Emerald Residence

Jln Bukit Belah, 11920 Bayan Lepas, Pulau Pinang, Malaysia

Property Transactions

3 subsales grouped by size

Median
RM 541,000
PSF
RM 483
Price Size
Period
transactions middle 50% (P25–P75)
1,100 sqft
Condo
RM 541,000
Level 17
1,119 sqft · RM 483 PSF
RM 557,000
Level 24
1,119 sqft · RM 498 PSF
RM 456,000
Level 26
1,119 sqft · RM 407 PSF
Legend Recent Highest Price Highest PSF

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Auction Properties

1 auction properties in Emerald Residence

1-B1-23A-1, EMERALD RESIDENCE, JALAN BUKIT BELAH, 11920, BAYAN LEPAS, Pulau Pinang
3.5% yield
Type Reserve Price Condominium RM 520,000
PSF Size Auction Date RM 464.70 1,119 sqft 23 Jul 2026

Market Snapshot

Residential

RM 541,000

RM 483 psf

Median transaction price

Low

Rental Yield Data

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Emerald Residence, Jln Bukit Belah, 11920 Bayan Lepas, Pulau Pinang, Malaysia

Maps

Emerald Residence in Barat Daya, Penang recorded 3 subsale transactions between 2021 and 2026, with a median price of RM 541K and a median price per square foot (PSF) of RM 483.

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 541K, with most transactions falling within a stable range of RM 497K to RM 557K, and a typical market range of RM 526K to RM 556K.

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

For price per square foot, the median is RM 483, with most transactions between RM 443 and RM 523. The usual range is RM 473.00 to RM 493.00, showing that most units are priced quite close to each other. A typical spread (IQR) of RM 20.00 and an average deviation (MAD) of RM 40 indicate a highly stable PSF trend across properties.

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.