Calgary’s November 2025 inventory shift: seasonal pause or choosier buyers?

emery_roan

First-time buyer
The limitation is that I can see current listings more easily than matched completed sales. In Calgary’s November 2025 market, well-presented townhouses appear to be taking about 105 days, while homes requiring work seem to linger. The difference I am seeing between advertised and completed prices is roughly 1.3%, although the comparison may not be like for like.

I am trying to work out whether this is a normal late-year slowdown or a stronger buyer preference for condition. Neighbourhood-level examples would be more useful than a citywide summary, especially if they identify the property type and distinguish original asking price, final asking price and sold price.
 
Those numbers alone cannot distinguish seasonality from selectivity. How was the 1.3% calculated: original asking price versus sold price, final asking price versus sold price, or active asking prices compared with a separate group of sales? Price reductions can make those versions tell very different stories. Transaction count and the number of townhouses behind the 105-day figure would also help.
 
The timing matters too. Is this a November 2025 snapshot, or a report published later with revised sales data? Active listings and completed transactions are different cohorts. A cleaner comparison would follow homes listed in a similar period through to sale, withdrawal, or continued availability, then separate renovated units from those needing work.
 
I’m not convinced a 1.3% visible gap demonstrates stronger buyer selectivity. Without a prior-month or prior-year comparison, it may simply be ordinary negotiation. The condition split sounds more informative, but even there we need the same neighbourhood, townhouse style, price range and fee structure. Otherwise “well-presented” may be standing in for several other differences.
 
I would break the Calgary total into a small table by neighbourhood and property type: number listed, number completed, original ask, final ask, sold price, and days on market. Also keep withdrawn or relisted properties visible rather than treating them as sales. If the pattern remains after that separation, the seasonal explanation becomes less persuasive.
 
One more caution: transaction volume can change the interpretation quickly. A 1.3% gap based on a small set may move substantially when late transactions are added or records are revised. I’d compare several monthly cohorts, note any policy timing without assuming causation, and focus on the distribution of results rather than one average. David, do you have the sample size and the Calgary neighbourhoods included?
 
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