What changed in Singapore this month? My sample is at 101 days

[gate.strong]

I can find asking data everywhere, but completed numbers are harder to pin down. Looking specifically at Singapore retail units listed between S$284,100 and S$426,100, my current sample suggests roughly 101 days to find a buyer.

Most of the outliers seem connected to insurance-related issues, although I may be classifying those badly. Do recent completed deals support a 101-day period, or am I overweighting older listings that remain online while withdrawn or quietly completed stock disappears?

 

[KeenInk]

The listings still online will naturally make the market look slower. Without withdrawn stock and completed transactions, 101 days is better treated as the age of your visible sample than as time to sale. I would separate active, withdrawn and confirmed completed units before drawing a market-wide conclusion.

 

[daan.cane]

What does “connected to insurance” mean here—difficulty insuring the premises, a permitted-use issue, or simply wording in the listing? That could be important, but it could also be a coincidence caused by condition or location. I’d also want to know whether your neighbourhood boundaries stayed constant during the comparison.

 

[pia_lending]

I agree about the visibility bias, but completed sales alone will not settle it. A unit may find a buyer well before completion, especially if financing or other conditions take time. The useful comparison would be original listing date, first price cut, apparent agreement date where known, and completion date. Those are different clocks.

 

[cyclesAndChalk]

New-listing volume matters too. If relatively few fresh units entered this price band, the remaining stock would age even if buyer demand had not changed much. Conversely, a burst of new listings could pull the average age down without anything selling faster. Can you compare the same group over time rather than taking separate snapshots?

 

[common_creek]

I’d be cautious about combining all retail units in that price range. Two similarly priced properties can attract very different buyers because of condition, access, current use and neighbourhood. A broad Singapore figure may hide several small markets. Even a rough split by area and condition would make the 101 days more informative.

 

[measureTheRoute]

There is also a seller-motivation problem. Some owners test an ambitious asking price and wait; others cut early because they need a deal. That does not mean the underlying properties have equal liquidity. I’d chart when each price cut happened and calculate time from the latest meaningful cut as a second measure.

 

[selma.gale]

Practical approach: freeze the current list, record first-seen date, current asking price, price changes, condition, area and status, then revisit the same units regularly. Mark disappearances as unknown unless you can confirm whether they sold or were withdrawn. That avoids treating every vanished listing as a completed deal and every old listing as genuine available stock.

 

[SteadyPebble]

One more caveat: buyer financing can affect both which units attract interest and how long a transaction remains uncertain. Cash assumptions and finance-dependent interest should not be blended if that distinction is available. Given the missing completion and withdrawal data, I would report “101 days among observable listings” rather than “101 days to find a buyer.”