PropKaki

Methodology

How PropKaki sources and calculates the Singapore property figures across our project, MRT, school and town pages — and the limits we're upfront about.

Where the data comes from

  • Transactions: URA caveat data for private residential sales — the official record lodged on every transaction. We surface recent caveats (trailing 12 months) and counts.
  • Listings:live for-sale and for-rent listings aggregated across PropertyGuru, 99.co and EdgeProp, de-duplicated so the same unit isn't counted twice.
  • Project facts: developer, tenure, TOP/completion year, total units and blocks — public development facts.
  • Locations: MRT/LRT stations and schools with their coordinates and (for schools) level, used for the proximity pages.

How the figures are calculated

  • PSF = price ÷ strata floor area. Median is the middle value (less skewed by outliers than an average).
  • Recent vs all-time: we lead with the recentmedian (trailing ~12 months) because a blended all-time median understates today's price for an appreciating project.
  • “Within 1 km of a school” uses the straight-line (great-circle) distance — which is exactly how MOE defines the 1 km boundary for Primary 1 registration priority. P1 priority is claimed for primary schools only; for secondary schools and JCs, 1 km is framed as proximity, since admission there is not distance-based.
  • “Near an MRT” = condo projects within 1.2 km straight-line of the station.
  • Gross rental yield = annualised median asking rent ÷ the median price, shown only when both are available and the result is plausible. It is indicative, before costs.
  • Cost-to-ownfigures (stamp duty, monthly instalment, income required) use current Buyer's/Additional Buyer's Stamp Duty tiers and TDSR rules at the stress-test rate.
  • Remaining leaseis derived from the tenure commencement/completion year and shown as an approximation (“≈ N years”), not an exact figure.

What we're honest about

  • Counts are exact; some medians are withheld. When a location has more than ~1,000 listings or transactions, the median is computed over a sample that can be biased — so we show the exact count but suppress that median rather than publish a skewed number. Most locations are well under that threshold.
  • Listing figures exclude new-launch placeholder prices and room rentals, to match what a buyer would actually shortlist.
  • Thin pages aren't indexed. A location or project with fewer than three projects / transactions is shown for visitors but marked noindex— we don't manufacture pages where there's no real data.
  • We don't have unit-level stack/facing/view, new-launch balance units, maintenance (MCST) fees, exact HDB grant amounts, or live mortgage package rates — and we say so rather than guess.

Freshness

Figures are re-aggregated from the latest data each reporting period. Data-dependent pages show an “as of” / “last updated” date and carry a machine-readable dateModified so the visible and structured freshness signals agree. Transacted figures cover the trailing 12 months to the stated month.

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