, where acquired intangibles sit between the two, and for Williams-Sonoma, where tariff cost is currently parked in inventory rather than in the profit and loss account. The Enterprise Values API then adds the capital base, which matters because a margin gain purchased with acquisition capital and one generated on an existing asset base look identical in a CAGR and nothing alike in a return.

Two more inputs close the loop on expectations and attribution. FMP's Financial Estimates API shows whether forward revenue and EPS assumptions have absorbed a change in direction or are still tracking the trailing trend, which is the specific open question at Williams-Sonoma with a report days away. And the Earnings Call Transcript API is where management's own account of the margin lives, including the parts that never reach a release: Fortinet's framing of hardware demand as capacity preparation, Wabtec's expectation that margin expansion accelerates as tariff pressure eases. Read together, the spread stops being a ranking of quality and becomes a dated question about mechanism, which is the only form in which it is actually useful.

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:

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:

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.

Watching the Spread as New Years Roll In

A CAGR spread describes what already happened, and three of these five have since started writing a different sentence. Re-running the Income Statement API and Income Statement Bulk API as each new fiscal year enters the window is what turns the screen from a snapshot of past leverage into a record of when the mechanism behind it changed.

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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.