| Road | Price | PSF | Size | Date | Type |
|---|
|
Level 1
|
RM225,000
|
RM312
|
721 sqft
|
|
|
|
Level 3
|
RM200,000
|
RM277
|
721 sqft
|
|
|
Jalan Seri Putra 4/3
|
RM610,000
|
RM450
|
1,356 sqft
|
|
|
|
Jalan Seri Putra 4/3
|
RM500,000
|
RM369
|
1,356 sqft
|
|
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Auction Properties
1 auction properties in Bandar Seri Putra
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PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Pekan Bangi Lama
Market Snapshot
ResidentialRM360,000
RM322 psfMedian transaction price
Does BANDAR SERI PUTRA rent out well?
Gross yield, median rent and sale psf — worked out from transacted prices and asking rents.
See the yield with PlusRM59 a month, cancel any time
Bandar Seri Putra, 43000 Kajang, Selangor, Malaysia
MapsBandar Seri Putra in Hulu Langat, Selangor recorded 5 subsale transactions between 2021 and 2026, with a median price of RM360K and a median price per square foot (PSF) of RM322.
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 RM360K, with most transactions falling within a stable range of RM220K to RM500K, and a typical market range of RM223K to RM498K.
Most transactions involved 2 - 2 1/2 storey terraced, with high diversity across multiple property types.
For price per square foot, the median is RM322, with most transactions between RM312 and RM332. The usual range is RM316.59 to RM326.59, showing that most units are priced quite close to each other. A typical spread (IQR) of RM10.00 and an average deviation (MAD) of RM10 indicate a highly stable PSF trend across properties.
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.