Comparables

How EQUIRE surfaces sold (CMBS) vs asking (listings) comps for a deal, and exactly how each comparable's match score is calculated.

The Comparables tab (under Market Research on a deal) shows two lanes of evidence for the subject property side by side:

Sold — CMBS: transacted comps from securitized deals (SEC EDGAR ABS‑EE filings) — i.e. what properties actually sold for.
Asking — Listings: active broker listings from EQUIRE's global indexed inventory — i.e. what comparable properties are currently asking.

Each lane shows its median cap rate and price per square foot, and the header surfaces the asking‑vs‑sold cap spread (asking median − sold median, in basis points) so you can see at a glance whether the market is asking above or below where comparable deals traded.

Click any comparable's name to open a detail popup with everything EQUIRE has on it — pricing, size, NOI, occupancy, parties, provenance, the source listing link, and the full match‑score breakdown. Use Pin to add a comp to the deal's Comparable Sales deliverable.

How the comparable score is calculated

Comps are matched in two stages. Both are deterministic — there is no AI or black‑box similarity model, so every score is explainable.

Stage 1 — candidate selection

Before scoring, each lane pulls candidates that already share the subject's geography and property type:

Sold (CMBS) is anchored to the subject's metro (CBSA, falling back to state) and filtered to the subject's canonical property type.
Asking (Listings) is anchored to the subject's state and filtered to the same canonical property type (only priced for‑sale listings qualify).

Stage 2 — the 0–100 match score

Every candidate is scored against the subject. The total (the Match chip in the table) is the sum of five weighted factors:

Factor	Max	How it scores
Location	25	same city 25 · same state 15 · otherwise 5
Size (SF)	25	within 10% 25 · within 25% 20 · within 50% 12 · otherwise 5
Type	20	same property type 20 · otherwise 3
Age	15	within 5 yrs 15 · within 10 yrs 10 · within 20 yrs 5 · otherwise 2
Price ($/SF)	15	within 15% 15 · within 30% 10 · within 50% 5 · otherwise 2

Lanes are sorted by total score, duplicates are removed, and the top comps are shown. The per‑factor values appear in each comp's detail popup.

When a factor has no data

A factor whose inputs are missing scores a neutral default (not zero), so it neither helps nor hurts the match:

Location 10 · Size 12 · Type 10 · Age 7 · Price 7

This is why the score is only as discriminating as the subject's known attributes. A deal that has a city, state, and property type but no building size, year built, or contract price will see most comps cluster at a similar score (location + type carry the result). Once the deal carries size, year built, and price, the size/age/price factors engage and the scores spread out — a 1.2M‑SF tower no longer ties a 40k‑SF building.

Notes and limits

Geography is metro/state, not radius. Same‑metro lifts the Location factor to its max; there is no true distance‑weighted proximity yet.
The Type factor is effectively pass/fail (20 for a match, 3 otherwise) — there is no partial credit for adjacent types such as office vs. medical office.
Cap rates throughout the Comparables surface are stored and displayed as decimal fractions (6.5% = 0.065).