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Mid-tier single-family prices are down 11% to 26% from peak in 15 large markets, while AI money pulled San Francisco off the list. Collateral marks have to be local now.
The Investor · Invest desk
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Wolf Richter's July tally counts 15 bigger cities and counties where prices of mid-tier single-family homes are down 11% to 26% seasonally adjusted from their own peaks, most of those peaks set in mid-2022 and two in 2024 [1]. The same run of data has San Francisco leaving the list entirely, which means anyone still underwriting or marking to a national house-price number is averaging two regimes that no longer move together [8].
The list itself is a measure of how fast this is widening. Richter raised the cut-off for July to a 11% decline from 10% "to keep the list tidy" [2], and notes that when the series started a year ago the cut-off was 8%, the list held 10 markets, and the worst decline was 22% [3]. Another five bigger cities came in at exactly 10% [4], so on last month's threshold the list would have run to 20 names [5].
Texas supplies both ends. Austin tops the table at -26% [6], while Houston is at -5% and Corpus Christi at -3% [7], a 23 point spread inside one state [19]. Dallas-Fort Worth splits down the middle: McKinney (-14%) and Fort Worth (-11%) qualify, while Frisco (-10%), Garland (-9%), Plano (-9%), Arlington (-7%) and the city of Dallas (-7%) do not [9]. Richter attributes the area's weakness to homebuilders who have to move inventory and are buying down mortgage rates, cutting price points and piling on incentives, with existing homes forced to compete [10]. That matters for comps: the recorded price and the effective price are not the same number.
California has Oakland (-24%), Hayward (-13%) and Contra Costa County (-12%) on the list [11]. San Francisco sat in fourth place a year ago at -15% and now prints -6%, which Richter puts down to money from AI companies including Anthropic being thrown around [12]. That is nine percentage points of re-inflation against its own peak in twelve months [13]. Meanwhile San Jose is at -6%, Sacramento -9%, Stockton -8%, San Diego -4% and Los Angeles -4% [14]. Oakland to San Jose is an 18 point gap across one bay [20].
Florida contributes three counties, because the well-known cities inside them are too small to qualify on their own [15], and Richter adds that Florida single-family is nowhere near as weak as the condo market, where the bottom has fallen out in a number of markets [16].
The lending arithmetic is unforgiving at the tail. A 90% LTV loan written at the 2022 peak in a market that has since given back 26% is now marked at roughly 122% of collateral value [21]. That is not a forecast, it is division. Also worth noting before anyone reconciles this to a median-price series: these are seasonally adjusted three-month averages from the Zillow Home Value Index, including off-market and for-sale-by-owner deals, and they are explicitly not median prices [17].
Watch the five markets sitting at -10%, which cross into the list on any further slippage [4]. Watch whether the cut-off has to be raised again. And watch demand: pending home sales dropped to the second lowest on record, with a record low in the West and a near-record low in the South [18]. The Texas builder response is the mechanism to track, because incentives set the clearing price for existing homes in the same submarket [10].
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Ranked by verification strength, evidence, and original report placement.
For July, the cut-off for inclusion was raised to -11% from -10% to keep the list tidy.
A year ago, when the sporadic series started, the cut-off was 8%, the list had just 10 markets on it, and the declines topped out at 22%.
According to Richter, Dallas-Fort Worth has attracted businesses, people and homebuilders for years; new homes compete with existing homes, builders have to sell them, and they are buying down mortgage rates, offering lower price points and throwing incentives at buyers, which the existing-home market feels.
San Francisco was in fourth position in July last year with a decline of 15% and came off the list this year at -6%, which Richter attributes to money from AI companies such as Anthropic being thrown around and the market going haywire.
Pending home sales dropped to the second lowest on record, plunging to a record low in the West and a near-record low in the South.
Prices of mid-tier single-family homes have dropped by 11% to 26% seasonally adjusted in 15 bigger cities and counties through July, from their respective peaks, mostly in mid-2022, but two of them in 2024.
Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Specific and sourced, but one publisher and one vendor
Every price figure is attributable to a single named vendor series (Zillow ZHVI) with a disclosed methodology — seasonally adjusted three-month averages of mid-tier single-family prices, not medians — and the article names dozens of individual cities and counties with values, which is unusually checkable. Against that: the cluster contains one source and one publisher, the underlying tables are referenced but not reproduced in the supplied text, no independent index (Case-Shiller, FHFA, local MLS) corroborates the readings, the inclusion threshold is an author-chosen screen moved between installments, and the supporting pending-sales datapoint is a self-citation.
No adoption-type events in scope
This is a housing-price measurement story. The supplied source contains no releases, deployments, benchmarks, security incidents, license changes, vendor pricing changes or usage disclosures — nothing that constitutes an adoption observation. Home-price index readings are market prices, not adoption of a product or standard, so no adoption score is inferred.
Numbers hold up; the causal stories run ahead of them
Slightly overstated. The quantitative spine — 11% to 26% declines in 15 markets, city-by-city figures, an explicit methodology — is proportionate and well specified, and the central editorial thesis that national marks conceal local dispersion is directly supported by the data shown. The overshoot is in interpretation and packaging: an 'Oh Dear' headline and 'AI money piling up knee-deep in the streets' carry causal weight that no supplied wage, hiring, liquidity or transaction data supports; the builder-incentive explanation for DFW is asserted without incentive or volume data; and the story's framing depends on a threshold the author raised himself, which mechanically flatters the 'already' urgency. The collateral-impairment implication in the cluster's dek is arithmetic illustration, not observed loan performance.
Independent outlet, reader-funded, engagement-shaped screen
The publisher is an independent single-author financial blog with no disclosed stake in the assets discussed and it names its data vendor openly, which limits commercial capture. Countervailing pressures are visible in the text: an explicit donation solicitation, a headline built on alarm ('Oh Dear... Already'), a recurring series whose inclusion threshold the author adjusts at his own discretion to keep the list 'tidy' — a choice that shapes how severe the picture looks — and cross-promotion of the publisher's own prior article as supporting evidence. These are attention- and reader-revenue incentives rather than vendor or issuer incentives.
Facts likely accurate; interpretation thinly evidenced
Moderate. The city-level price readings come from a named, widely used vendor index with a disclosed method and are internally consistent, so the descriptive core is likely accurate as reported. Confidence is capped by structural limits of the cluster: a single source and single publisher, no independent index cross-check, tables not present in the supplied text, an author-set and shifting inclusion threshold, absent volume or inventory context, and the two causal explanations (AI money in San Francisco, builder incentives in DFW) resting on assertion alone. Adoption is not assessable in this domain, removing one confirming dimension.
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1 article · August 18, 2026