Taman Wellesley (Bw/S.2)

Wellesley Residence, Kampung Bagan Dalam, 12100 Butterworth, Pulau Pinang, Malaysia

Property Transactions

1 subsales grouped by size

Price Size
Period
transactions middle 50% (P25–P75)
2,750 sqft
2-Sty Terrace
RM520,000
Jalan Mengkuang
2,745 sqft · RM189 PSF
Legend Recent Highest Price Highest PSF

Selling in Taman Wellesley (Bw/S.2)? Homes here sold for a median of RM520,000.

Free to list, about two minutes, and the buyers reading this page will see it.

List your property free

Posts about Taman Wellesley (Bw/S.2)

What’s happening in Taman Wellesley (Bw/S.2)?

No posts about Taman Wellesley (Bw/S.2) yet. Be the first to share what’s happening here.

Taman Wellesley (Bw/S.2)
© OpenStreetMap · CARTO

Wellesley Residence, Kampung Bagan Dalam, 12100 Butterworth, Pulau Pinang, Malaysia

Maps

Taman Wellesley (Bw/S.2) in Seberang Perai Utara, Penang recorded 1 Double Storey Terraced properties subsale transactions between 2021 and 2026, with a median price of RM520K and a median price per square foot (PSF) of RM189.

This area contains both residential and commercial properties. View 1 residential properties or 1 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat.

Within the Double Storey Terraced category, 2 - 2 1/2 storey terraced dominated the market, with moderate diversity in property types available.

For price per square foot, the median is RM189, with most transactions between RM189 and RM189. The usual range is RM42.70 to RM336.20, showing that most units are priced quite close to each other. With an IQR of RM293.50 and MAD of RM0, 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.