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Overall Market Trend (Min 12 months)

View attachment 96174

The dots in the red box that pull up the curve and the dots in the blue box that pull down the curve are not the same.

So what we have above in the red box represents the spring season, the most active time of year for real estate transactions. Then for the remainder of the year in the blue box, you see that the dots are towards the lower end of the range curing the line back down. It is generally fewer transactions during that time and the properties that trade around that time tend to be inferior to the properties that trade in the spring. That is why the dots are lower. The dots are lower because they are inferior properties, not because they are equivalent properties as the upper end of the range sales in the red box. Prices and values are not declining from the red box to the blue box.

Understanding that this is the cause for the shape of the curve and the change in median price data over the year is very important.
price per sf is an unreliable metric for this purpose
Why are you using that and not using sale prices?
 
That would be misleading for the subject affected area.
Well that is what FNMA wants us to do.

First 9 months prices increase 12% then last 3 months after plant closes prices drop 9% you mark increasing because of the overall trend for the year. And if its 12% up then 12% down its stable.
 
price per sf is an unreliable metric for this purpose
Why are you using that and not using sale prices?

I just looked at the feature in datamaster after the OP in the other thread posted about it.

But let me ask you, why is sale price better than price per SF for this purpose?
 
I just looked at the feature in datamaster after the OP in the other thread posted about it.

But let me ask you, why is sale price better than price per SF for this purpose?
Because we are analyzing prices, not price per SF, to arrive at a trend to see if prices need adjusting or not -

And the price per sf can be skewed esp if you add in lot and dwelling, which is how RE agents do i,t which is not generally used in an appraisal
 
I just looked at the feature in datamaster after the OP in the other thread posted about it.

But let me ask you, why is sale price better than price per SF for this purpose?
If you are using comparables sales price is better. If you are combining $100,000 properties with $2,000,000 properties its better to use price per sf, but even then its gonna mess up the data.
 
Because we are analyzing prices, not price per SF, to arrive at a trend to see if prices need adjusting or not -

And the price per sf can be skewed esp if you add in lot and dwelling, which is how RE agents do i,t which is not generally used in an appraisal

You don't want to compare two properties based on price per SF but for this purpose it is the same. I might even argue that median price per SF is more reliable for this purpose because it at least controls for the size of the houses.
 
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1738432730658.png

I think that datamaster polynomial curve equation is bad. I have no idea what that equation means. But that is what it is spitting out.

This is the same data populated into the MC form. It is not showing a 10% decline from June / August to today.
 
You don't want to compare two properties based on price per SF but for this purpose it is the same. I might even argue that median price per SF is more reliable for this purpose because it at least controls for the size of the houses.
You are arguing for your way, which is fine for you, but it is not that of most peers nor is it what the GSEs's are asking for regarding the past year's trend of PRICES as support for adjustments if made for market conditions.

If they wanted price per sf they would have said so.
 
You are arguing for your way, which is fine for you, but it is not that of most peers nor is it what the GSEs's are asking for regarding the past year's trend of PRICES as support for adjustments if made for market conditions.

If they wanted price per sf they would have said so.

Ok so do it the way you want to do it.
 
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