Vistana Condo

No. 32, Jalan Taiping, Off, Jalan Pahang, Titiwangsa Sentral, 50400 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

4 subsales grouped by size

Median
RM527,500
PSF
RM393
Price Size
Period
transactions middle 50% (P25–P75)
1,000 sqft
Condo
RM380,000
Level 7
1,023 sqft · RM372 PSF
1,050 sqft
Condo
RM550,000
Level 2
1,066 sqft · RM516 PSF
1,400 sqft
Condo
RM505,000
Level 8
1,378 sqft · RM367 PSF
RM570,000
Level 16
1,378 sqft · RM414 PSF
Legend Recent Highest Price Highest PSF

Selling in Vistana Condo? Homes here sold for a median of RM527,500.

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Market Snapshot

Residential

RM527,500

RM393 psf

Median transaction price

Vistana Condo
© OpenStreetMap · CARTO

No. 32, Jalan Taiping, Off, Jalan Pahang, Titiwangsa Sentral, 50400 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Vistana Condo in Kuala Lumpur, Kuala Lumpur recorded 4 subsale transactions in 2024, with a median price of RM528K and a median price per square foot (PSF) of RM393.

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 RM528K, with most transactions falling within a stable range of RM454K to RM570K, and a typical market range of RM490K to RM565K.

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

The median PSF stands at RM393, with core pricing between RM333 and RM453. Market pricing typically extends from RM360.66 to RM424.66, reflecting moderate variation in unit pricing. The spread of RM64.00 (IQR) and deviation of RM60 (MAD) suggest moderate price variations reflecting different property features.

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.