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Automated Valuation Models

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Eli

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Tennessee
I am curious about avm's and would like to know more.

For example, do AVM's make value?

How does an AVM relate legally in States where a person must be a licensed appraiser to provide an appraisal?
 

leasedfee

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Colorado
A Guide to Appraisal Valuation Modeling, Mark R. Linne, M. Steven Kane, George Dell (Appraisal Institute). Disclosure: I worked for and with the first two gentlemen; could'a been a co-author on this book but didn't get my chapter done. It is a relatively simple and short read, and mostly multiple regression analysis. MRA is covered 10 ways to Friday but this book uses examples that we relate to, unlike MRA examples that use drug-trial data as an example.

AVMs fall under USPAPs Mass Appraisal Standards.
 

Terrel L. Shields

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Arkansas
AVMs can and are used for certain things not involving origination of a loan.
 

CindyR

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Oct 26, 2003
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Certified Residential Appraiser
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Arizona
How does an AVM relate legally in States where a person must be a licensed appraiser to provide an appraisal?

Am AVM is not an appraisal so it need not be prepared by an appraiser.
 

Restrain

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Certified General Appraiser
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Florida
CoreLogic and related companies provide AVMs, currently used for 2nd liens, equity notes. Gives a range of values, but it is only as good as the data input. Tat is why CoreLogic has acquired MLS systems in non-disclosure states. Appraising in Texas, I would get AVMs citing sales that didn't exist. They would pull a mortgages, and call them sales, treating them at 80% LTV. I would research the data and find they were refinance loans, and often at 90% and higher LTVs.

However, with all the MLS data now available, you are looking at a raw data input, with a weighing in terms of size, proximity. If you have an active market and a market that is relatively homogenous, the current AVMs are relatively accurate, within about 10%.
 

J Grant

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Florida
From what I understand, AVM's receive "confidence scores", from low to high, indicating what level of confidence the user could have in relying on it.
 

Meandering

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Feb 26, 2006
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Real Estate Agent or Broker
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Pennsylvania
I am curious about avm's and would like to know more.

For example, do AVM's make value?

How does an AVM relate legally in States where a person must be a licensed appraiser to provide an appraisal?

AVMs do no "make value", and neither do appraisers. Buyers and sellers "demonstrate value" as value is demonstrated by a sale price negotiated between buyers and sellers who are knowledgeable, typically motivated, not influenced by favorable financing, blah, blah, blah.

Appraisers and AVMs correlate market activity to the definition requirements of a "defined value" to arrive at a determination of which sales and which transactions best represent reasonable substitutes for the property whose possible value in the market is being questioned.

AVMs are not appraisals, and appraisals are not AVMs. Just like appraisals are valuations, but not all valuations are appraisals.

If this sounds like language parsing, it is. Because that's they way the laws are written. Appraisals are opinions, AVMs are mathematical calculations.
So within states that require a person be a licensed appraiser to provide an appraisal, AVMs are not an issue, because, as defined in the law, appraisals are opinions, that are made by humans, and AVMs are not opinions.

.
.
 

leasedfee

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Professional Status
Certified General Appraiser
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Colorado
. . . AVM's receive "confidence scores", from low to high, indicating what level of confidence the user. . . .
Statistical models throw off a variety of variance measures, like Standard Error, R^2, coefficient of variation, Confidence Intervals, F-stats, P-stat, etc. The one that the general public is most familiar with are the "+ or -" you see on a political poll. All it means is that political opinion surveys or valuation predictions are a range and not a specific value. It also means that if this same survey was to be re-conducted exactly the same manner and method the results would fall within that range.The Confidence Interval range isn't going to help you if you can't reach vast swaths of the voting public on a cell phone, nor is the CI insightful if Trump's electorate declines to answer or answer falsely.

Thus, to say one politician or opinion is ahead or more popular at 46% vs. 44% {with 10% other} is statistically meaningless. To get the 3% or so that you see on political polls the honest companies commonly survey a 1,000+ people and they have to carefully try to obtain cluster sampling of each demographic segment. If you survey 1,000 people at a Monster Truck Rally or at a TED Talk all it means is that this is the likely result for that demographic -- not the nation or state! The famous Truman Beats Dewey headline resulted from the pollsters relying on phone interviews in an era when the lower- and middle-classes did not universally have phone lines thus skewing the "who", known as sampling, is surveyed. The dishonest pollsters, especially for special interest groups, know they can tweak the results, or push-poll results with "what" and "how" is being measured and asked.

What is being measured is as important as who. This becomes messy because of definitions. If we are sampling Koreans, do we mean North and South, both, or American-Koreans? If we are sampling blonde women, or single women, or soccer moms, or angry white men, or restaurants, or McMansions, then what is that exactly? Traditional statistical models require homogeneity of the data. If you are asking what is the average male height, then we have to define who is an average male. 18 and older? 18 to 65 yo? 25 to 65? Americans? All races or one? If all races, then is it representative of the demographic distribution.

Narrow tight definitions have more knowledge and less noise -- but they are less useful. Consider this question:

"What brand of tooth paste (or did they vote for Hillary or Trump) (or how much house payment can they afford)?" of white single-mothers aged 30 to 35 living in a 1980s multi-family Lakewood, Colorado prefer.​

Now that is useful knowledge! Very little noise if you survey 30 or more of these people. It can be successfully interpolated across the entire narrow population.
Yet the data is useless if you change any one of those variables: race; marriage status; family status; age range; housing type; city; state. Facebook, Kroger, and Visa collect this type of detailed dataset to every little pocket across America.

Broad loose definitions have little knowledge and extensive noise.

What brand of tooth paste (did they vote for Hillary or Trump) (how much house payment can they afford) of Americans?​

This is useless knowledge. Vast amounts of noise and doesn't mean much for making behavioral predictions of the statistical population or sub-population.

Bringing this back home, pun intended, the gigantic problem for AVMs is the (1) data, (2) definitions and (2) small sample size.
  1. Real estate data is sloppy, incomplete, wrong, out of date.
  2. The definitions can be too precise (e.g., breaking down the full array of bathroom mix which is simply too much unnecessary information), too generalized (e.g., tossing in basement sf into above-grade sf). Definitions aren't very clear: What exactly is a "condition" rating? Real estate academics have a tendency to think "if I have this data variable" then it must be important and I should use it. I call this the "everything in the blender" problem. So they may use "end of cul de sak" or not as their "location" variable but not include school district because they lack that variable in their acquired dataset -- and they will grab sales in dozens of neighborhoods that no sane appraiser, even the skippy appraisers, would consider.
  3. The sample sizes are so small that the Standard Error becomes gigantic. It is like conducting a survey to conclude the average man is 5' to 7' tall. Duh. It only truly works in cookie cutter subdivisions.
    Appraising in Texas, I would get AVMs citing sales that didn't exist. They [Corelogic] would pull a mortgages, and call them sales, treating them at 80% LTV. I would research the data and find they were refinance loans, and often at 90% and higher LTVs.
    Corelogic's statistical modelers trying to solve the sample size problem creates a "synthetic sale" but compounds it by making the real estate data wrong. It is an elegant lie.
It gets worse with real estate specific problems, like extrapolation problems like of age or size outside the dataset; unknown categorized externalities; biggest house on the block; nicest {worst} house on the block; potential to raze; distressed or non-arms length sales; renovations-condition.

It gets even worse when you consider model construction -- but this is enough for now.

Said more simply:
AVM = POS!
 

timd354

Elite Member
Joined
Jan 11, 2008
Professional Status
Certified Residential Appraiser
State
Maryland
AVM = POS!
That is a stupid commennt that is undoubtedly a result of your own ignorance regarding AVM's. AVM's are very useful for some purposes as long as the user of AVM's is aware of and understands their limitations. While I am of the opinion that AVM's are of  limited value on a property/loan level basis, they can be highly useful for portfolio analysis. For instance, we run several AVM's against our portfolio of insured loans and compare the median AVM values to the appraised values and calculate the variance - this can be used to identify lenders who submit appraisals that have an abnormally high variance compared to our overall book of business. Just because a lender has a higher appraisal variance that is outside the norm does not mean that their appraisals are inflated, but it is indictor that that particular lender may have a higher incidence of inflated appraisals and we can thus target additional loans from that lender to be included in our QA samples that we review which in turn helps us determine whether we have a problem with that particular lender
 
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