Updated on Rewritten with current SQM navigation, clearer metric definitions and a practical cross-check workflow; unsupported universal thresholds removed.
SQM Research Guide: Vacancy, Listings and Asking Prices

Joey Don
Co-Founder & CEO

General information only — not personal financial, tax, credit, or legal advice
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SQM Research’s free property tools help you investigate rental availability, advertised stock, vendor expectations and auction activity. Read these signals together, with the same geography and reference period where possible. No vacancy threshold or chart combination guarantees that a particular property is a good investment.1
Yan’s recent SQM video says, translated from Chinese: do not let yesterday’s scorecard make today’s decision. Timely evidence matters, but timeliness is not the same thing as a reliable three-month price forecast. This revision replaces the earlier article’s fixed market thresholds with a reproducible research workflow.
Start from the current property menu
Open SQM’s property portal and choose the required tool from its free-data menu. The portal currently links to vacancy rates, total property listings, asking prices, asking rents and auction results. Older saved PHP links may not behave like the current navigation.1
Enter the relevant location and preserve the chart’s unit, geography, date and dwelling category. If one chart is for a postcode and another is for a capital city, do not present their relationship as a suburb-level result. When a chart fails to load, use the publisher’s current navigation rather than substituting an unrelated statistic.
Rental vacancy: investigate availability and persistence
Use the vacancy chart to examine the level and direction of the publisher’s rental-availability measure.2 Read its method and look across a meaningful period. Check whether the local rental stock is small enough for a handful of listings to cause a noticeable movement.
A low rate can justify further investigation of leasing conditions. It does not tell you that your proposed rent is achievable, that every property type is scarce or that buying at any price is sensible. Inspect comparable rentals and ask for achieved lease evidence.
Total listings: count the actual competition
The listings tool addresses advertised stock for sale.3 Compare the direction and composition with the homes you are considering. More listings can reflect new supply, slower absorption or seasonal activity; the chart alone does not identify which explanation dominates.
Create a dated shortlist of competing properties and follow price changes and outcomes. Separate newly advertised homes from properties that have remained available. Do not infer mortgage stress or an owner’s loan-to-value ratio from total listings. Those are different measures requiring different evidence.
Asking prices: read the seller’s position
An asking-price series measures advertised expectations, not the amount every home actually sells for. SQM publishes an explanation of its approach.45 Compare houses with houses and units with units, and retain the selected location.
If expectations rise while competing stock also increases, investigate the individual listings. Vendors may be testing higher prices without completing sales. If asking prices fall, check whether the sample, mix or specific properties changed. Use completed comparable transactions before setting an offer.
Auction clearance: check the denominator
SQM’s auction page displays its calculation and records categories such as sold prior, sold at auction, rescheduled and withdrawn.6 Another provider may count or update outcomes differently. A difference between two reported clearance rates is not necessarily an error.
Check the scheduled sample and reporting date. A small local sample can be volatile, and many properties sell outside auctions. Use the auction series as additional context rather than a universal boundary between a buyer’s and seller’s market.
Join market signals with households and supply
Household and dwelling information describes the underlying stock and potential housing needs; it is not the same as the current rental-vacancy measure.7 Construction data then helps separate approved, started and completed supply.8
Write a short evidence note containing the location, three relevant chart observations, comparable properties and an alternative explanation. If the conclusion depends on one chart, investigate the missing side. Do not invent a confidence score simply because a dashboard can display one.
For the full sequence, read our .id Community workflow, population-per-dwelling guide, regional jobs checks and cash-flow ledger. Use suburb statistics for context and title due diligence before buying the specific property.
Questions buyers ask
Which SQM charts should a buyer start with?
Start with rental vacancy, total property listings and asking prices for the relevant location. Add auction results where the sample and sale method are relevant, then verify individual comparable properties.
How should buyers interpret a low vacancy rate?
No. The rate does not establish affordability, your property’s condition, competing supply or the rent a particular household will pay.
Are asking prices completed sale prices?
No. They describe advertised expectations. Use actual comparable sales and their dates when forming a purchase price opinion.
Source videos and verification scope
This article develops practical questions raised in the published videos below and checks them against the sources cited here. Case prices, forecasts and broad claims in a video do not establish the result for another property.
References
- [1]SQM Research: current property data tools
- [2]SQM Research: residential vacancy rates tool
- [3]SQM Research: total property listings tool
- [4]SQM Research: asking property prices
- [5]SQM Research: asking-price methodology (publisher document)
- [6]SQM Research: auction results and stated calculation
- [7]ABS: Housing, 2021 Census
- [8]ABS: Building Activity, March 2026
About the author

Joey Don
Co-Founder & CEO
With 200+ property transactions across Melbourne and a background in IT and institutional finance, Joey focuses on data-driven property selection in the outer southeast and eastern suburbs.