OUG Parklane

Jalan 1/152, Taman Perindustrian Oug, 58200 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

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From
RM 600K
Size
800 sqft

Property Transactions

5 subsales grouped by size · Serviced Apt →

Median
RM 550,000
PSF
RM 574
Price Size
Period
transactions middle 50% (P25–P75)
950 sqft
Serviced Apt
RM 362,000
Level 28
958 sqft · RM 378 PSF
RM 358,000
Level 20
958 sqft · RM 374 PSF
RM 600,000
Level 4
958 sqft · RM 626 PSF
RM 600,000
Level 5
958 sqft · RM 626 PSF
RM 550,000
Level 15
958 sqft · RM 574 PSF
Legend Recent Highest Price Highest PSF

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OUG Parklane, Jalan 1/152, Taman Perindustrian Oug, 58200 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia

Maps
List AI Investment Analysis. High-density value play balancing strong rental demand against significant supply-side pressure

OUG Parklane in Kuala Lumpur, Kuala Lumpur recorded 5 subsale transactions in 2026, with a median price of RM 550K and a median price per square foot (PSF) of RM 574.

This area contains both residential and commercial properties. View 435 residential properties or 6 commercial properties separately for more focused analysis.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM 550K, with most transactions falling within a stable range of RM 439K to RM 600K, and a typical market range of RM 460K to RM 600K.

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

Price per square foot shows a median of RM 574, though individual units vary from RM 458 to RM 690 in the core range. The broader market spans RM 479.50 to RM 668.50, indicating diverse property characteristics. The spread of RM 189.00 (IQR) and deviation of RM 116 (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. Moderate price stability provides a balanced market for both buyers and sellers. Limited transaction history suggests carefully evaluating comparable sales data.