This week's multi-year growth sweep turned up an unusually tight cluster of names where efficiency curves are accelerating faster than topline expansion. Pulls from the FMP's Income Statement API reveal a clear inflection: EBITDA trajectories bending upward at a pace that outstrips revenue across five otherwise unrelated companies.

In this note, we break down the signals emerging from those API reads and outline why this dataset is worth a closer look for anyone tracking structural—not cyclical—momentum.

5 Companies Showing Clear CAGR Momentum

ADSK Autodesk, Inc.

5-Year Revenue CAGR: 13.42%
5-Year EBITDA CAGR: 25.65%

Over the past half-decade, Autodesk's revenue growth — 13.42% compounded annually — indicates sustained demand for its design and engineering software across construction, manufacturing and media sectors. More notable is the 25.65% EBITDA CAGR, which signals that the firm is steadily improving not just top-line sales, but operational profitability. In other words: Autodesk isn't simply growing; it's getting more efficient as it scales.

That embedded profitability trend matters because it suggests margin expansion is not purely cyclical or timing-driven, but structural — likely driven by higher mix of recurring subscription revenue, operational leverage, and perhaps tighter cost control. Recent quarterly results reinforce that narrative: in Q3 2026, Autodesk reported ~18% revenue growth to US$1.85B and non-GAAP EPS of $2.67, ahead of expectations. Meanwhile, its adjusted operating margin reached 38% in Q3 2026 (Q3 earnings report, Yahoo Finance).

What makes this trajectory significant now is the context of rising demand for software to support cloud, AI, and data-center infrastructure projects. As firms pursue digital transformation and capital-intensive construction/industrial projects, Autodesk's AECO (architecture, engineering, construction, operations) and manufacturing-design suites become essential — driving both revenue growth and recurring subscription stability. Looking ahead, it would be useful to monitor data-points such as geographic revenue mix, subscription vs. license revenue ratio, and margin by segment, to assess sustainability of this trend.

NBIX Neurocrine Biosciences, Inc.

5-Year Revenue CAGR: 23.30%
5-Year EBITDA CAGR: 24.23%

Neurocrine's five-year revenue CAGR of 23.30% reflects robust underlying growth in its biotech/therapeutics business — a pace rare in non-blockbuster years. The accompanying 24.23% EBITDA CAGR implies it's not burning cash indiscriminately; rather, its growth appears disciplined, with earnings scaling roughly in line with sales. That kind of alignment is frequently indicative of effective cost control, lean R&D spending relative to success, or a shift toward higher-margin products.

This signal becomes more compelling in light of typical volatility in biotech, where many firms invest heavily before achieving revenue inflection. For NBIX, the data suggests it's beyond the early “burn rate” phase and may have reached a more stable operating cadence. To deepen this view, it would be helpful to review its product-level margins, R&D-to-sales ratio, and product pipeline success rates — especially since earnings momentum in biotech can hinge as much on approvals or clinical milestones as on consistent sales.

ANET Arista Networks, Inc.

5-Year Revenue CAGR: 26.78%
5-Year EBITDA CAGR: 33.64%

Arista's revenue grew at a compound annual rate of nearly 27% over five years — already impressive for a networking-hardware and cloud-infrastructure vendor. Even more striking is a 33.64% EBITDA CAGR, suggesting that as the company has scaled, its profitability has expanded even faster than its top line. That kind of acceleration in operating profit points to strong operating leverage, possibly driven by scale advantages in design, manufacturing, and distribution, combined with recurring software or services revenue.

To validate the signal, tracking gross margin trends, software-service revenues vs hardware sales, and capex/research spend relative to sales would give a clearer picture of how sustainable and scalable the economics are.

SCCO Southern Copper Corporation

5-Year Revenue CAGR: 11.06%
5-Year EBITDA CAGR: 18.66%

For a mining and materials company, Southern Copper's 11% revenue CAGR over five years suggests consistent growth — perhaps driven by commodity demand cycles, capacity expansion, or favorable pricing environments. The 18.66% EBITDA CAGR indicates that profitability has improved at a faster compound rate than revenues, implying margin enhancement rather than just top-line inflation. That points to better cost management, higher-margin ore grades, or operational efficiencies.

In a sector often at the mercy of commodity price swings, this steady EBITDA growth signals a degree of resilience: the firm isn't just riding commodity-price windfalls, but seems to have structural improvements that support earnings even in volatile markets. From an analytical vantage, it would be useful to surface data on ore-grade quality, operating cost per ton, capex cycles, and realized copper prices — to distinguish between sustainable improvement versus cyclical gains masked as earnings growth.

TALO Talos Energy Inc.

5-Year Revenue CAGR: 25.51%
5-Year EBITDA CAGR: 98.99%

Talos stands out most dramatically: a roughly 25.5% annual revenue growth compounded over five years is strong, but the near-100% EBITDA CAGR is striking — suggesting that profitability has exploded even more rapidly than sales. In capital-intensive energy or exploration sectors, such a disproportionate rise in EBITDA relative to revenue typically points to operational leverage, cost rationalization, or swings in commodity/production pricing — not a small feat.

This kind of skew implies that over the period, Talos may have significantly improved its cost structure, raised realized commodity prices, or achieved scale in production such that fixed costs dilute rapidly. It reflects a transition from perhaps growth-focused investment to efficient production/high-margin extraction. To gauge the durability of this leap, one should examine datasets such as realized oil and gas prices per barrel/mcf, unit operating costs, reserve replacement metrics, and capex vs cash flow — all of which would shed light on whether this EBITDA surge is sustainable or a product of temporarily favorable conditions.

Interpreting the Broader Pattern Behind the Numbers

Taken together, the five names reveal a shared structural dynamic: EBITDA is compounding faster than revenue across sectors that rarely move in tandem — software, biotech, networking, copper, and energy. That alignment points to operational leverage rather than simple demand-driven lift, suggesting these firms are extracting more efficiency out of each incremental dollar of growth.

The character of that acceleration varies by business model. Autodesk and Arista reflect scale economics typical of high-margin software and infrastructure. Neurocrine's pattern stems from disciplined expansion in a field where costs often surge. Southern Copper and Talos show the opposite end of the spectrum — industries shaped by input volatility — yet still post EBITDA growth outpacing revenue, a sign that operating discipline or production mix is playing a larger role than price cycles alone.

A deeper read emerges when these trajectories are viewed through multiple FMP datasets. Multi-year revenue and EBITDA trends gain clarity when set next to cash-flow behavior—especially when interpreted through frameworks like cash-flow-based earnings-quality analysis. Adding balance-sheet data from FMP's Financial Statements APIs helps distinguish genuine margin strength from leverage-driven gains, revealing which efficiency curves reflect durable operations rather than accounting optics.

Viewed from a distance, the signal is consistent: across very different industries, efficiency is proving to be the more telling differentiator. When EBITDA accelerates faster than revenue in companies with no shared structure, the trend points not to coincidence but to a broader shift in how operational advantage is being built.

How to Build a Clean CAGR Workflow Using FMP Data

A dependable CAGR screen doesn't need elaborate infrastructure. What matters is a consistent pull from the right endpoints and a workflow you can repeat without friction. The sequence below reflects how analysts typically handle multi-year growth checks directly from FMP's Income Statement endpoint, keeping the process lightweight and reproducible.

Step 1: Pull Income Statement Data

Start by requesting a single ticker through the standard Income Statement API. This initial call gives you the full run of historical reporting periods that the calculation depends on. Confirm your API key is active, then issue a request such as:

Endpoint:
https://financialmodelingprep.com/stable/income-statement?symbol=AAPL&apikey=YOUR_API_KEY

Step 2: Gather Historical Figures

From the JSON response, isolate the line item you want to evaluate — revenue, EBITDA, EPS, or any other metric — and sort those values in chronological order. You want a clean sequence before applying any growth math; consistency of ordering is what keeps CAGR logic reliable.

Step 3: Calculate CAGR

With the earliest and most recent data points identified, apply the standard formula:

CAGR = (Ending Value / Beginning Value)^(1 / Years) - 1

This approach compresses multi-year fluctuations into a single annualized rate, allowing you to see the underlying trajectory without being distracted by period-to-period swings.

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.

Expanding the Screen Into Full-Market Coverage

Broadening the workflow works best when done in stages. Begin with a small group of symbols and validate that your CAGR logic is returning consistent results; the Basic plan provides sufficient access to the Income Statement endpoints to validate the methodology before ramping up dataset size.

Once the logic holds up across that pilot set, stepping into the Starter tier becomes the natural progression. With full U.S. equity coverage, the screen can operate at market scale, making cross-company comparisons far cleaner and ensuring filters behave reliably across a wider universe.

If the analysis eventually needs to reach beyond U.S. listings or incorporate deeper historical timelines, the Premium plan adds global exchange data and extended reporting histories. At that point, the same CAGR workflow effectively transitions into an institutional-level screen — without altering the underlying process.

Turning Recurring Data Pulls into a Live Operational Read

Regular pulls through the FMP Income Statement API and Income Statement Bulk API turn CAGR from a static historical metric into a running read on how a company's efficiency curve is shifting in real time. Once the workflow is in motion, trend changes surface early, offering a clearer sense of when operational momentum is strengthening or starting to fade.

If you found this useful, you might also like: 5 Earnings Beat Streaks Tracked via FMP API (Week of Nov 24 - 28)