Sri Kenny Condo

Jalan Tun Ismail, Kuala Lumpur, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

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Pet friendly condo. 10mins to 1Utama

From
RM600K
Size
800 sqft

Property Transactions

6 subsales grouped by size

Median
RM1,425,000
PSF
RM653
Period
transactions middle 50% (P25–P75)
1,900 sqft
Condo
RM1,200,000
Level 4
1,905 sqft · RM630 PSF
2,000 sqft
Condo
RM1,300,000
Level 3
1,991 sqft · RM653 PSF
2,200 sqft
Condo
RM1,760,000
Level 5
2,196 sqft · RM802 PSF
2,400 sqft
Condo
RM1,430,000
Level 3
2,400 sqft · RM596 PSF
RM1,420,000
Level 2
2,400 sqft · RM592 PSF
RM1,980,000
Level 5
2,400 sqft · RM825 PSF
Legend Recent Highest Price Highest PSF

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Sri Kenny Condo
© OpenStreetMap · CARTO

Sri Kenny Condo, Jalan Tun Ismail, Kuala Lumpur, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Sri Kenny Condo in Kuala Lumpur, Kuala Lumpur recorded 6 subsale transactions between 2021 and 2026, with a median price of RM1.43 million and a median price per square foot (PSF) of RM653.

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 RM1.43 million, with most transactions falling within a stable range of RM1.25 million to RM1.60 million, and a typical market range of RM1.25 million to RM1.60 million.

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

For price per square foot, the median is RM653, with most transactions between RM605 and RM700. The usual range is RM572.71 to RM732.96, showing that most units are priced quite close to each other. With an IQR of RM160.25 and MAD of RM48, the PSF demonstrates reasonable consistency across the market.

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.