Are 31 days on market meaningful for this Hong Kong price band?

[scanTheBook]

I can find asking data everywhere, but completed numbers are much harder to line up. For Hong Kong apartments asking HK$4,836,000–HK$7,254,000, my current sample suggests roughly 31 days to find a buyer. Most outliers seem related to maintenance or condition.

Would you treat 31 days as useful yet, or wait for recent completed sales? I’m concerned that active listings, withdrawn stock and relisted units are distorting the result.

 

[gardensAndCorner]

I would not use 31 days as a market-wide figure yet. Active listings only tell you which homes have not disappeared from view, while completed sales represent a different group and may appear later. Split the sample into sold, withdrawn and still advertised. If those categories cannot be identified reliably, call it an asking-listing measure rather than time to find a buyer.

 

[kai.miles]

What area does the sample cover? Hong Kong at that price can mix very different neighbourhoods, building ages and apartment sizes. Even a boundary drawn one street differently could change the comparison. Also, by “maintenance,” do you mean the unit’s physical condition, recurring building costs, or major works? Those would affect buyers differently.

 

[gia_wren]

Alex’s question matters, but seller behaviour may be just as important. A motivated seller who sets a realistic price can move quickly; another can remain online for weeks before making the first meaningful cut. I’d record the original ask, each price-cut date and the final visible ask. Otherwise the 31 days hides when the listing actually became competitive.

 

[DevQuinn]

I disagree slightly with waiting for completed sales before using the figure. The sample can still be useful for comparing similar listings this month, provided Yara doesn’t present it as a completion measure. My bigger concern is new-listing volume: a burst of fresh stock can make the active pool look younger without any improvement in demand.

 

[XaviReed]

There is also a basic timestamp problem. Does day one mean the first public appearance, the latest agent upload, or the most recent price? If the same apartment is removed and relisted, its apparent marketing period may reset. I’d retain the earliest observed date and flag any gaps rather than automatically treating the new advertisement as a new property.

 

[ari_park]

Condition might explain some outliers, but buyer financing can also stretch the period between initial interest and an actual deal. That makes “found a buyer” difficult to infer from a listing disappearing. Unless you know why it vanished, disappearance should be its own outcome—not silently counted as sold or withdrawn.

 

[XaviReed]

Agreed. A practical table could have one row per apartment and columns for neighbourhood, building, size, condition, first-seen date, original ask, price changes, last-seen date and status. Keep unknown status as unknown. Then compare the 31-day group with the long-running group to see whether one factor repeatedly separates them, rather than attributing every long listing to maintenance.

 

[DevQuinn]

That works, although I would avoid overloading a small sample with too many categories. Start by narrowing the neighbourhood boundaries and separating clearly dated units from uncertain or relisted ones. Then add price-cut timing. If 31 days survives those two changes, it becomes more persuasive; if it moves sharply, the original result was mainly a sampling effect.

 

[XaviReed]

One more distinction: report the median observed time separately for completed, active, withdrawn and unknown listings, if the available records support it. Don’t combine them into a single “time to buyer” number. Seller motivation will remain hard to measure directly, but repeated cuts or a quick withdrawal can be noted as behaviour without guessing the reason behind it.