Perindustrian Pdc

1, Jalan Sultan Azlan Shah, Kawasan Perindustrian Bayan Lepas, 11900 Bayan Lepas, Pulau Pinang, Malaysia

Property Transactions

4 subsales found

Median
RM7,850,000
PSF
RM305
Price Size
Period
transactions middle 50% (P25–P75)
RM1,380,000
Lintang Bayan Lepas 4
2,303 sqft RM599 PSF
RM20,900,000
Lintang Bayan Lepas
88,479 sqft RM236 PSF
RM9,500,000
Jalan Sungai Keluang Phase 1
45,165 sqft RM210 PSF
RM6,200,000
Lintang Bayan Lepas 1
16,555 sqft RM375 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Commercial

RM7,850,000

RM305 psf

Median transaction price

Perindustrian Pdc
© OpenStreetMap · CARTO

1, Jalan Sultan Azlan Shah, Kawasan Perindustrian Bayan Lepas, 11900 Bayan Lepas, Pulau Pinang, Malaysia

Maps

Perindustrian Pdc in Barat Daya, Penang recorded 4 subsale transactions in 2023, with a median price of RM7.85 million and a median price per square foot (PSF) of RM305.

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 RM7.85 million, with most transactions falling within a stable range of RM1.38 million to RM15.04 million, and a typical market range of RM1.38 million to RM16.23 million.

Most transactions involved detached factory/warehouse, with moderate diversity in property types available.

Price per square foot shows a median of RM305, though individual units vary from RM151 to RM459 in the core range. The broader market spans RM249.36 to RM361.36, indicating diverse property characteristics. A wider spread (IQR: RM112.00) and deviation (MAD: RM154) 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.