Alam Avenue-Sek.16 Shah Alam

2, Jalan Serai Wangi L 16/L, Seksyen 16, 40200 Shah Alam, Selangor, Malaysia

Property Transactions

4 subsales grouped by size

Median
RM 1,725,000
PSF
RM 410
Price Size
Period
transactions middle 50% (P25–P75)
3,950 sqft
3-Sty Shop
RM 1,370,000
Jalan Serai Wangi 16/H
3,929 sqft · RM 349 PSF
RM 1,850,000
Jalan Serai Wangi H 16/H
3,929 sqft · RM 471 PSF
4,800 sqft
3-Sty Shop
RM 2,538,000
Jalan Serai Wangi G 16/G
4,801 sqft · RM 529 PSF
RM 1,600,000
Jalan Serai Wangi G 16/G
4,801 sqft · RM 333 PSF
Legend Recent Highest Price Highest PSF

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Alam Avenue-Sek.16 Shah Alam
© OpenStreetMap · CARTO

2, Jalan Serai Wangi L 16/L, Seksyen 16, 40200 Shah Alam, Selangor, Malaysia

Maps

Alam Avenue-Sek.16 Shah Alam in Petaling, Selangor recorded 4 3-Storey Shop properties subsale transactions between 2021 and 2026, with a median price of RM 1.73 million and a median price per square foot (PSF) of RM 410.

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 RM 1.73 million, with most transactions falling within a stable range of RM 1.37 million to RM 2.16 million, and a typical market range of RM 1.49 million to RM 1.97 million.

Within the 3-Storey Shop category, 3 - 3 1/2 storey shop dominated the market, though some variety exists in the market.

Price per square foot shows a median of RM 410, though individual units vary from RM 328 to RM 492 in the core range. The broader market spans RM 238.79 to RM 580.79, indicating diverse property characteristics. The spread of RM 342.00 (IQR) and deviation of RM 82 (MAD) suggest moderate price variations reflecting different property features.

While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.