Megan Setapak

Jalan Megan Setapak, Taman Megan Setapak, 53300 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

3 subsales found

Median
RM200,000
PSF
RM240

Property Type

Price Size
Period
transactions middle 50% (P25–P75)
RM200,000
Level 2
753 sqft RM265 PSF
RM205,000
Level 2
855 sqft RM240 PSF
RM160,000
Level 2
722 sqft RM222 PSF
Legend Recent Highest Price Highest PSF

Selling in Megan Setapak? Homes here sold for a median of RM200,000.

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Market Snapshot

Residential

RM200,000

RM240 psf

Median transaction price

Average

Does MEGAN SETAPAK rent out well?

Gross yield, median rent and sale psf — worked out from transacted prices and asking rents.

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Megan Setapak
© OpenStreetMap · CARTO

Jalan Megan Setapak, Taman Megan Setapak, 53300 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Maps

Megan Setapak in Kuala Lumpur, Kuala Lumpur recorded 3 subsale transactions in 2024, with a median price of RM200K and a median price per square foot (PSF) of RM240.

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 RM200K, with most transactions falling within a stable range of RM180K to RM205K, and a typical market range of RM192K to RM205K.

Most transactions involved flats, though some variety exists in the market.

For price per square foot, the median is RM240, with most transactions between RM222 and RM258. The usual range is RM223.77 to RM255.77, showing that most units are priced quite close to each other. A typical spread (IQR) of RM32.00 and an average deviation (MAD) of RM18 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.