Lisbon’s June 2025 inventory mix: seasonal change or more selective buyers?

A

ada.lowe

Property investor
I would like to show a genuine June 2025 change in Lisbon, but the available figures may be comparing unlike properties. Well-presented apartments seem to take about 112 days, while homes requiring work take longer, and the reported separation between asking and sale prices is around 9.7%.

That could indicate more selective buyers, seasonal variation or simply a different mix of homes entering and completing. Before drawing a conclusion, I need dated completed-sale records showing the areas and property condition represented in each group. Neighbourhood evidence would help establish whether the pattern is broad or confined to particular parts of the city.
 
To clarify, I’m not assuming the 9.7% is a straightforward negotiation discount. The asking and sold figures may cover different properties or time periods, which is exactly what I’m struggling with. I’d also like to know the sample size, when the completed-sale data was recorded, and whether earlier figures were later revised.
 
I would not describe that gap as buyer bargaining power unless the asking and completed prices are matched property by property. A citywide average can shift simply because more expensive renovated apartments are being advertised while a different mix is completing.

The 112 days also needs a definition: from first listing, latest relisting, or agreed sale? Splitting renovated and work-needed homes by neighbourhood would tell you much more.
 
Matching properties helps, but it still may not settle the seasonal question. Completed deals reflect decisions made earlier, whereas June asking inventory is current. Transaction volume matters too: a small number of completions can move the apparent gap without indicating a broad change.

I’d also separate any period around a policy change rather than treating the whole timeline as comparable. Which Lisbon neighbourhoods and property sizes are in the sample?
 
Agreed on the timing mismatch, though I wouldn’t wait for perfect matched data before responding. Present 9.7% as a difference between two datasets, not as the typical discount. Then show counts and median time on market by neighbourhood, condition and size, alongside completed-sale volume. If the pattern remains across several comparable groups and later revisions, selectivity becomes a stronger explanation; if it disappears, it was probably mix or seasonal noise.
 
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