What Creates Long-Term Value in Dubai Property
February 2, 2026
Headline sales figures are at all-time highs. How to read transaction data properly, and what it reveals about the depth and health of the market.
Head of Private Clients
Specializing in family office advisory and multi-generational wealth transfer. Victoria manages relationships with 50+ UHNW families across 15 countries.
Headlines about record transaction values are common in Dubai, and the latest figures are once again exceptional. But big numbers can hide important details. Understanding what transaction data measures, and what it does not, helps buyers and investors read the market more accurately.
Rising values can reflect higher prices, more transactions or a few very large sales. A high share of off-plan sales indicates confidence but also future supply.
Growth in both ready and off-plan sales, broad participation across price ranges and a strong end-user share suggest depth rather than speculation.
A rising share of quick resales of off-plan contracts or sharp price increases in a single segment could signal speculative activity.
Buyers should look at transaction data for their specific community and property type rather than citywide headlines.
Citywide average prices are often quoted, but they can be misleading. If more luxury homes sell in one month, the average rises even if prices for individual properties have not changed. If more affordable apartments sell, the average falls. Price per square foot, measured within the same building or community over time, gives a more reliable picture of real price movement. Repeat sales, where the same property sells more than once, are even more accurate. Buyers and sellers should look for data that compares like with like, rather than drawing conclusions from headline averages that mix very different properties. Advisers who provide building-level data offer a much clearer view of value than market-wide figures.
Record figures confirm Dubai's strength, but detailed analysis matters more than headlines. We use transaction data to guide clients' decisions at the level of individual buildings and communities.