This week's cross-section scan surfaced a clear tension: prices easing off recent highs while aggregated analyst targets keep edging upward. Duolingo, Legend Biotech, DraftKings, Shift4 Payments, and Carrier Global all show widening valuation drift—signals that tend to appear before the revision cycle moves. The pattern shows up cleanly through the Price Target Summary Bulk API from FMP, which we'll break down in this note

Five Names Showing Unusual Upside Skew

Duolingo Inc NASDAQ:DUOL

Current Price: $185.07 • Consensus Target: $357.22 • Upside Potential: 93.0%

The platform just crossed 50 million daily active users (DAU) in Q3 2025 — up 36 % year-over-year — as revenue climbed 41 % in the same period (Q3 earnings release).

Why that matters: disclosing this kind of user-acceleration suggests their monetisation engine (subscriptions, ads, premium tiers) is beginning to scale meaningfully. When user growth and revenue growth both lift together, it signals the business model may be gaining operational leverage.

What to watch: assess whether the upgrade path from free to paid is improving and if average revenue per user (ARPU) is rising — reviewing the income-statement trends and segmentation data will clarify whether growth is sustainable or just top-line. Also keep an eye on the competition for English-learning/adult-ed space and any regulatory or AI-driven changes in consumer behaviour. From the consensus target of $357, the implied nearly doubling of market value rests on growth being sustained and monetisation deepening.

In summary: Duolingo is riding a strong growth wave; the key signal is whether they convert users into paying customers at a higher rate and control cost-growth as engagement rises.

Legend Biotech Corp NASDAQ:LEGN

Current Price: $30.29 • Consensus Target: $57 • Upside Potential: 88.1%

Recent developments: the company opened a 31,000-sq-ft R&D facility in Philadelphia to broaden its pipeline of cell-therapy assets.

Q3 2025 results: revenue up ~70 % YoY to $272.3 M, EPS of -$0.11, versus -$0.34 a year ago (Q3 earnings release).

Why that matters: A sizable revenue ramp in a biotech company that remains unprofitable suggests the commercialisation phase is progressing — potentially moving from trial era into market era. The investment in R&D infrastructure underscores management's belief in future growth beyond current products, which is a forward signal that the pipeline may contribute meaningfully in coming years.

What to watch: track clinical-trial readouts, regulatory milestones (e.g., new indications), and margin trends as revenue scales. The analyst consensus target of $57 embeds a strong multi-year outcome; if the pipeline fails to deliver, downside risk is elevated. Datasets worth checking include R&D spend, trial success rates, and analyst-target revisions to gauge sentiment shifts.

In summary: Legend Biotech is trading at a high-risk/high-reward profile — its upside is large if the pipeline behaves, but the signals to watch are clinical outcomes and margin inflection.

DraftKings Inc NASDAQ:DKNG

Current Price: $29.58 • Consensus Target: $49.45 • Upside Potential: 67.2%

Recent signals: Over the past three months the stock is down roughly 34%, reflecting weaker-than-expected Q3 results and a reduced fiscal-2025 outlook.

Why that matters: The recent decline shows the market is questioning the growth narrative — whether incremental regulation, competitive pressure, or margin squeezes are emerging. Insider selling can amplify doubt, especially in a growth name. The consensus target still implies meaningful upside, but the signal here is mixed: upside remains, but execution risk is non-trivial.

What to watch: regulatory developments (e.g., state gaming-licence changes), competitive dynamics (new entrants, price-cuts), and whether operating-income margins begin to improve. The analyst target dataset and insider-trade dataset are key: if analyst targets drop or insiders unload more shares, the narrative may deteriorate.

In summary: DraftKings offers mid-range upside, but the signal set is cautionary — the next few quarters of execution will determine whether it regains momentum.

Shift4 Payments Inc NYSE:FOUR

Current Price: $69.88 • Consensus Target: $94.88 • Upside Potential: 35.7%

Recent developments: announced a partnership with the Cincinnati Bengals to deploy its payments platform at Paycor Stadium, highlighting its push into live-venue commerce (Press release). But: a large hedge-fund sold ~$78 million in shares recently, cutting its holding in the company (nasdaq.com).

Why that matters: The stadium deal signals expansion into experiential payments — a growth vector beyond traditional retail/hospitality — so the top-line growth story has a fresh angle. On the flip side, significant institutional selling raises a red flag: either liquidity worries, valuation pause, or internal concerns. The net effect is a tempered upside (35.7 %) based on the consensus target.

What to watch: transaction volumes in new verticals (sports/entertainment), margin trends as scale increases, and institutional ownership trends (via holdings-dataset). The endpoint for payments growth and trend-analysis is useful here: does Shift4's merchant base expand, and are take-rates stable?

In summary: Shift4 is slightly less explosive in upside than the prior names, but carries a clearer monetisation path — the challenge will be to convert that into sustained earnings growth and quiet institutional support.

Carrier Global Corp NYSE:CARR

Current Price: $54.10 • Consensus Target: $69 • Upside Potential: 27.5%

Recent signals: Announced an additional $1 billion investment in U.S. manufacturing footprint and R&D/workforce expansion (to create 4,000 jobs) back in May 2025 (Press release).

Also, recently showcased battery-enabled HVAC systems — a step into grid-support and sustainable-tech solutions (Press release).

Why that matters: The strategic pivot into energy-efficiency and grid-integrated HVAC systems places Carrier more squarely in the thematic of decarbonisation and smart-infrastructure, rather than mere legacy HVAC. For an industrial, this shift suggests upside is squeezed into execution — hence the relatively modest 27.5 % potential. The story is one of transformation rather than explosion.

What to watch: margin impact of new tech, book-to-bill trends, and order-pipeline health (check backlog data in financial disclosures). The income-statement and segment-reporting endpoints matter: if the new business leads to above-trend margins, then upside may expand beyond current target. Conversely, any weakness in core HVAC markets could drag the story.

In summary: Carrier is the most conservative pick here — lower upside, but arguably less binary risk. The signal to watch is whether its innovation pivot begins to show through in earnings margins and backlog growth.

Interpreting the Gap: What the Pattern Really Signals

What stands out across these five names is not the magnitude of the upside but the asymmetry in how quickly expectations are shifting. Prices have already reacted — in some cases sharply — while the analyst layer is still catching up. That delay is the real signal: the market is absorbing new information faster than consensus models can update, creating temporary pockets of valuation drift.

The character of that drift varies by company. For growth names like Duolingo, a wide gap makes more sense when engagement metrics and operating leverage are still inflecting — fundamentals that don't always show up immediately in published targets. For biotechs such as Legend, the gap often reflects regulatory or pipeline catalysts that markets price in on headline but that analysts incorporate only after confirming data. And in more mature stories like Shift4 and Carrier, the spread frequently maps to capital-flow behavior — institutions stepping in or stepping back ahead of formal estimate revisions.

Pulling these threads together requires looking beyond price targets alone. Comparing them with cash-flow trajectory, revenue trends, or even insider activity — all easily referenced from FMP's broader dataset — helps clarify whether a gap represents overlooked strength, unpriced risk, or simply a timing mismatch. That kind of multi-layered read mirrors the approach outlined in work on monitoring fair-value drift and target-price evolution, where price targets are treated as one signal among several. When these layers point in the same direction, the dispersion stops looking like noise and starts functioning as an early indicator — a preview of where conviction is taking shape before the revision cycle formally acknowledges it.

Building a Target-Gap Screen With FMP API

A target-gap screen is straightforward to automate if the data pulls are set up in the right order. Instead of tracking targets manually, you can run the entire process as a short chain of API calls that updates smoothly across any watchlist. The sequence below reflects how most desks structure this kind of routine data pull.

Make sure you have an active API key before you begin.

Step 1: Pull Analyst Price Targets

The first pass is grabbing the consensus targets in bulk. Use the Price Target Summary Bulk API, which returns aggregated target figures for all requested tickers in one response — ideal for batch workflows.

Endpoint:
https://financialmodelingprep.com/stable/price-target-summary-bulk?apikey=YOUR_API_KEY

Sample Response:

[

{

"symbol": "AAPL",

"lastQuarterCount": "12",

"lastQuarterAvgPriceTarget": "228.15",

"lastYearAvgPriceTarget": "205.34"

}

]

Step 2: Pull Latest Market Prices

After you have the target set, you'll need the live reference price for each name. That comes from the Company Profile Data API, which includes the most recent trading level used in the gap calculation.
https://financialmodelingprep.com/stable/profile/AAPL?apikey=YOUR_API_KEY

Step 3: Derive the Target Gap

With both the current price and the consensus target available, calculate the percentage difference:

Upside % = (Price Target - Current Price) / Current Price × 100

Working in percentage terms standardizes the results so that high-priced and low-priced names can be compared on the same footing.

Step 4: Apply a Threshold Filter

Once every ticker has a score, impose a cutoff to separate noise from actionable names. A 20%+ implied upside is a common baseline, but the key is context: a large gap means more when it's backed by a meaningful number of analyst inputs rather than a handful of outliers. The strongest candidates tend to be those with both a wide spread and solid participation behind the target.

Turning Individual Screens Into Firmwide Signals

A target-gap screen has limited impact when it lives as a personal workflow. Its real value emerges once the logic becomes a shared, institutional process — one that multiple teams can reference without reinventing the same calculations in their own spreadsheets. When the underlying assumptions, refresh timing, and data definitions are consistent, conviction stops being individual intuition and becomes an aligned, cross-desk signal.

The shift isn't about adding complexity; it's about putting guardrails around what already works. Minimum coverage thresholds, rules for handling stale estimates, and a defined update cadence prevent drift and keep everyone debating the interpretation of the data rather than the integrity of the inputs. In practice, it reduces duplicated effort, cuts down on ad-hoc recalculations, and eliminates the quiet divergence that often builds between research, PMs, and risk.

At a firm level, the only signals that scale are the ones that are reproducible and auditable. They need a single source of truth, not five private versions of the same idea. That's where a centralized data backbone — like the one offered through the FMP Enterprise plan — becomes less a convenience and more an operational requirement. Once price-target logic is treated as shared infrastructure rather than a personal shortcut, it stops behaving like an insight that fades with attention and starts functioning as a durable part of the firm's decision-making architecture.

When Sentiment Turns Before Consensus Does

Price-to-target gaps are most useful when treated as forward signals rather than final judgments. The advantage comes from spotting when sentiment starts to firm up before the revisions show it, and this screen is built to catch exactly that shift — anchored by the same dataset powering the workflow: FMP's Price Target Summary Bulk API.

If you enjoyed this analysis, you'll also want to read: 4 Insider Trades That Matter - Tracked with the FMP API (Week of Nov 3 - 7)