Distressed Conditions: Exposure

[ZZGAMAZZ]

I appraised as "Fair Market Value" because the Court instructions were only for an "As Is" Opinion of Value, which if approved by the court would be the lowest possible offer that the conservator could accept, which I presumed was obviously based upon the Court's desire to protect assets of the estate as much as possible.

Question please about a similar issue:
Am I correct thinking that the subject's estimated Market Exposure by definition will always be similar/identical to Market Exposure for the entire local market because the appraiser's Opinion of Value of the subject, even if being liquidated, would be less than the overall market exposure, consequently warranting the same exposure in terms of lenth of the property being marketed and leading up to a contract?

 

[George Hatch]

If/when the market demand is strong enough that a competitively priced property can be moved within the abbreviated time the values will be the same/similar.

How would you even go about developing a discount if/when the market is that hot?

 

[RCA]

I've always been confused about the concept of Market Exposure as it pertains to a scenario when the subject property conditions differ from the market standard. HOWEVER, I'm appraising a distressed property at present, and realize that exposure for the subject "always must be identical to market exposure" because the Opinion of Value expressed in the report reflects market reaction, consequently affecting the Opinion of Value so [coincidentally] exposure equals "market exposure," .... kinda like "always." Right or Wrong?/

Ummm... I don't see the problem. Your market value conclusion for the subject is based on a market exposure time of so many days, which says in other words that for a property similar to your subject, if it were placed on the market for the number of days you give for exposure time, starting that number of days before the effective date of the appraisal, it would likely sell for a price most probably equal to your value conclusion. So, in other words, you are indicating that your concluded market value is also valid for other homes in similar condition, sold in the same time frame.

Now, of course, there may not have been any other similar home on the market during that time frame (e.g., eff_date_of_appraisal - exposure_time_in_days to eff_date_of_appraisal), so you are inferring this value and exposure time from surrounding data. Likely, such inferences of exposure time are rough estimates; however, you could add exposure time for all sales to your data set and regress on that as well, to derive a formula for the impact of exposure time on net sale price. Using earth, you might want to expect the model will have additional interactions - but the problem is that it will have major interactions with condition and appeal, which are not quantized in your data. Note that if you regress on DOM, you, in effect, obtain an indirect and approximate measure of market appeal. The problem with using DOM is that it has a lot of "noise," e.g., DOM is impacted by real estate agent motivation, competence, and general market condition changes over time (that is to say the impact on net sale price of an exposure time of say 90 days depends on the date of sale).

So if running MARS on a data set with DOM as a variable, we would expect to see an interaction between DOM (i.e. exposure time) and Date-of-Sale (e.g Sale Date), effectively making the variable DOM useless as a measure of Appeal (e.g. condition, quality, **, design, ...). Although, as appraisers, we know that a DOM that very clearly doesn't fit the pattern is a sign that something is amiss.

Note: Usually, only MARS can make sense of the tangled mess of inter-relationships.

 

[ZZGAMAZZ]

If/when the market demand is strong enough that a competitively priced property can be moved within the abbreviated time the values will be the same/similar.

How would you even go about developing a discount if/when the market is that hot?

I eventually did a search based on selling prices of properties with competing physical characteristcs condition notwithstanding, going back I think 700 days, within a busy market, and it just so happened thar the list when sorted by selling price revealed that the lowest half dozen were all discounted bc of condition but not necessarily status although status and fair/poor condition displayed strong correlation-- although Exposure difference wasnt pronounced.... as basis of my next question: is subject exposure usually similar to overall Market Exposure bc condition differences are reflected in value opinions that should offset any potential differences [ or maybe Everybody but Me always were aware...I.e., Epiphanies roll in slowly to a dull boy...

 

[ZZGAMAZZ]

Ummm... I don't see the problem. Your market value conclusion for the subject is based on a market exposure time of so many days, which says in other words that for a property similar to your subject, if it were placed on the market for the number of days you give for exposure time, starting that number of days before the effective date of the appraisal, it would likely sell for a price most probably equal to your value conclusion. So, in other words, you are indicating that your concluded market value is also valid for other homes in similar condition, sold in the same time frame.

Now, of course, there may not have been any other similar home on the market during that time frame (e.g., eff_date_of_appraisal - exposure_time_in_days to eff_date_of_appraisal), so you are inferring this value and exposure time from surrounding data. Likely, such inferences of exposure time are rough estimates; however, you could add exposure time for all sales to your data set and regress on that as well, to derive a formula for the impact of exposure time on net sale price. Using earth, you might want to expect the model will have additional interactions - but the problem is that it will have major interactions with condition and appeal, which are not quantized in your data. Note that if you regress on DOM, you, in effect, obtain an indirect and approximate measure of market appeal. The problem with using DOM is that it has a lot of "noise," e.g., DOM is impacted by real estate agent motivation, competence, and general market condition changes over time (that is to say the impact on net sale price of an exposure time of say 90 days depends on the date of sale).

So if running MARS on a data set with DOM as a variable, we would expect to see an interaction between DOM (i.e. exposure time) and Date-of-Sale (e.g Sale Date), effectively making the variable DOM useless as a measure of Appeal (e.g. condition, quality, **, design, ...). Although, as appraisers, we know that a DOM that very clearly doesn't fit the pattern is a sign that something is amiss.

Note: Usually, only MARS can make sense of the tangled mess of inter-relationships.

Just saw this post.

 

[ZZGAMAZZ]

I don't know what the problem is here. There have been well over 200 sales of SFRs in Apple Valley on parcels of 30000sf-60000sf over the last year and the median DOMs is at 29 days. Unless your client needs a more limited exposure time of 2 or 3 weeks (which I doubt) the Liquidation Value will be the same as the Market Value.

View attachment 104478

Now the median DOMs of 29 days is a little longer than the 21 days a year ago but these exposure times still indicate to a strong demand for properties that are priced competitively. The median price has increased very slightly Y-O-Y, too. (~$7000). Some appraisers would call that a shallow rate of increase, others would call it stable via rounding and distribution.

All RE is local, but in this region we usually don't even get into an oversupply until the median DOMs exceed 3 or 4 months. That's when only the most motivated sellers are getting the sale, which will usually require some discounting (aka price declines).

Every region works off its own clock. So while prices are being reported as declining in many areas of the nation that isn't the case in every area of the nation. Or in every pricing tranch. These are opinions for the appraiser to develop specific to the assignment at hand, not assumptions for the appraiser to make based off the articles that are being published and relating to other markets outside the appraiser's area of operations.

The Chat GPAT storyline about exposure described every premise of the analysis in context with AV data. Might have been 100% bogus of course because the data wasnt mine, but each time I challenge it about anything, the responses are spot on. Because of a similar thread on AF. I questioned it about its comments about acceptable SD's in appraisal theory... and it shot back with 15th version of RE Dict, specific CE courses.

 

[ZZGAMAZZ]

Ummm... I don't see the problem. Your market value conclusion for the subject is based on a market exposure time of so many days, which says in other words that for a property similar to your subject, if it were placed on the market for the number of days you give for exposure time, starting that number of days before the effective date of the appraisal, it would likely sell for a price most probably equal to your value conclusion. So, in other words, you are indicating that your concluded market value is also valid for other homes in similar condition, sold in the same time frame.

Now, of course, there may not have been any other similar home on the market during that time frame (e.g., eff_date_of_appraisal - exposure_time_in_days to eff_date_of_appraisal), so you are inferring this value and exposure time from surrounding data. Likely, such inferences of exposure time are rough estimates; however, you could add exposure time for all sales to your data set and regress on that as well, to derive a formula for the impact of exposure time on net sale price. Using earth, you might want to expect the model will have additional interactions - but the problem is that it will have major interactions with condition and appeal, which are not quantized in your data. Note that if you regress on DOM, you, in effect, obtain an indirect and approximate measure of market appeal. The problem with using DOM is that it has a lot of "noise," e.g., DOM is impacted by real estate agent motivation, competence, and general market condition changes over time (that is to say the impact on net sale price of an exposure time of say 90 days depends on the date of sale).

So if running MARS on a data set with DOM as a variable, we would expect to see an interaction between DOM (i.e. exposure time) and Date-of-Sale (e.g Sale Date), effectively making the variable DOM useless as a measure of Appeal (e.g. condition, quality, **, design, ...). Although, as appraisers, we know that a DOM that very clearly doesn't fit the pattern is a sign that something is amiss.

Note: Usually, only MARS can make sense of the tangled mess of inter-relationships.

Thank you. 1. Why would Date of Sale as a confounding factor diminish the significance of DOM as an independent variable? 2. But if so, could the impact be addressed by weighting the [presumably inverse] relationship? 3. Or [Please excuse this question, but...] if that premise is true, would the impact of Date "go away" if it is simply ignored in the equation??

 

[RCA]

Thank you. 1. Why would Date of Sale as a confounding factor diminish the significance of DOM as an independent variable?

I never mentioned confounding factors. DOM is NOT an independent variable; it is rather a derived, dependent, or resultant variable. DOM depends on the property characteristics and the listing date or date of sale. Date of Sale is a Primary Descriptor or Independent Variable for the Sales transaction.

You can consider causal effects. A specific DOM never implies a specific or likely Date of Sale for a single property or for a group of properties. DOM values repeat across many dates. However, a Date of Sale for a specific property or a group of properties implies a probable DOM value. My house might have sold in 1987 with a DOM of 30 days, it might also sell today with a DOM of 30 days, in the meantime the house was 1200sf in 1987 and today it is 3,000sf. And so what does DOM mean? - It depends on the context: If we have a specific property sold at a specific date, the DOM tends to indicate how difficult it was to sell the property for a given sale price in the context of the various DOM values at the time of sale for the neighborhood in question. So, if the average DOM for the Date of Sale is 2 days and the house took 90 days to sell, then we would expect that the house had major deficiencies or was grossly overpriced.

2. But if so, could the impact be addressed by weighting the [presumably inverse] relationship?

Imact of what? Yea, I don't think this question makes any sense.

3. Or [Please excuse this question, but...] if that premise is true, would the impact of Date "go away" if it is simply ignored in the equation??

I am not sure there is a premise here. What equation?

 

[RCA]

As a side note, questions relating DOM to Date of Sale would be excellent to include on an appraiser aptitude test. Confounding or collinear relationships, causal effects - can the candidate understand the nuances involved?

Appraisers often lack data analytical knowledge and statistics.

 

[ZZGAMAZZ]

I never mentioned confounding factors. DOM is NOT an independent variable; it is rather a derived, dependent, or resultant variable. DOM depends on the property characteristics and the listing date or date of sale. Date of Sale is a Primary Descriptor or Independent Variable for the Sales transaction.

You can consider causal effects. A specific DOM never implies a specific or likely Date of Sale for a single property or for a group of properties. DOM values repeat across many dates. However, a Date of Sale for a specific property or a group of properties implies a probable DOM value. My house might have sold in 1987 with a DOM of 30 days, it might also sell today with a DOM of 30 days, in the meantime the house was 1200sf in 1987 and today it is 3,000sf. And so what does DOM mean? - It depends on the context: If we have a specific property sold at a specific date, the DOM tends to indicate how difficult it was to sell the property for a given sale price in the context of the various DOM values at the time of sale for the neighborhood in question. So, if the average DOM for the Date of Sale is 2 days and the house took 90 days to sell, then we would expect that the house had major deficiencies or was grossly overpriced.


Imact of what? Yea, I don't think this question makes any sense.


I am not sure there is a premise here. What equation?

By equation I meant the formula for ml regression that I think is the basis of your premise re determine the affect of a variable on others [although IMO DOM is indeed an independent variable, with selling price as the dep variable]. Appreciate ur scholarly advice as always, trying to condense it into a practical application that I can apply. Regards.