Weekly Signals Desk | Price-Target Gaps Identified via the FMP API (Oct 12-16)

A price-target gap can widen for two reasons: analysts raise their numbers, or the stock falls while the numbers stay put. This week was almost entirely the second kind. As AI hardware sold off for a second straight week, four of the five widest gaps in our screen opened up in semiconductor packaging, defence drones, data-centre power and optical networking, sectors where prices moved in days while published targets tend to adjust over weeks. The fifth, Las Vegas Sands, sits near its 52-week low ahead of its quarterly report.

That makes target freshness the central question. Using FMP's Price Target Summary Bulk API, this edition examines Amkor Technology, AeroVironment, Vertiv, Coherent and Las Vegas Sands, checks each consensus figure against the targets analysts have actually published in recent weeks, and shows how to build a screen that separates fresh conviction from stale numbers.

Key Takeaways

• Upside to consensus ranges from 52.9% to 88.3%, but most of that spread was created by falling prices rather than rising targets, so the gaps measure how far the market has moved away from analysts, not the reverse.
• AeroVironment and Coherent have last-quarter targets averaging above their consensus, which suggests analysts have not yet stepped back despite the price decline.
• Vertiv and Las Vegas Sands both drew target cuts this week while ratings stayed positive, a sign that consensus is starting to drift lower toward the price.
• Amkor, Las Vegas Sands and Vertiv all report results between October 21 and October 28, so several of these gaps will be tested against fresh data within two weeks.

Subscribe to FMP on Substack

Where Prices Fell Furthest Below Consensus

Amkor Technology, Inc. (AMKR)

Current Price: $41.82 • Consensus Target: $78.75 • Upside Potential: 88.3%

Amkor carries the widest gap in the screen, and the price action explains most of it. The semiconductor packaging and test provider closed lower in nine consecutive sessions through Thursday, a run that erased more than a fifth of its value, and it now sits well under half of its 52-week high. The stock is still well above where it stood a year ago, which shows how much of this year's AI-driven re-rating has been unwound in a matter of weeks rather than how the business itself has changed.

The coverage behind the consensus is thin. Only two published targets landed in the last quarter, both close to the consensus figure, and there were none in the past month. That does not make the targets wrong, but it does mean the $78.75 figure reflects views formed before the latest sell-off, when the market was paying more for advanced packaging exposure tied to AI accelerators. Amkor's operating margin is also well below the technology sector median, which leaves earnings more sensitive to utilisation swings than its higher-margin peers.

Amkor reports on October 26, which will be the first opportunity for analysts to reset with new information. FMP's Price Target Summary API on a per-symbol basis will show whether the next round of published targets lands closer to the current price or holds near consensus, while the Income Statement API tracks whether utilisation and margins are improving as advanced packaging volumes ramp.

AeroVironment, Inc. (AVAV)

Current Price: $121.79 • Consensus Target: $215.64 • Upside Potential: 77.1%

AeroVironment presents the strongest case in the group that analysts have not lost conviction. The four targets published in the past month average well above the consensus figure, and last quarter's average sits above it as well. That pattern is unusual for a stock that has fallen to within a few percent of its 52-week low and now trades at less than a third of its yearly high. The gap here reflects a market that has moved sharply away from a coverage group that has stayed constructive.

The fundamental backdrop gives analysts some support. In its fiscal first quarter, reported in early September, AeroVironment beat revenue and earnings estimates, posted a record funded backlog, and reaffirmed full-year guidance, with a sizeable counter-drone system award adding to the order book. The tension sits in timing: management expects most of its annual earnings in the second half of the fiscal year, and its space, cyber and directed energy segment declined, which leaves near-term results carrying a heavy burden of proof.

The Financial Estimates API is the natural tool for testing that second-half weighting, since it shows how quarterly revenue and EPS expectations are distributed across the year. Pairing it with the Balance Sheet Statement API helps track how working capital and contract assets are building as backlog converts, a useful indicator of whether the order book is turning into cash on schedule.

Vertiv Holdings Co (VRT)

Current Price: $206.42 • Consensus Target: $364.94 • Upside Potential: 76.8%

Vertiv shows the clearest sign of a consensus starting to adjust. Two firms trimmed their targets this week while keeping positive ratings, and the average of targets published in the last month sits below the consensus figure. The data-centre power and cooling supplier has fallen well below its 52-week high, with this week's decline tied to market concerns about how AI infrastructure build-outs will be financed rather than to any company-specific disclosure.

That distinction matters for interpreting the gap. Vertiv's business depends on hyperscale and colocation customers continuing to commit capital to new data centre capacity, so questions about credit costs and funding for those projects feed directly into how the market values its order book. Analysts, meanwhile, are still anchored to demand trends visible in recent quarters. The result is a wide gap that combines a falling price with a gradually softening target base.

Vertiv reports on October 28, and orders, backlog and book-to-bill will carry more weight than the headline earnings figure. The Earnings Report API shows how often Vertiv has met or exceeded estimates over the past several quarters, while FMP's Historical Stock Grades API offers a way to track whether the recent target cuts turn into rating changes as more firms revisit their models.

Coherent, Inc. (COHR)

Current Price: $232.90 • Consensus Target: $385.89 • Upside Potential: 65.7%

Coherent sits in the middle of the optical networking sell-off, which hit the group hardest of any AI hardware segment this week. The stock fell more than 25% between the Friday closes, alongside steep declines at Lumentum and Ciena, without any company-specific announcement. The move followed a year in which optical suppliers delivered some of the largest gains in the market, and much of the selling has been described as profit-taking and rotation into more defensive sectors.

On the target side, last quarter's average sits above the consensus figure, though the single target published in the past month came in lower. That suggests analysts have not yet repriced the business but may be starting to. Management said on its most recent earnings call that it saw no signs of customer demand weakening, and the company's exposure to transceivers, indium phosphide lasers and co-packaged optics keeps it central to data centre bandwidth upgrades.

The Revenue Product Segmentation API is useful here because it separates the data centre and communications business from Coherent's industrial and materials segments, which helps show how concentrated the earnings base is in the part of the market now under pressure. The Key Metrics TTM API adds valuation context, showing how far multiples have compressed relative to the company's own recent history.

Las Vegas Sands Corp. (LVS)

Current Price: $38.01 • Consensus Target: $58.13 • Upside Potential: 52.9%

Las Vegas Sands is the only name in the group without direct AI exposure, and its gap has a different character. The stock sits near its 52-week low and well below its high, and the casino operator's results in the second quarter fell short of earnings expectations. This week Goldman Sachs cut its target substantially while keeping a Buy rating, and the single target published in the past month sits below consensus, pointing to an estimate base that is starting to move lower.

The debate centres on Macao and Singapore, where the company's integrated resorts generate essentially all of its earnings. Last quarter's average target sits slightly above consensus, so analysts as a group still see recovery potential, but the most recent cuts suggest they are tempering expectations for the pace of that recovery. The gap here looks less like a sudden price dislocation and more like a slow-moving disagreement about the earnings base.

Las Vegas Sands reports on October 21, the first of the five to do so. The Financial Estimates API tracks whether revenue and EBITDA forecasts are drifting ahead of the report, and the Revenue Geographic Segments API can separate Macao from Singapore results, which matters because the two markets have recovered at different rates.

What a Falling-Price Gap Tells You

The common thread this week is that four of the five gaps were created primarily by price, not by targets. When a sector sells off quickly, the price-target gap widens mechanically, and the size of that gap says more about the speed of the market move than about analyst conviction. A wide gap in that environment is a prompt to check how recent the targets are, how many analysts stand behind them, and whether the latest revisions are moving up or down.

That is where target freshness becomes the most useful lens. AeroVironment and Coherent still show last-quarter target averages above consensus, which suggests analysts are holding their views through the sell-off. Vertiv and Las Vegas Sands show recent cuts, a pattern that has often preceded a lower consensus figure as more firms update, depending on what the next results show. Amkor sits in between, with too few recent targets to judge. Within the FMP dataset, comparing the last-month, last-quarter and last-year averages in the Price Target Summary Bulk API is a simple way to rank gaps by freshness rather than size.

The next layer is whether fundamentals are moving in the same direction as targets. Combining the Price Target Consensus API, which shows the high and low ends of the target range, with the Financial Estimates API reveals whether target changes are being driven by lower earnings forecasts or by lower valuation multiples. With three of the five reporting by the end of October, the Earnings Calendar API also helps time when each gap is most likely to be tested, turning the screen from a static snapshot into a schedule of upcoming checkpoints.

Creating a Structured Target-Gap Workflow

A price-target spread only becomes useful when the calculation can be reproduced reliably. That means fixing the data inputs, pulling them in a consistent sequence, and applying the same formula every time the screen runs. Once those elements are standardized, the exercise stops being a one-off comparison and turns into a process that can be refreshed on a schedule.

The only requirement before running the workflow is a valid API key.

Step 1: Pull Analyst Price Targets

The process starts by establishing where consensus currently sits. This is done by querying the Price Target Summary Bulk API, which returns average price targets along with analyst participation counts across the ticker set in a single call. That combination matters: the average target provides the reference level, while coverage depth helps contextualize how representative that number is. Together, they form the baseline against which market prices will be compared.

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

Once targets are in place, the next input is the current trading price. This comes from the Company Profile Data API, which includes the most recent quote used for comparison. At this stage, the goal isn't granularity or intraday precision — it's simply to anchor each name to the same market reference point so gaps are calculated consistently.

https://financialmodelingprep.com/stable/profile/AAPL?apikey=YOUR_API_KEY

Step 3: Derive the Target Gap

Once both values are available, the gap itself is straightforward to compute. Express it as a percentage to normalize results across different price levels:

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

Using percentages allows large-cap and lower-priced names to sit in the same ranking without distortion.

Step 4: Apply a Threshold Filter

The final layer is judgment. Most workflows introduce a minimum threshold — often around 20% — to filter out routine variance and focus attention on gaps that are large enough to matter. At this stage, analyst coverage becomes part of the interpretation: a wide gap backed by broad, recent coverage carries a different weight than one driven by a small or outdated estimate set.

Structured this way, the process moves beyond a simple valuation screen. It becomes a repeatable diagnostic tool — one that highlights where price and consensus are drifting apart and does so in a way that can be refreshed, audited, and scaled across time and coverage universes.

From Individual Screen to Institutional Research Process

Most quantitative workflows begin quietly — a model or screen built by a single analyst to answer a recurring question with greater consistency. The first version usually lives in a spreadsheet or a small script: efficient, practical, and tailored to the needs of one desk. The turning point arrives when the signal proves useful enough that colleagues begin asking for it. Replication follows, and with it comes an unintended side effect: slight variations in endpoints, refresh schedules, or calculation logic start producing subtly different results.

At that stage, the analyst who created the workflow often becomes an informal architect of standardization. The challenge shifts from running the screen to defining the method behind it. Institutional value emerges when the process is formalized: the data sources are fixed, the sequence of API pulls is documented, formulas are locked, and thresholds are explicitly defined. Once those elements are stabilized, the workflow stops being a personal tool and begins to function as a shared research input.

Moving the process into a centralized dashboard with scheduled updates is usually the next step in that evolution. Instead of circulating spreadsheets or ad-hoc scripts, teams interact with the same data pipeline and the same calculation framework. This reduces workflow fragmentation across research groups and allows portfolio managers, analysts, and risk teams to reference the same signal simultaneously. When everyone is drawing from the same dataset and methodology, discussions shift away from reconciling numbers and toward interpreting what the signal actually means.

Standardization also strengthens governance and transparency. A centralized workflow creates a visible audit trail: where the data originated, when it refreshed, and how each metric was derived. That lineage matters in institutional environments where reproducibility is essential. When colleagues run the same query and obtain the same result, the signal becomes dependable infrastructure rather than a one-off analytical shortcut.

Scaling that kind of workflow across a team requires stable access to the underlying datasets and consistent distribution across users. Infrastructure becomes less about adding features and more about removing friction from the research process. Platforms designed for institutional usage — such as FMP's Enterprise plan — provide the access controls, refresh stability, and shared environment needed when a desk-level workflow transitions into a broader research tool.

When that transition happens successfully, the model itself changes role. The target-gap screen is no longer simply a clever comparison between price and analyst targets. It becomes part of the firm's analytical framework — a standardized diagnostic that multiple teams can rely on to identify where market pricing and consensus expectations are beginning to drift apart.

When Prices Move Before the Targets Do

This week's widest gaps were opened by the market, not by analysts, and the coming earnings reports will show which side moves to close them. Watched through FMP's Price Target Summary Bulk API , the freshness of each target matters as much as its distance from the price.

If you enjoyed this analysis, you'll also want to read: Weekly Signals Desk | Concentrated Analyst Revisions via the FMP API (Oct 5-9)

Get your free API key

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.