Sek. 23, Shah Alam

Seksyen 23, 40300 Shah Alam, Selangor, Malaysia

Property Transactions

2 subsales grouped by size

Median
RM 4,700,000
PSF
RM 408
Price Size
Period
transactions middle 50% (P25–P75)
4,450 sqft
3-Sty Shop
RM 1,800,000
Pelabur A 23/A
4,456 sqft · RM 404 PSF
18,450 sqft
Semi-D Factory
RM 7,600,000
Jalan Ringgit 23/11
18,439 sqft · RM 412 PSF
Legend Recent Highest Price Highest PSF

Posts about Sek. 23, Shah Alam

What’s happening in Sek. 23, Shah Alam?

No posts about Sek. 23, Shah Alam yet. Be the first to share what’s happening here.

Property News

More property news →

Market Snapshot

Commercial

RM 4,700,000

RM 408 psf

Median transaction price

Sek. 23, Shah Alam
© OpenStreetMap · CARTO

Seksyen 23, 40300 Shah Alam, Selangor, Malaysia

Maps

Sek. 23, Shah Alam in Petaling, Selangor recorded 2 subsale transactions in 2025, with a median price of RM 4.70 million and a median price per square foot (PSF) of RM 408.

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 4.70 million, with most transactions falling within a stable range of RM 1.80 million to RM 7.60 million, and a typical market range of RM 2.52 million to RM 6.88 million.

Most transactions involved semi-detached factory/warehouse, with high diversity across multiple property types.

For price per square foot, the median is RM 408, with most transactions between RM 404 and RM 412. The usual range is RM 197.33 to RM 618.59, showing that most units are priced quite close to each other. With an IQR of RM 421.25 and MAD of RM 4, the PSF demonstrates reasonable consistency across the market.

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.