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SGPropertyIntel
Strata Terrace99-yearOutside Central RegionInvestment score 70

Mont Timah

BUKIT WAY · D21

Median PSF · 12m

S$934

Median price · 12m

S$4.29M

Latest sale

S$4.30M

Aug 2026

1-year change

+7.4%

Sales · 12m

4

12 all time

Gross yield

3.92%

1 leases

Price history

How this development has traded

Median transacted price and price per square foot by quarter, from every sale on record here.

Change over window
+14.0%
Annualised
+5.4%
Transactions
12
1 year
+7.4%
3 years p.a.
5 years p.a.
Median size
4,564 sqft

Against the neighbourhood

How it compares within D21

Upper Bukit Timah, Clementi Park, Ulu Pandan. All figures are medians over the last 12 months for private homes in this district.

District analytics
MeasureMont TimahD21 medianDifference
Median PSFS$934S$1,833-49.0%
Median priceS$4.29MS$1.99M+115.3%
Gross rental yield3.92%3.74%+0.2 pts
1-year price change+7.4%+8.7%-1.2 pts

This development trades about 49% below the D21 median price per square foot.

Rental

Rent and yield

From URA private residential rental contracts.

Median monthly rent

S$14,000

Contracts · 12m

1

Implied annual rent

S$168K

Gross yield

3.92%

Unit typeContractsMedian rent
All units1S$14,000

Investment analysis

Investment score 70 / 100

Each component is a percentile rank against every other private development in the database. This is an analytical indicator, not financial advice.

70/100

100% of the scoring weight measurable

Every bar is a percentile rank, so 70 means this development sits above roughly 70% of its peers on that factor. Factors we cannot measure are excluded and the remaining weights are rebalanced, rather than scored as zero.

  • Valuationweight 22%98

    How its median price per square foot compares with its own district.

  • Price momentumweight 18%84

    Three-year annualised change in median PSF, or one year where three is unavailable.

  • Liquidityweight 15%82

    Transactions in the last 12 months — how easily it trades.

  • Rental yieldweight 20%76

    Gross yield against every other development in its segment.

  • Locationweight 15%25

    Distance to the nearest rail station, plus schools within 1 km. Nearest is Beauty World MRT at 680 m.

  • Supply riskweight 10%23

    Upcoming units recorded in the same district. Higher score means less competing supply.

The investment score is an analytical indicator computed from transaction and location data. It is not a recommendation, a forecast, or financial advice.

Location

Nearby amenities

Rail stations

  • Beauty World MRT680 m
  • Hume MRT1.2 km
  • Dt4 MRT1.3 km
  • King Albert Park MRT1.5 km

Schools within 2 km

  • Pei Hwa Presbyterian Primary Schoolprimary1.0 km
  • Bukit Timah Primary Schoolprimary1.6 km
  • Methodist Girls' School (Secondary)secondary (s1-s4)1.7 km

Distances are straight-line. Proximity does not determine school admission eligibility.

Supply

Upcoming competition

No upcoming supply is recorded nearby. URA pipeline data requires an API key, which is not configured, so this section may be incomplete.

The record

Transactions at this development

Browse all transactions
MonthTypePriceSizePSFFloorLease left
Aug 2026Strata TerraceS$4,300,0004,564 sqftS$942-76 yr 5 mo
Jul 2026Strata TerraceS$4,300,0004,628 sqftS$929-76 yr 6 mo
Feb 2026Strata TerraceS$4,288,0004,564 sqftS$940-76 yr 11 mo
Oct 2025Strata TerraceS$4,288,8884,628 sqftS$927-77 yr 3 mo
Jul 2025Strata TerraceS$4,038,0004,628 sqftS$872-77 yr 6 mo
Oct 2024Strata TerraceS$4,068,0004,693 sqftS$867-78 yr 3 mo
Jul 2024Strata TerraceS$3,750,0004,413 sqftS$850-78 yr 6 mo
Jun 2024Strata TerraceS$3,800,0004,413 sqftS$861-78 yr 7 mo
Nov 2023Strata TerraceS$3,980,0004,564 sqftS$872-79 yr 2 mo
Jun 2022Strata TerraceS$3,875,0004,542 sqftS$853-80 yr 7 mo
Apr 2022Strata TerraceS$4,000,0004,402 sqftS$909-80 yr 9 mo
Dec 2021Strata TerraceS$3,800,0004,628 sqftS$821-81 yr 1 mo

Important

Property values shown are estimates generated from available transaction and market data and are not official valuations. Actual transaction prices may differ. Data availability and accuracy depend on the underlying source datasets. Users should conduct their own due diligence and seek professional advice where appropriate.