JOSH BUCHANAN

September 28, 2016

This post is designed to supplement post #60 and won’t make as much sense without reading that post first.

In my original statistical forecast, I looked at year-over-year changes in the sales-to-listings ratios over the past 14 years to see what kind of price changes they led to in the following year. The one flaw with this analysis is that I only looked at price changes in response to ratio changes but did not take into consideration the deviation from a balanced ratio of 0.50.

As explained in previous posts, a sales-to-listings ratio of 0.50 is considered balanced and should lead to prices remaining flat. Once the ratio rises above 0.50, prices should rise once there has been enough time to react. The higher the ratio, the larger the price growth should be. On the other hand, the same goes for ratios below 0.50 as they will see negative growth the further the ratio deviates down from the balanced point of 0.50.

In this post, I have used the same analysis only I have accounted for the balanced ratio threshold to see how much prices change per 0.01 change in ratio once they have deviated from 0.50.

For example, let’s say that the year 2000’s ratio was 0.60 which is a 0.10 deviation from the balance point of 0.50 and after the 1-year price delay for this year, prices increased by $12,000 from the previous year. This would mean that for every 0.01 deviation from 0.50, prices grew by $1,200.

Below I have made a chart showing the statistics from 2001-2014 to show what kind of price changes we have seen based on deviation from the balance point.

Source: SRAR

Based on the numbers from the chart, the average price change from a 0.01 deviation in the ratio is $1,787.02 using this sample of years. The minimum was $252.70 and the maximum was $4,485.67. Therefore, if you apply the minimum, average and maximum changes to the ratio deviation in 2015, we should get a good idea as to where 2016 prices should be trending based on this sample. Because the ratio in 2015 deviated by 0.10, I will multiply the given price changes by a negative 10-point deviation in order to get price forecasts:

Minimum price change forecast:

$252.70(-10) = -$2,527.00

Average price change forecast:

$1,787.02(-10) = -$17,870.25

Maximum price change forecast:

$4,485.67(-10) = -$44,856.70

Using the previous 14 years as our sample for price changes and given the fact that 2015 had a ratio that deviated 10 points from a balanced ratio, the minimum price decline we should be seeing in 2016 is $2,527 which we have already surpassed. The average price decline should lead to a drop of $17,872 which is exactly what I predicted in my 2016 predictions post but we still have a ways to go before getting there. The maximum drop we should see is $44,857 which seems almost impossible to reach by the end of the year but could still happen into 2017 once we build up enough momentum and prices react appropriately to the 2015 and 2016 ratios that are well below balanced.

Of course there is no perfect method for measuring prices or forecasting them but this analysis should give a pretty good idea of what we should be seeing currently and moving forward with average MLS sales prices in Saskatoon based on market conditions and historical behaviour.

The views represented are solely those of Josh Buchanan and are independent from any professional organization.