Segambut Industrial Area

Perdana Botanical Gardens, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Property Transactions

2 subsales grouped by size

Median
RM2,950,000
PSF
RM578
Price Size
Period
transactions middle 50% (P25–P75)
2,500 sqft
Terrace Factory
RM1,900,000
Jalan 2/57B
2,519 sqft · RM754 PSF
9,950 sqft
Factory
RM4,000,000
Jalan Segambut Pusat
9,955 sqft · RM402 PSF
Legend Recent Highest Price Highest PSF

Selling in Segambut Industrial Area? Homes here sold for a median of RM2,950,000.

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Market Snapshot

Commercial

RM2,950,000

RM578 psf

Median transaction price

Segambut Industrial Area
© OpenStreetMap · CARTO

Perdana Botanical Gardens, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Segambut Industrial Area in Kuala Lumpur, Kuala Lumpur recorded 2 subsale transactions in 2023, with a median price of RM2.95 million and a median price per square foot (PSF) of RM578.

This area consists exclusively of commercial properties, with no residential listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM2.95 million, with most transactions falling within a stable range of RM1.90 million to RM4.00 million, and a typical market range of RM1.90 million to RM4.00 million.

Most transactions involved terraced factory/warehouse, though some variety exists in the market.

Price per square foot shows a median of RM578, though individual units vary from RM402 to RM754 in the core range. The broader market spans RM530.08 to RM626.08, indicating diverse property characteristics. A wider spread (IQR: RM96.00) and deviation (MAD: RM176) indicate significant PSF variations, likely due to diverse property types or conditions.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.