One Foresta

11900 Bayan Lepas, Penang, Malaysia

Property Transactions

18 subsales grouped by size

Median
RM 452,500
PSF
RM 498
Price Size
Period
transactions middle 50% (P25–P75)
900 sqft
Condo
RM 450,000
Level 23
904 sqft · RM 498 PSF
RM 455,000
Level 9
904 sqft · RM 503 PSF
RM 450,000
Level 10
904 sqft · RM 498 PSF
RM 415,000
Level 7
904 sqft · RM 459 PSF
RM 460,000
Level 10
904 sqft · RM 509 PSF
RM 480,000
Level 27
904 sqft · RM 531 PSF
+10 more
1,000 sqft
Condo
RM 455,000
Level 32
1,001 sqft · RM 455 PSF
1,050 sqft
Condo
RM 805,000
Level G
1,055 sqft · RM 763 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM 452,500

RM 498 psf

Median transaction price

Average

Rental Yield Data

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One Foresta
© OpenStreetMap · CARTO

11900 Bayan Lepas, Penang, Malaysia

Maps
List AI Investment Analysis. High-Density Affordable Housing Delivering Robust Capital Gains Despite Supply Overshang

One Foresta in Barat Daya, Penang recorded 18 subsale transactions in 2024, with a median price of RM 453K and a median price per square foot (PSF) of RM 498.

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 RM 453K, with most transactions falling within a stable range of RM 392K to RM 541K, and a typical market range of RM 428K to RM 478K.

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

The median PSF stands at RM 498, with core pricing between RM 423 and RM 572. Market pricing typically extends from RM 472.69 to RM 522.69, reflecting moderate variation in unit pricing. With an IQR of RM 50.00 and MAD of RM 75, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.