Queens Residences Q2 @ Queens Waterfront

Persiaran Bayan Indah, Bayan Indah, 11900 Bayan Lepas, Pulau Pinang, Malaysia

Property Transactions

13 subsales grouped by size

Median
RM890,000
PSF
RM937
Price Size
Period
transactions middle 50% (P25–P75)
950 sqft
Condo
RM950,000
Level 13
947 sqft · RM1,003 PSF
RM900,000
Level 21
958 sqft · RM939 PSF
RM897,000
Level 13
947 sqft · RM947 PSF
RM900,000
Level 20
947 sqft · RM950 PSF
RM1,000,000
Level 11
947 sqft · RM1,056 PSF
RM975,000
Level 23
947 sqft · RM1,029 PSF
+7 more
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM890,000

RM937 psf

Median transaction price

Average

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Queens Residences Q2 @ Queens Waterfront
© OpenStreetMap · CARTO

Persiaran Bayan Indah, Bayan Indah, 11900 Bayan Lepas, Pulau Pinang, Malaysia

Maps

Queens Residences Q2 @ Queens Waterfront in Barat Daya, Penang recorded 13 subsale transactions between 2021 and 2026, sized between 925 and 974 sqft, with a median price of RM890K and a median price per square foot (PSF) of RM937.

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

Price remained flat, and PSF growth was PSF remained flat. The median price is RM890K, with most transactions falling within a stable range of RM850K to RM934K, and a typical market range of RM850K to RM1.00 million.

Most transactions involved condominium/apartment, with minimal variety in property types.

For price per square foot, the median is RM937, with most transactions between RM888 and RM986. The usual range is RM791.05 to RM1,082.80, showing that most units are priced quite close to each other. With an IQR of RM291.75 and MAD of RM49, 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.