Operating leverage is starting to show up in places the market may not be fully pricing yet. This week's screen surfaced five companies where EBITDA growth materially outpaced revenue growth over the past five years: a pattern that often signals improving efficiency, stronger margin capture, or a business model moving through a more profitable phase of its cycle.
Using FMP's Income Statement API, we screened for companies where EBITDA CAGR significantly exceeded revenue CAGR over the same period. In this article, we break down the five names that stood out, examine what the divergence may be signaling beneath the surface, and walk through how the same framework can be built and scaled using FMP's Income Statement data.
Key Takeaways
- Five companies from five very different industries showed the same underlying pattern: EBITDA grew materially faster than revenue over a five-year period, highlighting improving operating efficiency rather than simple top-line expansion.
- Exelixis, IDEXX Laboratories, Parker-Hannifin, DRDGOLD, and CME Group each arrived at this outcome through different business drivers, demonstrating that profitability inflections can emerge across diverse sectors and market environments.
- Revenue growth alone often misses important changes occurring within a business. Comparing long-term EBITDA and revenue CAGR can help identify companies where operating leverage, pricing power, cost discipline, or business mix improvements are contributing to stronger financial performance.
- Using FMP's Income Statement API and Income Statement Bulk API, the same screening framework can be applied consistently across a broad universe of companies, allowing profitability trends to be evaluated systematically rather than through isolated company analysis.
Five Companies Showing a Clear Profitability Inflection
Exelixis, Inc. (EXEL)
5-Year Revenue CAGR: 18.72%
5-Year EBITDA CAGR: 121.06%
Exelixis produced the widest spread in this screen by a considerable margin. Revenue expanded at an already notable 18.72% annualized rate over the past five years, but EBITDA compounded at 121.06%, indicating that profitability accelerated far faster than top-line growth. When EBITDA growth outpaces revenue by this magnitude, the signal is often less about demand alone and more about operating leverage, product mix, commercialization efficiency, and the maturation of a company's revenue base.
In Exelixis' case, the pattern coincides with the continued expansion of its oncology franchise and the increasing contribution of higher-margin revenue streams. Recent company updates showed continued growth in product revenues and ongoing advancement of its oncology pipeline, while management also raised portions of its 2025 financial guidance earlier in the year. The key observation is not simply that revenue increased, but that incremental revenue appears to have translated into profitability at a much faster rate than during earlier stages of the company's development.
For readers evaluating whether this trend remains intact, the most relevant datasets extend beyond revenue alone. Historical income statement data helps quantify margin expansion, while product-level revenue trends, operating expense trajectories, and pipeline development milestones provide context for whether the profitability improvement reflects durable operating changes or temporary business factors.
IDEXX Laboratories, Inc. (IDXX)
5-Year Revenue CAGR: 10.02%
5-Year EBITDA CAGR: 14.61%
IDEXX presents a different type of profitability signal. The gap between revenue growth and EBITDA growth is not dramatic, but it is consistent. Revenue compounded at 10.02% annually while EBITDA grew at 14.61%, suggesting that management converted a steadily expanding business into an even faster-growing earnings engine. In mature healthcare and diagnostics businesses, this type of spread often reflects pricing power, recurring revenue characteristics, and disciplined operating execution rather than a single catalyst.
That distinction matters because IDEXX operates within a business model heavily tied to recurring diagnostic testing volumes and software usage. Recent results highlighted continued growth in companion animal diagnostics and recurring revenue streams despite periodic concerns surrounding veterinary visit trends. The company's ability to continue expanding profitability while navigating fluctuations in clinic traffic illustrates why margin trends can sometimes reveal more than revenue growth alone.
The next layer of analysis would be less about headline sales growth and more about utilization metrics. Income statement trends explain the EBITDA acceleration, but segment-level diagnostics data, recurring revenue growth, instrument placements, and analyst estimate revisions help determine whether operating efficiency is continuing to strengthen across the business.
Parker-Hannifin Corporation (PH)
5-Year Revenue CAGR: 8.29%
5-Year EBITDA CAGR: 16.20%
Industrial companies rarely appear near the top of profitability screens unless something meaningful has changed beneath the surface. Parker-Hannifin's revenue CAGR of 8.29% is respectable for a diversified industrial manufacturer, but EBITDA expanding at nearly double that rate points toward a business generating increasing returns from its existing revenue base.
This type of divergence often emerges when management initiatives begin showing up consistently in financial statements. Over long periods, industrial firms can improve profitability through portfolio optimization, operational efficiency programs, pricing discipline, and greater exposure to higher-margin end markets. The significance of Parker-Hannifin's result is not that revenue accelerated dramatically, but that earnings quality appears to have improved as growth progressed.
For analytical follow-up, investors would likely gain more insight from segment-level operating margins, free cash flow generation, and capital allocation data than from revenue growth alone. Income statement data identifies the profitability inflection; cash flow statements and return metrics help determine how efficiently those gains are being converted into shareholder value over time.
DRDGOLD Limited (DRD)
5-Year Revenue CAGR: 14.03%
5-Year EBITDA CAGR: 28.92%
Commodity-linked businesses frequently experience earnings swings that exceed revenue movements, making DRDGOLD's appearance on this screen particularly interesting. Revenue increased at a healthy 14.03% annualized pace, while EBITDA expanded at more than double that rate, reaching 28.92%. That spread suggests operating leverage was working in the company's favor over the measurement period.
Unlike many traditional miners, DRDGOLD's business model centers on gold tailings retreatment and surface recovery operations. As a result, changes in production efficiency, processing economics, and commodity pricing can have an outsized influence on profitability. When EBITDA growth materially exceeds revenue growth in a resource company, it often signals that operating performance improved alongside supportive market conditions rather than merely reflecting higher commodity prices.
The most useful supporting datasets here would include production statistics, realized gold prices, cost-per-ounce metrics, and cash flow trends. Revenue growth explains part of the story, but profitability acceleration in mining businesses is often best understood through the interaction between operational efficiency and commodity exposure.
CME Group Inc. (CME)
5-Year Revenue CAGR: 6.21%
5-Year EBITDA CAGR: 8.29%
CME Group generated the narrowest spread among the companies in this screen, yet its inclusion remains notable because of the nature of its business model. Revenue compounded at 6.21% annually while EBITDA grew at 8.29%, indicating incremental profitability gains despite already operating from a position of significant scale and efficiency.
For exchange operators, even modest EBITDA outperformance can be meaningful. These businesses benefit from substantial fixed-cost infrastructure, meaning increases in trading activity, clearing volumes, and market participation can create operating leverage without requiring proportional expense growth. In that context, CME's profitability profile reflects a business that continued extracting incremental earnings efficiency even as revenue growth remained relatively moderate.
Recent years have also seen elevated demand for risk-management and hedging tools across interest rate, commodity, equity index, and foreign exchange markets. Rather than focusing solely on revenue, analysts often examine trading volumes, open interest trends, clearing activity, and transaction revenue composition to understand how operating leverage is developing within exchange businesses. The income statement identifies the margin trend; market activity data helps explain what is driving it.
The Signal Beneath the Growth Numbers
What makes this screen interesting is not that the five companies operate in the same industry, face the same macro backdrop, or share similar business models. They do not. A biotechnology company, a veterinary diagnostics provider, an industrial manufacturer, a gold producer, and a derivatives exchange would rarely appear together in a traditional sector-based screen. The common thread is financial: over a multi-year period, EBITDA expanded materially faster than revenue.
That distinction matters because revenue growth alone often tells an incomplete story. Top-line expansion can be driven by favorable industry conditions, acquisitions, commodity prices, or temporary demand shifts. EBITDA growth that consistently outpaces revenue, however, points toward something happening inside the operating structure of the business itself. Whether through pricing discipline, cost efficiency, product mix improvement, scale benefits, or portfolio optimization, these companies converted incremental revenue into profitability at an accelerating rate.
Importantly, EBITDA acceleration should not be viewed as a standalone signal. The next analytical step is determining why the divergence exists and whether it is being supported across other parts of the financial profile. This is where combining multiple datasets becomes more useful than relying on a single metric. Income Statement data may identify the profitability inflection, but Cash Flow Statement data helps determine whether those gains are translating into stronger operating cash generation, while Balance Sheet data can reveal whether margin improvement is occurring alongside changes in leverage, liquidity, or capital allocation.
Viewed through a broader research process, the signal becomes even more informative. One of the advantages of working across the datasets available through FMP is the ability to move beyond a single observation and test whether improving profitability is also showing up in cash generation, analyst expectations, insider activity, or changes in market value. The more independent datasets that support the same conclusion, the more confidence an analyst can have that the underlying trend is operational rather than incidental.
The larger takeaway from this week's screen is that profitability trends often emerge before they become obvious in headline narratives. Revenue growth attracts attention because it is easy to measure. The more informative signal is frequently found in how efficiently that revenue is being converted into earnings, cash flow, and operating performance over time. The five companies highlighted here arrived from different sectors and different market environments, but the underlying pattern was remarkably similar: profitability improved faster than sales, suggesting that the quality of growth deserves as much attention as the quantity.
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.
From Static Screens to a Continuous Operating Signal
The value of a screen like this is not the individual names it surfaces, but the repeatable process behind it. By consistently tracking how EBITDA and revenue evolve through Income Statement API and Income Statement Bulk API datasets, what begins as a one-time screen becomes an ongoing way to monitor where operating performance is improving faster than headline growth suggests.
If you found this useful, you might also like: Weekly Signals Desk | Five Dividend Increases Flagged by the FMP API (June 8-12)
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.
