Self-Storage REIT Valuation Multiples Compared: Where the Numbers Live

A valuation multiple is a price numerator divided by a fundamental denominator - earnings, book value, sales or EBITDA - so a cross-ticker comparison needs three inputs per name: a current market price, a set of standardized fundamentals, and a common as-of date. For the four core listed self-storage REITs (PSA, EXR, CUBE, NSA), all three exist in cataloged sources.

The market-numerator layer is Yahoo Finance Self-Storage REIT Quotes (PSA, EXR and peers): each quote page pairs a quote block with statistics sections carrying trailing and forward P/E, PEG ratio, price/sales (ttm), price/book (mrq), EV/revenue, EV/EBITDA and a 1-year analyst target estimate. The fundamental-denominator layer is SEC EDGAR Full-Text Search & Filings, whose XBRL companyfacts JSON returns audited revenue, income and book figures per registrant - Public Storage's file alone carries 454 us-gaap concepts in about 3 MB under CIK 1393311. The sector-context layer is the Nareit Self-Storage REIT Sector Hub, which stamps the whole cohort to one date: its FTSE overview block is sourced as of 7/31/2026 and its company roster prices as of the 08/21/2026 close.

Datadory catalogs this slice at 18 pooled records, of which only 4 are storage-native; the other 7 primary entries are semiconductor datasets caught by a tagging artifact and excluded from any valuation work. Of the 11 primary records, the mean quality score runs 8.27 of 10 against 7.81 catalog-wide.

One caution from the roster itself: one-year returns in the panel ran from CUBE's 8.87% up to NSA's 48.45% as of 08/21/2026, a spread wide enough that any multiple computed on trailing fundamentals will embed very different momentum assumptions per name.

Each source owns a different slice of the comparison, and the table is the working map:

Two structural notes matter when you use it. First, occupancy and same-store metrics for storage REITs are not consistently tagged in us-gaap XBRL - they live in MD&A text and exhibits, so the denominator side of an EV/EBITDA-style screen needs filing-text parsing beyond companyfacts. Second, the sector aggregates from Nareit's T-Tracker are cash-flow panels, not multiples: they give you the FFO ($1,448 million in Q1 2026) and NOI ($1,794 million) base that a sector-level price/FFO calculation would divide by, while Yahoo supplies the price side per ticker.

The walkthrough produces one dated row per ticker with six multiples and one consensus target:

1. Pin the universe and date. Take PSA, EXR, CUBE and NSA from the Nareit roster and record the close date you snap prices at (the roster itself stamps 08/21/2026). A multiples table is only comparable if every numerator shares one timestamp.

1. Pull the ratio block per ticker. Each Yahoo Finance quote page publishes the whole set in its statistics section: PE Ratio (TTM), Trailing P/E, Forward P/E, PEG Ratio (5yr expected), Price/Sales (ttm), Price/Book (mrq), Enterprise Value/Revenue, Enterprise Value/EBITDA and 1y Target Est - nine fields per name, enough for a six-multiple screen plus one consensus column.

1. Compute the derived rows yourself. Divide Yahoo's Enterprise Value by EDGAR's trailing EBITDA-equivalents where you want a number independent of Yahoo's own arithmetic, and record both versions. Where the two disagree, the XBRL figure is the audited one.

1. Add the sector anchor line. Append the FTSE overview values - 4 index constituents, 4.08% dividend yield, 23.49% YTD total return as of 7/31/2026 - so each ticker's yield can be read against the sector aggregate rather than in isolation.

1. Overlay supply signals. Flag names with heavy development exposure using Inside Self-Storage's monthly development-and-zoning roundup (the August 2026 edition published 2026-08-20) - new supply compresses future NOI growth, which is the growth assumption inside every forward multiple in the table.

That is why the demand side belongs next to the screen. U.S. Census Bureau Data API - CBP / Economic Census / Wholesale Trade carries County Business Patterns establishment counts by county across roughly 1,800 Census datasets (CBP back to 1986), quantifying business density in storage trade areas - the demand context Nareit and EDGAR series do not carry. Its sibling entry, U.S. Census County Business Patterns - Automobile Dealers Establishments, applies the same program to automobile-dealer counts as a local consumer-activity proxy.

For rate-sensitivity framing, the Nareit REIT Indexes and Market Performance Landing publishes index-level performance series that test whether storage's 23.49% YTD run is sector-specific or part of a wider listed-REIT move - useful before crediting management teams for multiple expansion.

Yes, for the denominator side, and the audit trail is the reason to bother. EDGAR companyfacts stamps every fact with start/end periods and form type, so a screen can compute as-of multiples without look-ahead, reaching roughly 2009 onward per registrant - about 3 MB and 454 us-gaap concepts for Public Storage under CIK 1393311. Where a vendor ratio and a filed-figure ratio disagree, the filed figure wins, because it is the audited input.

Two limits shape the rebuild. Occupancy and same-store inputs sit in MD&A text rather than us-gaap tags, so those columns need filing-text reading before they enter the table; and the sector aggregates from Nareit's hub are cash-flow panels rather than multiples, best used as the denominator-side sanity check behind every per-ticker number. Depth holds up: the 11 primary records average 8.27 of 10 on Datadory's quality rubric versus 7.81 catalog-wide.

Start with the self-storage-reits data guide, the pillar post mapping all 18 pooled records in the industry - 11 primary plus 7 related - and showing where valuation ratios sit beside T-Tracker FFO panels, ISS transaction roundups and Census trade-area counts. Then take the screen further: the best self-storage-reits datasets ranking scores every record in the slice, and investors-quants use cases shows how point-in-time multiples feed factor models. The head-to-head of the two market-facing sources lives at Nareit Self-Storage REIT Sector Hub vs Yahoo Finance Self-Storage REIT Quotes (PSA, EXR and peers), and the self-storage-reits data hub collects the rest of the industry's pages.