Sungai Penchala
60000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
60000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
| Road | Price | PSF | Size | Date | Type |
|---|
|
Jalan Penchala Indah 2 (Jalan 2/71C)
|
RM740,000
|
RM438
|
1,690 sqft
|
|
|
Off Jalan Sungai Penchala
|
RM1,750,000
|
RM429
|
4,080 sqft
|
|
|
Off Jalan Sungai Penchala
|
RM1,750,000
|
RM417
|
4,198 sqft
|
|
|
Jalan Sungaipechala 12 (Puncak Penchala)
|
RM1,400,000
|
RM297
|
4,715 sqft
|
|
|
Jalan Sungai. Penchala 2
|
RM4,500,000
|
RM387
|
11,614 sqft
|
|
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Sungai Penchala
PSF median price per sq ft · 12m its change over the past 12 months
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Market Snapshot
ResidentialRM1,750,000
RM417 psfMedian transaction price
Sungai Penchala, 60000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
MapsSungai Penchala in Kuala Lumpur, Kuala Lumpur recorded 5 subsale transactions between 2021 and 2026, with a median price of RM1.75 million and a median price per square foot (PSF) of RM417.
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 RM1.75 million, with most transactions falling within a stable range of RM1.40 million to RM2.10 million, and a typical market range of RM1.58 million to RM1.93 million.
Most transactions involved detached, though some variety exists in the market.
For price per square foot, the median is RM417, with most transactions between RM387 and RM447. The usual range is RM395.87 to RM437.87, showing that most units are priced quite close to each other. A typical spread (IQR) of RM42.00 and an average deviation (MAD) of RM30 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. Some price volatility exists, making thorough market research essential before transacting. Limited transaction history suggests carefully evaluating comparable sales data.