This week's broad screen of quarterly EPS patterns — generated through the FMP's Earnings Surprises Bulk API — surfaced five names that continue to deliver uninterrupted beat sequences. Before diving into the individual streaks, here's a concise read on what the data is actually signaling and why these breakouts stand apart from the wider earnings universe.

Five Names Driving the Earnings Momentum Map

RTX RTX Corporation

Beat Streak: 8 quarters.
Next quarterly report: Jan. 27 — EPS: $1.44; Revenue: $22.65B (consensus).

RTX arrives at this list with an eight-quarter beat streak, and its most recent Q3 2025 results reinforce that consistency. The company delivered sales of $22.5 billion, up 12% year-over-year, and delivered adjusted EPS of $1.70, a 17 % gain. What makes this noteworthy isn't just a single beat but the durability across business lines: commercial aerospace (aftermarket and OE), military/defense contracts, and backlog. As of Q3, RTX reports a backlog of $251 billion — a mix of $148B commercial and $103B defense-related orders (Q3 earnings report).

That backlog affords visibility across multiple years and reduces reliance on spot-market cycles, giving the beat streak structural ballast rather than coincidence.

The signal here is structural execution. Across commercial aerospace, defense, and services, RTX is delivering volume, cash flows, and backlog growth — a triad that underpins sustainable earnings delivery. Pulling up additional datasets, such as segment-level margin trends and contract win-rates (new awards) would help illustrate whether this beat streak is driven by higher pricing, volume, margin expansion, or a mix.

CRDO Credo Technology Group

Beat Streak: 6 consecutive quarters.
Next quarterly report: March. 3 — EPS: $0.73; Revenue: $247.6M (consensus).

Credo enters with a six-quarter beat streak. The consensus for the next quarter lists EPS of $0.73 and revenue of $247.6M.

The recent fiscal-year 2025 report shows a sharp acceleration: revenue reached $170.0 million in Q4 (up 179.7 % year-over-year), and the firm ended the period with cash and short-term investments of about $431.3 million (Q4 earnings report).

This growth likely reflects rising demand for high-performance interconnect solutions from hyperscale data centers and AI infrastructure providers. If the demand backdrop for AI/ML workloads continues, Credo is possibly riding structural demand tailwinds rather than cyclical spikes. For readers, the strength in both top line and margins makes the beat streak more credible than a simple “quarter-to-quarter outperformance.” To further evaluate sustainability, one might pull order-book data, customer concentration stats, and backlog disclosures — these would clarify how much of current results are recurring versus one-off license or deployment events.

STX Seagate Technology

Beat Streak: 6 quarters.
Next quarterly report: Jan. 20 — EPS: $2.77; Revenue: $2.73B (consensus).

Seagate's six-quarter beat streak comes against a contrasting industry backdrop for storage demand. According to its Q1 fiscal 2026 release, the firm reported revenue of around $2.63 billion and non-GAAP EPS of $2.61, up significantly compared with the prior year (Q1 earnings report).

What stands out beyond the numbers is the structural shift in demand — Seagate is increasingly benefiting from heightened cloud-storage and AI-driven data-center demand, rather than legacy PC/consumer cycles. The company recently ramped its HAMR-based “Mozaic” high-capacity drives to lead cloud customers. That transition points to a demand re-orientation: larger capacity, fewer units, higher margin, and recurring replenishment — a fundamentally different revenue model than classic PC HDD demand.

For readers, the beat streak suggests Seagate isn't just outperforming near-term estimates but is aligning its product roadmap with secular trends (cloud/AI/data center scale-up). More revealing would be data on backlog, customer segmentation (cloud/hyperscale vs enterprise vs legacy), and margin breakdown by product type — such datasets would show if current strength is a temporary bounce or structural repositioning.

VLO Valero Energy Corporation

Beat Streak: 5 quarters.
Next quarterly report: Jan. 29 — EPS: $3.31; Revenue: $28.47B (consensus).

Valero posts a five-quarter beat streak, with the next earnings target signaling EPS of $3.31 and revenue consensus of $28.47B.

The importance of Valero's beat streak lies partly in the balance between traditional refining cash flow and evolving energy transition initiatives. As regulatory and demand dynamics shift, a firm able to deliver consistent earnings while investing in low-carbon fuels may combine resilience with optionality. For deeper analysis, segment-level metrics — refining throughput, crude spreads, renewable-fuels margin, capital expenditure on clean-fuel infrastructure — would help assess whether the beats lean on legacy strengths or on future-oriented capabilities.

W Wayfair Inc.

Beat Streak: 3 quarters.
Next quarterly report: Feb. 19 — EPS: $0.64; Revenue: $3.29B (consensus).

Wayfair brings a shorter but noteworthy streak — three consecutive quarters of earnings beats.

Although public coverage is thinner than for the other firms, a triple-quarter beat sequence suggests the company has regained some control over execution — possibly through better margin management, cost discipline, or a mix-shift toward higher-margin categories. Given the volatility typical in e-commerce retail, maintaining consistent EPS beats points to discipline in operations, inventory, and demand forecasting.

From a signal perspective, sustaining such a streak — even at a relatively modest length — signals that Wayfair may be navigating the broader retail headwinds better than peers. To validate the durability, it would be useful to see data on gross margin trends, inventory turnover, and customer acquisition costs. These metrics will show whether current earnings beats reflect transient promotions or structural improvements in unit economics.

Reading the Signal Beneath the Streaks

Looking across the five streaks, the through-line isn't sector similarity but operational coherence. RTX leans on long-cycle backlog visibility, Credo on scaling into a high-demand connectivity curve, Seagate on its pivot toward data-infrastructure capacity, Valero on disciplined refining economics, and Wayfair on sharper cost control. Each streak reflects a different mechanism for delivering consistent earnings beats, which is why treating the data as a cluster rather than isolated quarters gives the pattern real interpretive value.

The most useful way to read these sequences is as consistency signatures. When analysts pair quarterly surprise histories from the Earnings Surprises Bulk API with revenue, margin, and cash-flow trends from FMP's Financial Statements datasets, it becomes easier to see whether a streak is anchored in expanding profitability, better forecasting discipline, or simply estimate drift.

A deeper signal emerges once the earnings paths are cross-checked with market-facing metrics. Analyst estimates and insider activity — all accessible across the broader FMP platform — help determine whether the streak reflects sustainable execution or temporary lift. That mindset aligns with the analytical lens used in Quality of Earnings: Uncovering Red Flags in Financial Reports, where the focus is on distinguishing durable results from accounting noise.

Ultimately, what matters is the shape of the streak. Beats that coincide with cleaner cash generation, steady margins, and constructive estimate trends carry weight; those driven by one-offs or softer revenue quality fade quickly. Connecting these data layers turns streaks from simple scorekeeping into something closer to a reliability signal — a framework for judging how well each company's story holds up under scrutiny.

Building a Repeatability Screen with FMP Data

When the aim is to identify companies that deliver earnings beats on a reliable, recurring basis, the cleanest approach is to start broad and narrow only once the data gives you something meaningful to sort on. Rather than checking tickers individually, you begin with the full sweep of quarterly EPS surprises and only later evaluate which names exhibit a pattern. The Earnings Surprises Bulk API is built for that kind of top-down first pass.

Just make sure your API key is active before running the workflow.

1. Pull Bulk Earnings Surprises

Begin by hitting the Earnings Surprises Bulk API, which aggregates every quarterly EPS surprise — positive or negative — for the year you specify:

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"

}

]

From here, the first cut is mechanical: isolate the entries where epsActual > epsEstimated. That gives you the universe of names that beat expectations at least once during the period — essentially a raw pool before you evaluate whether any of them can deliver that result consistently.

2. Retrieve Company-Level Details

With the preliminary list built, shift to the second layer: continuity. For each ticker that survived the first screen, pull its full quarterly earnings record using the Earnings Report API:

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

Reviewing these chronologies lets you count how many periods each company has outperformed consecutively. Different teams draw the line differently: some consider three beats in a row enough to matter, while others add a minimum surprise threshold to avoid capturing noise. Regardless of the cutoff, the goal is the same — building a repeatability profile that shows not just whether a company has beaten expectations, but how consistently and with what level of signal clarity.

Broadening the Universe as Coverage Scales

A practical way to pressure-test the repeatability framework is to begin with the Free plan, which already covers widely followed tickers such as AAPL, GOOGL, and JPM. That roster is broad enough to confirm that your streak logic behaves as expected before committing to wider scans. Once the workflow feels solid, the Starter plan is the logical progression — it extends access to the full U.S. equity universe, giving the screen a more representative sector mix and a cleaner distribution across market caps.

If the goal is to run the same analysis across multiple geographies, the Premium plan adds U.K. and Canadian listings, letting the repeatability filter operate globally without gaps in coverage.

Scaling the Framework Across the Firm

Once a beat-streak screen consistently holds up in day-to-day analysis, its real value emerges when it stops being a personal shortcut and becomes part of the firm's shared research infrastructure. A workflow used by one analyst is helpful; a workflow adopted across teams becomes a common language — a way for portfolio managers, strategists, and risk groups to interpret the same signal without maintaining parallel versions of the model.

Standardizing the inputs is what makes that possible. When streak criteria, surprise thresholds, and margin interpretations all pull from the same validated datasets, narratives stay aligned and downstream decisions become easier to audit. Analysts gain a stable reference frame, PMs can plug the signal directly into sizing or factor processes, and risk teams benefit from clear provenance and historical traceability rather than ad-hoc spreadsheets scattered across desks.

To sustain that level of consistency, the process needs infrastructure: permission controls, versioning, lineage, and shared dashboards that reflect a single source of truth. The environment provided by the Enterprise plan supports exactly that kind of institutional workflow, allowing teams to build on top of the same curated data rather than reinventing it. At that stage, the beat-streak logic isn't just another model — it becomes a standardized, firmwide signal that travels cleanly across research, investment, and oversight functions.

Turning Past Beats Into Forward Indicators

Once the streaks are mapped, the exercise shifts from cataloging history to tracking how operational momentum evolves in real time. By continuing to monitor quarterly results through the FMP Earnings Surprises Bulk API, the same framework that surfaced past consistency becomes a running gauge of which companies are reinforcing their trajectory and which ones are starting to drift.

Want more? Explore our earlier article: 5 Stocks Flagged by the FMP API: Target-Gap Signals for the Week of Nov 24- 28