Greenview Apt

Green View Apartment, Taman Pusat Kepong, 52000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

7 subsales found

Median
RM210,000
PSF
RM249
Price Size
Period
transactions middle 50% (P25–P75)
RM187,000
Level 1
855 sqft RM219 PSF
RM220,000
Level 3
855 sqft RM257 PSF
RM178,000
Level 1
735 sqft RM242 PSF
RM190,000
Level 2
855 sqft RM222 PSF
RM210,000
Level 3
735 sqft RM286 PSF
RM230,000
Level 2
855 sqft RM269 PSF
RM213,000
Level 4
855 sqft RM249 PSF
Legend Recent Highest Price Highest PSF

Selling in Greenview Apt? Homes here sold for a median of RM210,000.

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Market Snapshot

Residential

RM210,000

RM249 psf

Median transaction price

Greenview Apt
© OpenStreetMap · CARTO

Green View Apartment, Taman Pusat Kepong, 52000 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Greenview Apt in Kuala Lumpur, Kuala Lumpur recorded 7 subsale transactions in 2024, with a median price of RM210K and a median price per square foot (PSF) of RM249.

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 RM210K, with most transactions falling within a stable range of RM192K to RM228K, and a typical market range of RM194K to RM226K.

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

For price per square foot, the median is RM249, with most transactions between RM227 and RM272. The usual range is RM231.22 to RM267.22, showing that most units are priced quite close to each other. A typical spread (IQR) of RM36.00 and an average deviation (MAD) of RM22 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.