A fresh pass through recent earnings data surfaced five tickers still clearing Street expectations with surprising consistency — even as estimate dispersion tightens and sentiment skews defensive. The screen, powered by Earnings Surprises Bulk API and Earnings Report API, continues to flag operational outliers hiding inside otherwise crowded themes.

This article breaks down how we're structuring that scan using the FMP APIs, and why streak durability matters more than the headline beat in this phase of the cycle.

Companies Sustaining EPS and Revenue Outperformance

ZS — Zscaler, Inc.

Beat Streak: 20 quarters.
Next report: Nov. 26 (Q1'26) — EPS: $0.86; Revenue: $773.25M (consensus).

Zscaler heads into Q1 with guidance that essentially brackets consensus ($0.85-$0.86 EPS; ~$772-$774M revenue), a tell that management believes last year's 23% FY growth can translate into steady—but scrutinized—momentum rather than step-ups. The August print showed ~$2.67B FY revenue (+23% YoY) and continued scale in ARR and margins; yet the stock's mixed reactions to “beats” underscore that the buy-side is grading durability of billings/RPO and platform consolidation wins more than headline surprises.

What to watch on Nov. 26: Deal cycle length and federal/large-enterprise mix will frame how sustainable mid-20s growth is against a still-defensive tape. Watch RPO and calculated billings trajectory relative to revenue (conversion + seasonality), as well as early FY26 commentary; the market has faded beats when forward look is merely “in-line.”

DDOG — Datadog, Inc.

Beat Streak: 20 consecutive quarters.
Next report: Nov. 6 (Q3'25) — EPS: $0.45; Revenue: $852.64M (consensus).

Datadog's setup into Q3 is defined by two vectors: product surface area widening (security, databases/Oracle support, experimentation/Eppo) and steady top-line raise cadence earlier this year, which tightened the cushion above consensus. Management set a $0.44-$0.46 non-GAAP EPS guardrail for Q3 and has a history of incremental raises tied to multi-product adoption—meaning the beat/raise bar now hinges on breadth of modules per customer and $100K+ cohort expansion rather than pure logo adds.

What to watch on Nov. 6: Net expansion and module attach will be the read-through for 2026 operating leverage; commentary on AI-adjacent workloads (vector DBs, LLM apps) could refresh the growth narrative if cloud optimization headwinds re-appear.

MU — Micron Technology, Inc.

Beat Streak: 10 quarters.
Next report: Dec. 17 (Q1'26) — EPS: $3.76; Revenue: $12.56B (consensus).

Micron enters FY26 with AI memory scarcity still the core thesis: HBM supply is effectively sold out into 2026, and the company has been signaling not just volume, but mix-driven margin lift (HBM vs. commodity DRAM/NAND). Recent disclosures around HBM4 sampling and roadmap cadence suggest a pricing/ASP umbrella that could persist even as peers catch up—keeping gross margin trajectory the focal point of the long thesis.

What to watch on Dec. 17: Bookings visibility for HBM/HBM4, capacity adds, and wafer-supply discipline will determine whether FY26 prints stair-step higher or flatten.

LITE — Lumentum Holdings Inc.

Beat Streak: 9 quarters.
Next report: Nov. 4 (Q1'26) — EPS: $1.03; Revenue: $526M (consensus).

The AI datacom build-out has shifted Lumentum's center of gravity toward 400G/800G and coherent pluggables; FY25 closed with non-GAAP GM ~35% and operating margin just under 10%, showing mix improvement even through telecom pauses. New L-band 400/800G ZR+ modules, now sampling, widen the addressable market for DCI and long-haul upgrades—key for sustaining margin as hyperscalers push bandwidth density.

What to watch on Nov. 4: Order cadence and price/mix in datacom vs. telecom; any color on 800G ZR+ ramps into calendar '26 will shape how credible the streak is against cyclical inventory resets.

AMZN — Amazon.com, Inc.

Beat Streak: 4 quarters.
Next report: Oct. 30 (Q3'25) — EPS: $1.56; Revenue: $177.75B (consensus).

For Amazon, the “beat” debate is less about retail comps and more about AWS margin velocity and ads durability. Into Q3, the market focus has narrowed to unit-level efficiency (regionalized logistics/robots) and AI monetization pacing inside AWS—especially after a recent AWS outage put resiliency and cost of reliability in the conversation. Company guidance anchors the date and format; previews point to the standard late-October cadence with investors zeroing in on AWS growth re-acceleration versus Q2.

What to watch on Oct. 30: AWS operating margin and backlog, ads growth ex-political, and North America retail EBIT run-rate.

Reading Beat Streaks in Context

Across this week's set — cybersecurity platforms scaling into federal budgets, observability vendors broadening product attach, memory suppliers benefiting from AI mix, optical components riding bandwidth upgrades, and hyperscale platforms extracting margin from logistics and cloud — the common thread isn't just that they beat. It's how those beats materialize. Once a streak emerges, the market shifts from celebrating discrete surprises to interrogating trajectory: are margins widening because of mix and scale, or because costs were deferred? Are billings and backlog pulling forward demand, or merely holding as expectations rise?

To parse that dynamic, layering datasets becomes the differentiator. When quarterly margin trends from the Income Statement Bulk API are observed alongside deferred revenue growth and RPO data from the Earnings Report API, you can separate structural operating leverage from short-lived pricing power. At the same time, estimate revisions and price targets sourced through the Analyst Estimates API reveal whether the Street is still catching up — or has already priced in perfection. That's where streaks often break: when sentiment outruns evidence.

Capital allocation offers another filter. Cross-referencing share repurchase and capex spending from the Cash Flow Statement API with insider transaction disclosures via the Latest Insider Trading API can surface management's conviction (or caution) into their own forward curve. When buybacks accelerate as margins inflect, or insiders lean in ahead of product cycles, the streak's credibility looks very different than when compensation-driven selling coincides with guidance haircuts.

The strategic read-through: beat streaks compress the reaction function. As quarters stack, the burden shifts from “Did they beat?” to “Did the beat improve the forward slope?” Companies that pair upside with expanding backlog, mix-driven margin lift, and credible guidance typically earn multiple support even through macro rotation. Those delivering beats while backlog flattens or expense timing does the work risk benign prints trading sideways. Ultimately, the streak is the symptom. The signal sits in how consistently these operators convert operational control into forward leverage — and whether the market remains genuinely surprised, or simply waiting for gravity.

A Practical Workflow for Surfacing Repeat Outperformance via FMP API

A straightforward way to identify companies that repeatedly clear expectations is to start with a broad EPS surprise sweep rather than cherry-picking individual tickers. The Earnings Surprises Bulk API lets you pull every reported beat and miss for a given year with a single call, making the initial universe easy to assemble:

1. Pull Bulk Earnings Surprises

Use the Earnings Surprises Bulk API to retrieve positive or negative EPS surprises across a broad universe:

https://financialmodelingprep.com/stable/earnings-surprises-bulk?year=2025&apikey=YOUR_API_KEY

Sample Response:

[

{

"symbol": "AMKYF",

"date": "2025-07-09",

"epsActual": 0.3631,

"epsEstimated": 0.3615,

"lastUpdated": "2025-07-09"

}

]

Since the payload includes both positive and negative surprises, the first filter is simple: keep only names where epsActual is greater than epsEstimated. That trims the dataset to companies that actually cleared the bar.

2. Retrieve Company-Level Details

Once you have that smaller list, shift from isolated beats to streak behavior. For each ticker that survived the first pass, call the Earnings Report API:

https://financialmodelingprep.com/stable/earnings?symbol=AAPL&apikey=YOUR_API_KEY

Review the historical quarters and count how long the company has been posting results at or above consensus. You can apply your own screening rules here — maybe you only flag streaks of three straight beats, or require a minimum surprise percentage to eliminate marginal outperformance.

If you want to push the analysis further, connect this workflow to other fundamentals available at FMP. Layering margin trends, balance-sheet signals, or cash-flow pressure on top of beat streaks often exposes whether the upside is coming from mix, discipline, or one-off timing — turning a simple filter into a more durable signal.

For a more sophisticated angle, integrate insights from this article on earnings-quality by FMP, using it as a guide to check whether a beat streak is supported by durable cash flow and transparent accounting rather than just headline buoyancy.

Scaling the Screen as Coverage Broadens

You can prototype this streak screen on the Free plan, which already covers high-profile tickers such as AAPL, GOOGL, and JPM — plenty to confirm the logic against well-trafficked names. As the workflow matures, the Starter plan expands reach across the full U.S. equity universe, making the signal more representative across sectors and market caps. For teams comparing peers across regions, the Premium plan extends coverage into U.K. and Canadian listings, allowing the same methodology to run without geographic blind spots.

Standardizing the Signal Across Research and Risk

Once an earnings-streak screen proves reliable at the desk, the real leverage comes from pushing it into the firm's common process. Centralizing the data means the signal isn't trapped in one analyst's spreadsheet; instead, research, portfolio, and risk functions can reference the same structured history and interpret trends from a shared baseline.

With a unified feed, each group can calibrate its own parameters — streak length, surprise magnitude, margin resilience — without rebuilding the plumbing. Portfolio managers can map the output to sector exposure or conviction tiers to identify crowded momentum pockets. Risk and compliance benefit from standardized timestamps and outcomes, improving backtests, reviews, and audit trails without manual reconstruction.

For teams rolling this into dashboards or internal tools, the Enterprise plan offers the infrastructure to centralize versioning, reinforce governance, and keep cross-team workflows aligned rather than fragmented. The end result is a repeatable signal that scales — not another one-off model living on an island.

Turning Consistency into Forward-Looking Insight

Reliable beat streaks tend to bend expectations forward, influencing how credibility and future leverage get priced. With a systematic layer built using the Earnings Surprises Bulk API and adjacent fundamentals, the signal evolves from a quarterly surprise check into a continuous read on operational momentum.

Want more? Explore our earlier article: Where Stock Price Lags Analyst Target: 5 Stocks Flagged via FMP API