What changed in Athens this month? My sample is at 90 days (5 bed)

[drawTheTrail]

I’m tracking Athens warehouses listed between €265,000 and €397,400, focusing on two neighbourhoods rather than the citywide average. The current listings suggest roughly 90 days to find a buyer, with the outliers seeming related to property tax issues.

Is that consistent with recent completed deals, or is my sample distorted by properties that remain online? I’m trying to decide whether 90 days reflects real demand or simply stale and withdrawn stock.

 

[oren_chase]

Active listings alone will usually make the market look slower because the properties that sold quickly have disappeared. I’d separate completed sales, withdrawn listings and genuine price cuts. Also note when each reduction happened: a warehouse listed for 90 days but cut only last week has not really tested its current asking price for 90 days.

 

[makeTheAnchor]

You want the 90-day figure to describe real demand, but it will not help much unless the two neighbourhood samples and building conditions are genuinely comparable. A usable renovated warehouse at €397,400 may draw a different buyer from a cheaper one that needs extensive work, even if both appear in the same broad search.

I would first narrow the boundaries, grade condition consistently and then check completed transactions separately. Also record the date terms were agreed where that information is available, because financing and completion delays can make a successful sale look slower than the marketing period really was.

 

[isa.james]

I wouldn’t assume property tax explains most outliers without more detail. Seller motivation can produce the same pattern: an unrealistic asking price sits, while a motivated owner cuts earlier and completes. New-listing volume also matters. If few suitable properties came on this month, 90 days could describe old inventory rather than a recent change in Athens demand.

 

[drawTheTrail]

That distinction between total listing age and time since the latest price cut is useful. I’ll rebuild the sample by neighbourhood, condition and current-price date, then mark anything withdrawn separately rather than treating it as unsold. I’ll also compare how many new listings appeared this month before drawing a conclusion from the 90-day figure. The tax explanation may be weaker than I first thought.