Hamilton Record Sales in November 2016!
Its a sellers market! If you are selling your house we can help you make the most on your investment and here is why!
Here is a report from the REALTORS® Association of Hamilton-Burlington that 1,323 sales were processed by the RBHA Mutiple Listing Service® (MLS®) System in November 2016. Because of November 2016's 5.6 percent sales increase from November 2015, this month has set a new record high.
Here is a recap of some of the data recovered in this triumph of property sales!
- Adjusted seasonal sales were 1.1 percent lower in November 2016 than November 2015 on real estate property for sale
- Average sale price was 19 per cent higher in November 2016 than November 2015
- November 2016's new listings were 2.6 percent higher in numbers for seasonal adjusted numbers
- Sales of residential homes were 1,267 overall and 5.3 percent higher than November 2015
- Condominium market sales were 16.6 percent higher than November 2015
- Condominium properties increase 26.7 percent compared to last year
- Median price of freehold properties increased by 21.1 percent in November 2016
- Average price of freehold properties increased 20.2 percent from November 2015
- Average sale price in condominium market increased 23.5 percent in November 2016
- Average sale price is based on the total dollar volume of all properties sold through the RAHB MLS®System.
- Average sale price can be useful in establishing long-term trends, but should not be used as an indicator that specific properties have increased or decreased in value.
Contact our real estate broker agent for information about your area or property.
- Average number of days on market decreased from 36 to 25 days in the freehold market in November 2015
- Average number of days on market decreased from 34 to 26 days in the condominium market in November 2015
All communities within RAHB’s market area have their own localized market. Take a look at the data chart below and contact us for more information.
*Seasonal adjustment removes normal seasonal variations, enabling analysis of monthly changes and fundamental trends in the data.