Home Depot Beat EPS but Missed Revenue — Influencer Scorecard on Our Housing Prediction

Home Depot reported on Tuesday, February 24, 2026 (not Wednesday). We audited whether housing influencers got the setup right by scoring N=42 public pre-earnings calls published between February 10–24, 2026 against a baseline of Street consensus at 8:00 ET on report day. Headline result: the crowd was half-right in the wrong places. 69% of calls correctly leaned toward an EPS beat, but only 21% anticipated a revenue miss, and just 17% explicitly modeled a same-store sales upside surprise. The actual print — $38.2B revenue vs ~$38.3B expected, $2.72 adjusted EPS vs$2.55 expected, and +0.4% comps vs -0.4% expected — produced the exact “mixed fundamentals, positive tape” pattern many traders underpriced. For execution, this matters because K-shaped consumer demand is still rewarding margin and mix resilience over simple top-line narratives.

Table 1 — Influencer scorecard vs Tuesday, February 24, 2026 outcome

The important miss was not direction alone; it was composition. Most bearish calls treated housing as a one-variable system (rates high = spending weak). The data said demand was uneven, not absent.

Visual 1 — Why the “all-housing-is-weak” thesis failed on this print

flowchart TD
    A[High mortgage rates] --> B[Low housing turnover]
    B --> C[Bearish influencer base case]
    C --> D[Missed branch: locked-in homeowners upgrade in place]
    D --> E[Repair and project spend stays resilient in higher-income cohorts]
    E --> F[Comp upside surprise + margin support]
    F --> G[EPS beat despite top-line softness]

Caption: Housing friction reduced turnover but did not eliminate renovation demand.

What to notice: The branch that mattered was customer mix and project quality, not just transaction volume.

So what: For housing-linked names, top-line pressure can coexist with tradable earnings resilience.

Finding 1 — The “revenue miss + EPS beat” pattern is becoming a regime, not an exception

Home Depot’s result looked similar to the recent Walmart setup: the market tolerated a light top line when profitability and operating quality held up better than feared. In this tape, investors are rewarding companies that preserve earnings power through mix discipline, shrink control, supply-chain efficiency, and selective pricing.

That is exactly why premarket price action was positive despite the revenue miss. The market did not read the quarter as “demand collapse.” It read it as “demand normalizing, but not breaking,” with better execution than the consensus implied.

Table 2 — Expectation vs actual: where the surprise really came from

The critical number was comps: a +0.8 percentage-point delta versus expectation. That gap forced a repricing of the “consumer is rolling over everywhere” narrative.

Finding 2 — The comp reversal supports a K-shaped spending map

A +0.4% comp print does not mean the U.S. consumer is uniformly strong. It means aggregate demand remained better in specific pockets than the consensus expected. The most useful read-through is K-shaped behavior: discretionary pressure at the lower end, but durability in repair, maintenance, and selected project categories tied to homeowners who are rate-locked and staying put.

This is also why sector context matters: consumer discretionary led on the day even as macro chatter stayed cautious. Traders who only tracked macro headwinds missed the cross-current that equity markets were actually pricing.

Visual 2 — K-shaped consumer signal after HD earnings

xychart-beta
    title "Expectation gap by metric (actual minus consensus)"
    x-axis [Revenue, EPS, Comps]
    y-axis "Surprise" -0.2 --> 1
    bar [-0.1, 0.17, 0.8]

Caption: Top line disappointed slightly, but profitability and in-store demand surprised up.

What to notice: Comps delivered the largest positive surprise, overpowering the minor revenue miss.

So what: In this regime, traders should rank surprise quality, not only sign.

Our prior housing thesis still holds: one-variable bearish calls missed that mix, margins, and comp surprise could dominate top-line anxiety. We now refine the framework by using comp surprise versus consensus as a first-pass catalyst-strength filter for housing retail.

Action Checklist — How to trade this type of “mixed beat” setup

• Verify the event clock first: Home Depot reported Tuesday, February 24, 2026.
• Separate top-line surprise from quality surprise (EPS/comps/margin mix).
• Compare first-session move to sector ETFs before chasing single-name momentum.
• Track whether post-earnings bids are broad-based or short-covering-driven.
• Use comp surprise delta as a position-sizing input for next housing retail prints.
• Demand explicit guidance evidence before extending a one-day reaction into a multi-week thesis.
• Keep K-shaped consumer assumptions dynamic; do not generalize from one retailer.
• Predefine invalidation: if relative strength fails within 2–3 sessions, reduce exposure.

Evidence Block

• Influencer sample (N=42): Public X, YouTube, Substack, and podcast-linked calls explicitly discussing HD earnings direction between 2026-02-10 and 2026-02-24 (U.S. premarket cutoff).
• Primary event timeframe: Home Depot fiscal Q4 release and immediate reaction window (premarket through first regular U.S. session after report).
• Baseline: Sell-side consensus for revenue, adjusted EPS, and comps snapshot as of report morning (8:00 ET).
• Headline number definition: “69% called EPS beat” = share of sampled calls explicitly stating EPS would exceed consensus.
• Assumptions: U.S. cash equity execution, no options overlay in performance interpretation, no after-hours slippage adjustment.
• Limitations: Public influencer sampling may overweight larger accounts and English-language channels.
• Use case: Educational market-structure analysis, not personalized investment advice.

References

1. Home Depot investor relations earnings release and webcast materials (Q4 FY2025 reported Tuesday, February 24, 2026). https://ir.homedepot.com/
2. Consensus and earnings calendar snapshots for HD. https://www.nasdaq.com/market-activity/stocks/hd/earnings
3. U.S. housing turnover data (existing home sales). https://www.nar.realtor/research-and-statistics
4. Freddie Mac mortgage rate series. https://www.freddiemac.com/pmms
5. Consumer discretionary sector performance context. https://www.sectorspdrs.com/