Lisbon apartments: wait or offer when condition drives the discount?

W

WarmLens

Property investor
Offering now could secure one of the better Lisbon apartments before the choice narrows, but waiting might show whether the current figures reflect a real pattern. Neither feels comfortable when the watchlist spans €143,500 to €215,300 and the properties vary so much in condition.

The snapshot shows movement of +4.3% and about 59 days on market, though I have heard conflicting explanations about seasonality. I am not yet convinced those figures are comparable: the percentage may refer to asking rather than completed prices, while an advert removed after 59 days may have been withdrawn rather than sold.

Condition and energy performance appear to affect achievable discounts, but they may simply be standing in for wider renovation needs. Would recent completed sales by neighbourhood and property type be the better test? I would also like to know how others exclude withdrawn stock when comparing listing times.
 
Before treating the 59 days as a market signal, is that measured to removal of the advert or to a completed sale? Those are very different endpoints. Also, does the +4.3% refer to asking prices or completed prices? Energy performance could matter, but it may also be acting as a proxy for the apartment’s overall renovation needs.
 
The price range alone may be mixing unlike apartments. Floor area, state of repair and exact neighbourhood boundaries could each change the result. I would split the watchlist into comparable groups first, then look at days listed and reductions within each group rather than across all Lisbon apartments.
 
I’m not convinced energy performance is the main driver. Seller motivation and buyer financing can produce a much larger gap between asking and agreed price, especially when one seller can wait and another wants certainty. Are the bigger discounts happening after several weeks, or are they already built into the first offer discussions?
 
A simple way to test this is to record the original asking price, current price, first price-cut date, stated energy performance, visible condition and listing status. Keep withdrawn properties rather than deleting them. After a few weeks, you should be able to see whether poorer-performing apartments are discounted earlier or merely remain advertised longer.
 
@sofiah’s endpoint question is important. A listing disappearing at day 59 could mean sold, withdrawn or relisted. I’d also want to know how narrowly the OP is defining each neighbourhood, because listings near a boundary are often grouped differently and can distort a small sample.
 
Seasonality would show up more clearly in new-listing volume than in one average days-on-market figure. Follow separate weekly cohorts: how many arrive, how many receive a cut, and how many vanish. Otherwise a burst of fresh stock can change the apparent market even if buyer behaviour has not changed.
 
On energy performance, I would compare the rating with the actual condition and likely improvement work rather than using it alone. Two apartments with similar stated performance may present very different costs and disruption. Buyers may be negotiating against the whole package, which supports @sofiah’s point that energy can be a proxy rather than the cause.
 
There is another complication with price cuts: timing can reveal motivation, but not always value. A quick reduction may mean the opening price was ambitious; no reduction may simply mean the seller is prepared to wait. Recent completed sales would be a better comparison, provided they are genuinely similar apartments in the same defined area.
 
I’d narrow the next step to three comparisons: renovated versus needing work, financed buyers versus offers not dependent on financing where that information is actually available, and active versus withdrawn stock. That should help separate property condition from seller circumstances without assuming every disappearance was a sale.
 
The replies are pointing to a measurement problem more than a clear Lisbon-wide trend. I would not base an offer on +4.3% or 59 days until the OP confirms what each figure measures. For an individual apartment, its price-cut history, comparable completed sales and renovation burden are likely more useful than the broad average.
 
Agreed, though I wouldn’t wait indefinitely for perfect data. Define the neighbourhood boundary and apartment type, track new listings and withdrawals, then set an offer range from the closest completed comparisons. Use energy performance and visible condition to adjust that range, while treating financing and seller motivation as case-specific rather than market-wide.
 
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