TAF and USPAP - great analysis

[RCA]

My bold at the end of the paragraph. That right there is emotional.... the hottie wife (mistress?) pushes the remote control button in her Maserati to open the gates to drive into the approximate, $11 million private compound. "Whatever it takes", all cash purchases.....

MARs or any other super number crunching program is not going to accurately pinpoint the "most probable price", or price per square foot as they're emotional purchases. Sure, if you took all these Carmel oceanfront homes of similar size, quality of construction, views, etc., your program would cut a line straight through all the noise and give you a price per square foot, per bedroom, etc. However, I bet that scatter plot would have really wide variances.

It sounds to me from reading your posts about Mars, that it would be better as an AVM like Zillow or Redfin as opposed to a program to be utilized for a single residential dwelling.

Post an appraisal that was done with Mars and give us a look. Not a bunch of charts and graphs in a particular area, but an appraisal.

I often get models that predict the price of sales that account for 80% of the price variance just on the measured attributes from the MLS - plus, at times, my hard work of doing certain kinds of measurements that are not in the MLS. The other 20% is accurately valued by the residual.

I've explained this many times on this forum, and I don't have time to repeatedly repeat myself to the same forum members. However, appraisers can appraise complex properties, such as in the SF Bay Area, and be well within 2% of each other—or, if you will, within +/-2% of the likely value of a given property.

I've shared enough information for you to apply it to your work if you're up for the challenge.

What I have done on this forum is used by others to build their businesses. Usually, in my opinion, good-for-nothing opportunists pass it over to developers and statisticians working remotely. (They never thought those Indian or foreign developers would go out on LinkedIn and send emails.) But that's the way life is. Many people in statistics know they do all the work—and waste bags come along and take profit. That's their fault, of course.

Some people are more interested in solving problems, while others are more interested in buying new Lamborghinis, fancy rugs, or whatever. The best defense is to either hide the information, make it very complicated to understand - or make it open source to share with anyone who wants to use it -- with some added defensive mechanisms.

You will find free, open-source software, but using it proficiently can sometimes be daunting. You have to get the keys to get to the final goal. And that is the stumbling block for many. It is not that easy. However, all that means is that the productivity tools for appraisers, ones that actually work, will surely come later rather than sooner. Probably much later.

 

[Fernando]

Having some legitimate samples out there to emulate could prompt the underperformers to add more and ALSO clue the overperformers into where lies the point of diminishing returns. Save them time and effort without compromising the IRL utility of their workproduct within the context of the intended usage.

One reason some appraisers are paranoid about their quality is because nobody knows for certain what exactly passes for "adequate" in the eyes of the users.

I have looked at many appraisals and reviewed many in the past and I see how some are good and bad.
With the good, I was fortunate enough to see how it could make my reports better. Usually I would take their "good" comments and make them my own in my report.
Loner appraisers may benefit in seeing how others do their reports. They can see how some are bad and not be like them.

 

[Fernando]

I often get models that predict the price of sales that account for 80% of the price variance just on the measured attributes from the MLS - plus, at times, my hard work of doing certain kinds of measurements that are not in the MLS. The other 20% is accurately valued by the residual.

I've explained this many times on this forum, and I don't have time to repeatedly repeat myself to the same forum members. However, appraisers can appraise complex properties, such as in the SF Bay Area, and be well within 2% of each other—or, if you will, within +/-2% of the likely value of a given property.

Definitely not. With median price of $2,000,000, you're seeing most appraisers will appraise between $2,040.000 and $2,080,000.

I've shared enough information for you to apply it to your work if you're up for the challenge.

What I have done on this forum is used by others to build their businesses. Usually, in my opinion, good-for-nothing opportunists pass it over to developers and statisticians working remotely. (They never thought those Indian or foreign developers would go out on LinkedIn and send emails.) But that's the way life is. Many people in statistics know they do all the work—and waste bags come along and take profit. That's their fault, of course.

Some people are more interested in solving problems, while others are more interested in buying new Lamborghinis, fancy rugs, or whatever. The best defense is to either hide the information, make it very complicated to understand - or make it open source to share with anyone who wants to use it -- with some added defensive mechanisms.

Many don't understand MARS and misleading valuation can be done hiding behind MARS. Reports should be understandable to the reader to see how conclusions are drawn.

You will find free, open-source software, but using it proficiently can sometimes be daunting. You have to get the keys to get to the final goal. And that is the stumbling block for many. It is not that easy. However, all that means is that the productivity tools for appraisers, ones that actually work, will surely come later rather than sooner. Probably much later.

Much later. Since 30 years ago from my thesis, I still don't see how computer models can replace us ... but Fannie has the potential.

 

[Joe Flacco]

More data just goes against the most basic rule of real estate which is location location location.

Can insights be gains from analyzing bigger sets of data? Yes.

Is it better than comparing small sets most relevant to what is being valued? Hard no.

 

[Joe Flacco]

The idea that analyzing bigger sets of data is more accurate for valuing individual properties goes against everything I know and understand about residential real estate.

 

[Fernando]

The idea that analyzing bigger sets of data is more accurate for valuing individual properties goes against everything I know and understand about residential real estate.

It may work for tract homes in conforming neighborhoods to a small extent but then it can easily appraise without computer models.
Bert's hometown has tract homes which are easiest to appraise in Bay Area. Don't need darn computer models.

 

[Joe Flacco]

The fundamental difference between datascience and appraisal is that with datascience comparable selection is less important and you can get to the value with any comps as long as accurate adjustments are applied. In appraisal, it is comparable selection that is most important with adjustments made mainly to differences that have a significant impact on value.

They are very different philosophies. Datascience is just not better than appraisals for valuation of individual properties. It's just not.

 

[Fernando]

The fundamental difference between datascience and appraisal is that with datascience comparable selection is less important and you can get to the value with any comps as long as accurate adjustments are applied. In appraisal, it is comparable selection that is most important with adjustments made mainly to differences that have a significant impact on value.

They are very different philosophies. Datascience is just not better than appraisals for valuation of individual properties. It's just not.

With comps, fewest adjustments are the best. Data science analyzes multitude of variables (with MARS miss crucial subjective variables) and look at all SALES, not comps which is not appraising as we know.

 

[Joe Flacco]

It's not even that one location is better than another location. It is that the way people behave in one location is different from the way people behave in another location. It's very different.

Location Location Location

 

[Zoe]

I believe in GIGO.

That stands for "garbage in garbage out".