Time Adjustments

[Metamorphic]

What does the graph tell you? Houses sold in 04/01/2001 for $300,000 (DOM 0) are now selling for $100,000 03/28/2008 (DOM 90)?

What am I missing? What about, price range, SF, Style, view, neighborhood, etc?

It tells you that in 2005 houses in this neighborhood were selling for between 200, and 350 k with the average house selling for about 280 with a negligible market time. The market was very active with a dozen or more sales each month. It tells you that in the first quarter of 06 things started to change, marketing time began to increase and prices began to fall. By 4th quarter 06 the decline in values was well established and much fewer sales were occurring. Declining prices and below normal activity continued through 4th quarter 07 at which point volume began to increase, marketing time was still increasing running close to 90 days on average with a significant number of properties staying on the market much longer. At the inspection date, properties were still declining with properties selling for between 75k and 200k, although most of the activity is in the lower priced properties. Volume was much relatively high, prices are still declining but there's a suggestion that there is some resistance at the 100k level. The average price is currently about 115k. The yellow line is the by comparing the value at any two points on the yellow line you have a reasonably well founded basis for making a market adjustment between those two time periods.

I can filter these results by all the things you mention, but its mostly counter productive if you've defined an appropriate neighborhood. Basically what you find is that in dense, conforming neighborhoods like this one massaging the data doesn't get you much. In non conforming neighborhoods the graphs can be a little indistinct until you go through and weed out the odd ball properties ( really big or really small GLA, big/small lots, super old properties or super new stuff in established neighborhoods, etc.). But really the whole point of doing a statistical method is that the occasional weird sale does not change much of anything.

Really the killer for this method is that you have to have a lot of sales to make the trend distinct. When you dont have very many sales you have to increase the size of the area you're pulling from to get enough data and then the applicability is reduced.

 

[Ariba]

I can filter these results by all the things you mention, but its mostly counter productive if you've defined an appropriate neighborhood. Basically what you find is that in dense, conforming neighborhoods like this one massaging the data doesn't get you much. In non conforming neighborhoods the graphs can be a little indistinct until you go through and weed out the odd ball properties ( really big or really small GLA, big/small lots, super old properties or super new stuff in established neighborhoods, etc.). But really the whole point of doing a statistical method is that the occasional weird sale does not change much of anything.

Really the killer for this method is that you have to have a lot of sales to make the trend distinct. When you dont have very many sales you have to increase the size of the area you're pulling from to get enough data and then the applicability is reduced.

So the bottom line is that it basically means nothing in defining a declining market in a specific market area.

I have found many pockets in my market area that have been increasing substantially that are surrounded by declining markets. Your graph might be great for the whole metro market area but has little value about specific markets.

 

[Metamorphic]

That's about 4 square miles of dense, highly conforming 50-60's tract with about 5 different models and I think its highly significant.

 

[Riick]

So the bottom line is that it basically means nothing in defining a declining market in a specific market area.

I have found many pockets in my market area that have been increasing substantially that are surrounded by declining markets. Your graph might be great for the whole metro market area but has little value about specific markets.

One Robin does not make a Springtime, nor one isolated market, a trend.

I've been experimenting with similar graphing, just to make the the data visceral to the reader.
My charts are not nearly so dramatic, since prices have been a lot more stable here.
But, if I cut out the upper and lower ends of the chart (NO, not the data, the CHART)
to allow you to focus on the trendline, the decrease in average value is readily apparent.

Pointless to track Days on Market today - after 60 days, Brokers just withdraw the property and re-list it.
("Honestly Mary-Ann, things are so slow here, I've been thinking of moving to another town, and starting over as a Virgin")
-That's a joke son, a joke -

 

[Mztk1]

It tells you that in 2005 houses in this neighborhood were selling for between 200, and 350 k with the average house selling for about 280 with a negligible market time. The market was very active with a dozen or more sales each month. It tells you that in the first quarter of 06 things started to change, marketing time began to increase and prices began to fall. By 4th quarter 06 the decline in values was well established and much fewer sales were occurring. Declining prices and below normal activity continued through 4th quarter 07 at which point volume began to increase, marketing time was still increasing running close to 90 days on average with a significant number of properties staying on the market much longer. At the inspection date, properties were still declining with properties selling for between 75k and 200k, although most of the activity is in the lower priced properties. Volume was much relatively high, prices are still declining but there's a suggestion that there is some resistance at the 100k level. The average price is currently about 115k. The yellow line is the by comparing the value at any two points on the yellow line you have a reasonably well founded basis for making a market adjustment between those two time periods.

Your description of the chart is what would makes your quality stand out. A lot of people look at charts and don't know what to make of them, but when they are told what the chart is saying, suddenly they see it the same way. For a summary appraisal I think your comments describing the chart are perfect and it wouldn't matter if you put the chart in the report or just left it in the workfile.