This week's screen surfaced a familiar but widening pattern: valuation gaps are reopening across parts of the market that have quietly lagged recent momentum trades. Using the FMP's DCF Valuation API as the anchor, we ran a fresh pass across U.S. equities to identify where price has drifted furthest from modeled intrinsic value — not as a call to action, but as a signal of where expectations and fundamentals may be diverging again.

What emerged was a small cluster of large, liquid names where sentiment and price have moved faster than the underlying cash-flow math. This piece walks through those five cases and explains how the same API-driven framework can be used to monitor whether these gaps continue to widen, stabilize, or reverse as new data flows in.

This Week's Screen: Where Valuation and Price Are Furthest Apart

Merck & Company Inc (NYSE: MRK)

DCF Value: $195.76 — Market Price: $106.45 → Upside Potential: ~+84%

Merck's valuation gap is the widest in this screen, shaped largely by investor focus on patent exposure and long-term revenue replacement risk. While near-term earnings remain supported by key franchises, the market continues to discount uncertainty around the post-patent period, compressing the multiple despite sustained cash flow strength.

From a data perspective, this is a case where forward-looking valuation models diverge sharply from sentiment-driven pricing. Monitoring pipeline disclosures, regulatory milestones, and revenue mix evolution becomes central to interpreting whether the discount reflects a realistic earnings transition or an overly conservative read-through of long-term risk.

PayPal Holdings Inc (NASDAQ: PYPL)

DCF Value: $100.80 — Market Price: $60.04 → Upside Potential: ~+68%

PayPal continues to screen as one of the widest valuation dislocations among large-cap financial technology names. The gap reflects a prolonged reset in growth expectations as transaction volumes normalize and competition intensifies across digital payments. Despite this, the business still generates substantial free cash flow, and recent operating commentary has emphasized cost discipline and margin stabilization rather than top-line acceleration.

The disconnect highlighted by the DCF output underscores how sharply market sentiment has repriced platform economics relative to long-term cash generation. For analytical context, pairing valuation data with trends in total payment volume, take rates, and operating margin progression helps determine whether the discount reflects structural erosion or simply a recalibration of growth assumptions.

Progressive Corp (NYSE: PGR)

DCF Value: $378.01 — Market Price: $227.66 → Upside Potential: ~+66%

Progressive's screen result reflects the lag between underwriting-driven earnings recovery and market recognition of improved profitability. Recent pricing actions and underwriting discipline have materially reshaped loss ratios, yet equity pricing has not fully caught up to the magnitude of that improvement in modeled cash flows.

In this case, the valuation gap is best interpreted through the lens of underwriting cycle normalization rather than top-line growth. Tracking combined ratios, premium growth, and reserve development offers a clearer framework for understanding whether the valuation disconnect narrows as earnings quality becomes more visible in reported results.

Deckers Outdoor Corporation (NYSE: DECK)

DCF Value: $151.53 — Market Price: $100.95 → Upside Potential: ~+50%

Deckers stands out as a case where price momentum has cooled faster than the underlying earnings profile. The gap between modeled value and market price reflects a period of consolidation following several years of strong brand-led growth, particularly across HOKA and UGG. While recent quarters have shown normalization in demand after an unusually strong post-pandemic cycle, cash generation and margin structure remain materially stronger than pre-2020 levels. The divergence suggests the market may be compressing multiples faster than the underlying operating profile has deteriorated.

From a signal perspective, this is a classic example of a consumer discretionary name where expectations have reset quickly, but fundamentals have not collapsed in parallel. Tracking forward revenue revisions, inventory levels, and gross margin stability—alongside the DCF trend—offers a clearer lens on whether the valuation gap reflects transient sentiment or a deeper shift in earnings durability.

Hormel Foods Corporation (NYSE: HRL)

DCF Value: $35.91 — Market Price: $24.35 → Upside Potential: ~+47%

Hormel's valuation gap reflects a prolonged reset in packaged food equities, driven by margin pressure from input costs and uneven volume recovery. While near-term profitability has been pressured, the company's cash-flow profile remains comparatively stable, supported by a diversified brand portfolio and pricing actions that have gradually filtered through the income statement.

The disparity between price and modeled value highlights how defensive consumer staples can still experience valuation compression when earnings visibility weakens. Tracking cost trends, pricing elasticity, and volume recovery provides the most relevant signal for whether the current discount narrows or persists.

Interpreting the Signal Beneath the Price Action

Viewed together, these five names point to a common dynamic: price has moved ahead of underlying cash-flow expectations, but not in a uniform or purely sentiment-driven way. The divergence spans consumer, healthcare, financials, and staples, suggesting the market is not rotating wholesale but selectively repricing durability. In several cases, valuation compression appears tied less to deteriorating fundamentals and more to uncertainty around how sustainable recent performance proves to be.

This becomes clearer when DCF outputs are examined alongside supporting data rather than in isolation. Comparing intrinsic value estimates with operating cash flow trends, margin behavior, and forward expectations helps distinguish between short-term earnings noise and longer-cycle structural questions. Frameworks such as those outlined in FMP's overview of Discounted Cash Flow modeling for growth companies are useful here, not as forecasting tools, but as a way to understand how assumptions compound over time.

Seen through that lens, the screen functions less as a ranking of mispriced equities and more as a diagnostic lens. By grounding valuation gaps in underlying financial data available through the Financial Modeling Prep platform, the analysis highlights where expectations and fundamentals are drifting apart—and where future disclosures are most likely to reshape the narrative.

Turning DCF Snapshots Into a Live, Repeatable Signal

A single DCF snapshot can highlight a valuation mismatch in the moment, but it loses relevance quickly as prices, estimates, and assumptions update. To make the signal durable, the process has to move from a one-off check to something that refreshes automatically—recomputing intrinsic value, aligning it with live pricing, and tracking how the gap evolves over time rather than treating it as a static data point.

Before you start, make sure your API key is ready.

Step 1. Query the DCF Valuation API

The workflow starts with the DCF Valuation API, which serves as the foundation for the entire process. This endpoint returns both the modeled intrinsic value and the current market price in one response, removing the need to reconcile multiple data sources before analysis begins. Having valuation and price captured together ensures consistency and reduces the risk of timing mismatches that can distort comparisons.

Sample response

[

{

"symbol": "AAPL",

"date": "2025-02-04",

"dcf": 147.27,

"Stock Price": 231.80

}

]

Step 2. Compute the Upside

With both fields in hand, the next step is to normalize the gap. Converting the difference between DCF and market price into a percentage allows the results to be compared across names with very different share prices:

Upside % = (DCF - Stock Price) / Stock Price × 100

In the example above, the calculation produces roughly -36%, indicating the stock is trading above the modeled intrinsic value. Positive figures flag the opposite condition—where price sits below DCF—which is the core signal this screen is designed to capture.

Step 3. Scale It into a Screening Loop

The workflow becomes materially more useful once this logic is applied at scale. Running the DCF endpoint across a defined universe, calculating the percentage spread for each symbol, storing the results, and ranking them by upside converts a static check into a living screen. When automated on a recurring cadence, the process continuously surfaces where price and intrinsic value are drifting further apart or beginning to converge, making it easier to monitor valuation pressure as market conditions shift.

Scaling a Proven Valuation Framework Across Broader Coverage

Valuation workflows tend to scale best when they're extended deliberately rather than all at once. The Basic plan is typically where the process proves itself—supporting enough throughput to validate the DCF logic, confirm calculation consistency, and test how results store and rank across a limited universe. At this stage, the objective isn't breadth, but confidence that the mechanics hold up under repeat use.

Once that foundation is stable, expanding coverage becomes a matter of scope rather than redesign. The Starter plan allows the same framework to run across a broader set of U.S. equities and deeper historical windows, without changing how the workflow itself operates. The underlying logic remains intact; only the surface area increases. That continuity is what allows scale without introducing unnecessary complexity or rework.

For teams running frequent updates or monitoring multiple geographies, the workflow naturally evolves into the Premium tier. Higher request limits and access to additional markets, including the U.K. and Canada, shift the system from an occasional analytical tool to a persistent reference layer.

When Analyst Tools Become Shared Infrastructure

As valuation workflows mature, their role often shifts from individual productivity aids to shared analytical infrastructure. What begins as a single analyst's method for standardizing assumptions and tracking valuation signals tends to expose a broader need across the organization: consistency in how data is sourced, interpreted, and updated. Once multiple teams are referencing similar questions—often with slightly different models or spreadsheets—the inefficiency becomes structural rather than personal.

At that stage, the value of a common framework becomes clear. A repeatable workflow built around consistent inputs and transparent logic allows teams to align on the same reference points, reducing discrepancies that arise from fragmented models or manual updates. Shared dashboards replace isolated files, valuation logic becomes reviewable rather than implicit, and changes to assumptions can be traced and discussed rather than rediscovered independently. The result is less time spent reconciling numbers and more time spent interpreting what they imply.

For organizations reaching that level of coordination, the transition to an enterprise-grade setup is less about scale for its own sake and more about durability. The Enterprise Plan supports this shift by enabling shared access, governance, and auditability across teams, allowing a valuation framework that began at the desk level to function as a consistent analytical backbone across the firm.

Using Valuation Gaps to Frame What Comes Next

Viewed together, these valuation gaps are less about calling inflection points and more about identifying where future information will matter most. When price and modeled value diverge this clearly, the signal isn't predictive—it's directional, highlighting where updates to cash flows, guidance, or fundamentals are most likely to change the narrative. Framed this way, tools like the FMP DCF Valuation API become less about forecasting outcomes and more about keeping analytical focus aligned with where the next meaningful data is likely to land.

Expand your watchlist with our previous deep dive: Weekly Signals Desk | 5 Dividend Hikes via the FMP API (Dec 15-19)

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.