Taman Segambut Damai

51200 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Property Transactions

4 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
1,650 sqft
2-Sty Shop
RM500,000
Jalan 1/60B
1,658 sqft · RM302 PSF
1,950 sqft
2-Sty Shop
RM500,000
Jalan 1/60B
1,959 sqft · RM255 PSF
2,100 sqft
2-Sty Shop
RM639,000
Jalan 1/60B
2,120 sqft · RM301 PSF
RM498,000
Jalan 1/60B
2,120 sqft · RM235 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Segambut Damai? Homes here sold for a median of RM500,000.

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Market Snapshot

Residential

RM450,000

RM568 psf

Median transaction price

Taman Segambut Damai
© OpenStreetMap · CARTO

Taman Segambut Damai, 51200 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Maps

Taman Segambut Damai in Kuala Lumpur, Kuala Lumpur recorded 4 Double Storey Shop properties subsale transactions between 2021 and 2026, with a median price of RM500K and a median price per square foot (PSF) of RM278.

This area contains both residential and commercial properties. View 10 residential properties or 4 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM500K, with most transactions falling within a stable range of RM498K to RM560K, and a typical market range of RM498K to RM555K.

Within the Double Storey Shop category, 2 - 2 1/2 storey terraced dominated the market, though some variety exists in the market.

The median PSF stands at RM278, with core pricing between RM249 and RM307. Market pricing typically extends from RM205.79 to RM350.79, reflecting moderate variation in unit pricing. With an IQR of RM145.00 and MAD of RM29, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.