Millerz Square @ Okr

Megan Legasi, 357, Jln Klang Lama, 58000 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Property Transactions

2 subsales found

Median
RM1,629,500
PSF
RM1,147
Price Size
Period
transactions middle 50% (P25–P75)
RM1,417,000
Level 1
1,421 sqft RM997 PSF
RM1,842,000
Level 2
1,421 sqft RM1,296 PSF
Legend Recent Highest Price Highest PSF

Selling in Millerz Square @ Okr? Homes here sold for a median of RM1,629,500.

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Market Snapshot

Commercial

RM1,629,500

RM1,147 psf

Median transaction price

Average

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Millerz Square @ Okr
© OpenStreetMap · CARTO

Megan Legasi, 357, Jln Klang Lama, 58000 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Maps

Millerz Square @ Okr in Kuala Lumpur, Kuala Lumpur recorded 2 subsale transactions between 2021 and 2026, sized between 1,375 and 1,424 sqft, with a median price of RM1.63 million and a median price per square foot (PSF) of RM1,147.

This area contains both residential and commercial properties. View 29 residential properties or 39 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM1.63 million, with most transactions falling within a stable range of RM1.42 million to RM1.84 million, and a typical market range of RM1.42 million to RM1.84 million.

Most transactions involved office lot, with moderate diversity in property types available.

The median PSF stands at RM1,147, with core pricing between RM997 and RM1,296. Market pricing typically extends from RM1,080.74 to RM1,212.99, reflecting moderate variation in unit pricing. With an IQR of RM132.25 and MAD of RM150, the PSF demonstrates reasonable consistency across the market.

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.