MON'T KIARA PINES Transaction Price & PSF
MON'T KIARA PINES Condominium/Apartment Residential Property Market | residential | Data through April 2026
This targeted market snapshot examines MON'T KIARA PINES within the residential sector, focusing on the Condominium/Apartment segment and how readers can interpret the available transaction data without asserting outcomes.
Market overview
The dataset indicates activity is concentrated in Kuala Lumpur, with Mukim Batu serving as the primary submarket. MON'T KIARA PINES is the dominant scheme within the observed transactions, reflecting its central role in this residential market slice. The data capture a history of activity across multiple years, illustrating how transaction patterns can vary over time while remaining anchored in this specific locale.
Property type benchmarks
The figures below are calculated from transaction records in the PropMedian database. Median PSF is shown only where sufficient parcel area data is available.
Condominium/Apartment
In MON'T KIARA PINES, the Condominium/Apartment category is the represented property type in the dataset, and it is the main source of observed activity within this scheme.
How to interpret this market
Use the transaction benchmarks as contextual reference for the same property type within the same submarket. Do not assume that a single property will move in the same way as the benchmarks; characteristics such as features, condition and timing can lead to different results.
Explore the underlying market
View the PropMedian property-data hub for this district to explore available property types and transaction benchmarks.
View Kuala Lumpur property dataFrequently asked questions
What is the dominant property type and submarket for MON'T KIARA PINES in the residential segment?
The data indicate that the Condominium/Apartment category is the represented type for MON'T KIARA PINES, with activity centered in Kuala Lumpur and the Mukim Batu area.
How should buyers use the transaction benchmarks when evaluating a property?
Use benchmarks as contextual guidance for the same property type within the same submarket, keeping in mind that individual properties can differ in features, condition and timing.
What should readers keep in mind about the data period and its implications?
The benchmarks reflect historical transactions up to the data period; they describe market patterns rather than predicting future moves or guaranteeing outcomes.
Summary
Readers should compare property types and transaction benchmarks within similar markets to form a balanced view, avoiding overinterpretation of any single data point.
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Methodology
Median transaction price for the selected market scope.
Parcel PSF is the median of valid transaction-level parcel PSF values, not median price divided by median area.
Unavailable measurements are not estimated or inferred.
Parcel PSF is displayed when there are at least 10 valid PSF observations and coverage is at least 25%.