| LIST.MY · Mahkota Hills | |||||
|---|---|---|---|---|---|
|
Road
|
Price
|
PSF
|
Size
|
Date
|
Type
|
| 2024 | |||||
|
Level 2
|
RM360,000
|
RM452
|
796 sqft
|
|
Townhouse |
|
Level 3
|
RM335,000
|
RM421
|
796 sqft
|
|
Townhouse |
| 2023 | |||||
|
Level 2
|
RM380,000
|
RM477
|
796 sqft
|
|
Townhouse |
|
Level 2
|
RM350,000
|
RM440
|
796 sqft
|
|
Townhouse |
|
Level 3
|
RM350,000
|
RM440
|
796 sqft
|
|
Townhouse |
| 2022 | |||||
|
Level G
|
RM360,000
|
RM452
|
796 sqft
|
|
Townhouse |
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Mahkota Hills
PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Cheras
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Market Snapshot
ResidentialRM355,000
RM446 psfMedian transaction price
3QHJ+V8 Marissa Hills, Kampung Bukit Raya, 43200 Cheras, Selangor, Malaysia
MapsMahkota Hills in Hulu Langat, Selangor recorded 6 subsale transactions between 2021 and 2026, sized between 775 and 824 sqft, with a median price of RM355K and a median price per square foot (PSF) of RM446.
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 RM355K, with most transactions falling within a stable range of RM341K to RM369K, and a typical market range of RM335K to RM380K.
Most transactions involved town house, with moderate diversity in property types available.
For price per square foot, the median is RM446, with most transactions between RM429 and RM463. The usual range is RM419.24 to RM472.74, showing that most units are priced quite close to each other. With an IQR of RM53.50 and MAD of RM17, 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. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.