Taman Segambut Damai

51200 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Property Transactions

4 subsales grouped by size · 2-Sty Terrace →

Median
RM 465,000
PSF
RM 513
Price Size
Period
transactions middle 50% (P25–P75)
750 sqft
2-Sty Terrace
RM 550,000
Jalan. 6/60B
764 sqft · RM 720 PSF
800 sqft
2-Sty Terrace
RM 430,000
2/60B
797 sqft · RM 540 PSF
RM 388,000
Jalan 7/60B
797 sqft · RM 487 PSF
1,950 sqft
2-Sty Shop
RM 500,000
Jalan 1/60B
1,959 sqft · RM 255 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM 430,000

RM 540 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 subsale transactions in 2022, with a median price of RM 465K and a median price per square foot (PSF) of RM 513.

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 RM 465K, with most transactions falling within a stable range of RM 403K to RM 527K, and a typical market range of RM 410K to RM 520K.

Most transactions involved 2 - 2 1/2 storey terraced, though some variety exists in the market.

Price per square foot shows a median of RM 513, though individual units vary from RM 348 to RM 679 in the core range. The broader market spans RM 440.98 to RM 585.98, indicating diverse property characteristics. A wider spread (IQR: RM 145.00) and deviation (MAD: RM 166) indicate significant PSF variations, likely due to diverse property types or conditions.

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.