Bye-bye 1004MC, Hello Analysis
- Who Are You Going to Call? - October 22, 2018
- Bye-bye 1004MC, Hello Analysis - August 17, 2018
- Paint a Picture with Words - July 2, 2018
On July 31, 2018, at the Appraisal Institute Annual Conference, Fannie Mae announced the end of the 1004MC. News quickly spread among the appraisal blogosphere, and on August 7, 2018, the new Selling Guide showed that the 1004MC was no longer required.
Rejoicing was heard throughout the land.
Although the 1004MC is no longer required by Fannie Mae, the appraiser still needs to support their opinion of market trends, supply and demand, and marketing time. The exact verbiage found in the 8/7/18 updated Selling Guide is:
The appraiser’s analysis of a property must take into consideration all factors that affect value. Because Fannie Mae purchases mortgages in all markets, this is particularly important for neighborhoods that are experiencing significant fluctuations in property values including sub-markets for particular types of housing within the neighborhood. Therefore, lenders must confirm that the appraiser analyzes listings and contract sales as well as closed or settled sales, and uses the most recent and similar sales available as part of the sales comparison approach, with particular attention to sales or financing concessions in neighborhoods that are experiencing either declining property values, an over-supply of properties, or marketing times over six months. The appraiser must provide his or her conclusions for the reasons a neighborhood is experiencing declining property values, an over-supply of properties, or marketing times over six months.
When completing the One-Unit Housing Trends portion of the Neighborhood section of the appraisal report forms, the trends must be reflective of those properties deemed to be competitive to the property being appraised. If the neighborhood contains properties that are truly competitive (that is, market participants make no distinction between the properties), then all the properties within the neighborhood would be reflected in the One-Unit Housing Trends section. However, when a segmented or bifurcated market is present, the One-Unit Housing Trends portion must reflect those properties from the same segment of the market as the property being appraised. This ensures that the analysis being performed is based on competitive properties. For example, if the neighborhood contains a mix of property types not considered competitive by market participants, then a segmented or bifurcated market is present. The appraiser should also provide commentary on the other segment(s) of the neighborhood when segmentation is present.
What does this mean to the residential practitioner operating in the mortgage space? It means that the requirement for analyzing the market remains, and it is now up to the practitioner to support their opinion, without the benefit of a flawed format. Appraisers can now choose how they present their analysis, which may include multiple sources to support an opinion. Fannie Mae is clear that the one-unit housing trends section should reflect properties that are directly competitive with the property being appraised. The following information relates to several different ways to support trends, but is not an exhaustive list.
Appraiser developed trends
The data array above considers all sales other than the “to be built” properties in a specified school district, over a 20-month period. The sales are run year-to-year, advancing on a monthly basis. This way it is possible to see changes in a subtler manner as opposed to year-to-year study, when related to any adjustments that are made for changing market conditions. For example, comparing a property that went under contract in April 2018 to the appraisal effective of August 13, 2018, lines 16 and 20 would be compared. This can be used in combination with the submarket chart, to see what is happening with the market. Ideally both median prices and price per square foot are analyzed.
The columns in the chart relate to the timeframe, number of sales, the median list and sales prices, the list to sales price ratios, gross living area (GLA) and price per square foot (PPSF). The reason that GLA and PPSF are included relates to changes in size affecting sales prices. The final two rows in the chart relate to how many listings are active and under contract as of the date of the study, referred to as the “contract-to-listing ratio” which is relevant. In my opinion, this is one of the most relevant pieces in the analysis, as indications of change are noted before sales close. It also supplies information related to supply and demand.
Laying the sales price information out in a chart can help the visual reader as well.
It is evident by observing this data, that the market has increased over time — from $328,000 to $355,000 or 8.23% (row 8 to 20) — but in the past year, not as substantial an amount, from $349,900 to $355,000 or 1.46% (row 8 to 20). Price per square foot has increased from $148.08 to $160.49 over the 20-months period (8.38%), and $156.72 to $160.49 year to year (2.41%). What this shows is that, although there was an increase of over 8% in the measured period, the past year does not show as marked an increase, and it could be construed as stabilized or stabilizing, based on the appraiser’s analysis, in particular after studying the current contracted sales.
There is another piece to this puzzle, and that is how many houses are showing as under contract in this macro market, and what the supply looks like relative to demand. This is the “contract-to-listing ratio” which shows 90 houses on the market total, with 22 under contract. This is a ratio of 24.44% in this segment. Through employing this type of analysis on each appraisal report completed, it is possible to see a shift in the market start to occur, before sales prices reflect it. In my market, 24% of sales under contract is indicative of a normal market, one that is neither favoring buyers or sellers. What is also extremely meaningful is the listing prices of the houses under contract compared to the listing prices of the previous segments sales. The listing prices of those properties under contract are now $10,000 lower than the list prices of the previous period, in spite of a small increase in median size. This tells us that we may have a price correction occurring, but before closing, we cannot be certain. We can however use this information and explain to our client, what we see happening in the market.
Fannie Mae wants to see the specific market segment, and not necessarily the macro market — although that is relevant as well since understanding the larger macro market is necessary before an assignment specific market can be analyzed. The submarket in this instance shows an increasing market in prices, but the median asking prices of the contracted sales are 13.33% lower than the asking prices of the previous segments sales. This is in part due to a decrease in median gross living area, and also in part due to a much smaller segment of data for analysis. Nevertheless, the market also shows a greater absorption of these properties than the macro market as the contract to listing ratio shows over forty percent of the properties offered as under contract. We could easily see this market as either stable, or still increasing slightly. It is up to the appraiser to explain their thought process on the conclusion of market trends.
It is possible to structure something similar to what is reflected in the chart above with whatever is considered relevant by the appraiser doing the analysis. The appraiser might wish to do year-to-year, month-to-month, monthly, weekly, or whatever period the appraiser considers relevant. Whatever is chosen provides support for the appraiser’s opinion as to market trends. In the event of a change in the market, we have some evidence-based data supporting our market trends conclusion.
As much as we might want to rely on our own data, there are other sources available that can also help with a determination of market trends. Using the same hypothetical property above, it is easy to pull various sources such as Realtors Property Resource (RPR), Realist, Trulia, Movoto and others.
The RPR sample below uses a sale in the same area above, and shows the following graph. The property price increased over time, but is generally stable over the past year. The zip code shows an increasing price, and the county prices increasing steadily, as to, the entire state of Michigan. This is useful additional data to include either in the report itself, or in the workfile for posterity.
Most appraisers have access to both RPR and Realist via their MLS. An example of market trends from Realist is shown below. This data is not related to the subject submarket, but does include the zip code and city, as well as county, showing mixed trends data compared to the appraiser developed data addressed above. If one relies on this information, the market shows as increasing after a dip over the winter.
Trulia, Movoto and other similar applications are not able to differentiate between the submarket and the overall market, but are useful and provide additional sources of support. Movoto enables the user to observe data trends over different segments of time, and by price per square foot as shown below. It also allows segmentation between single family properties and condominiums. Examples of properties in the same market as the sample discussed throughout this report are shown below.
(snapshot from Movoto on price per square foot over 2-years)
Trulia allows the user to identify the number of bedrooms, or include all sales
(snapshot from Trulia for Dexter)
Another way to support change is to observe sales that resell in a defined period. This is particularly useful when the subject property has a recent prior sale. It helps provide a basis for where the property was at the time of the prior sale, compared to the market today. Most MLS have a data export ability, and it is simple to set up a search within your parameters, observe any sales that resold, and then compare possible changes between the sales periods. My research in this market isolated two sales that were within my search parameters over a 2-year period. One set sold 4/17/17 at $399,500 and then again on 4/9/18 for $647,500. That is an increase of 62% and unlikely market appreciation. Looking at the MLS comments and photos, the difference relates to the first sale as a more original property, somewhat tired to today’s standards. The second sale shows a gut-rehab with HGTV style bling. I could use this sale/resale as evidence of value added for a significant remodel, but would not want to rely on it for market change.
My second set of data included a property that sold 8/9/16 for $411,500, and then again on 6/27/17 for $439,000. This is an increase of 6.68%, but the most recent sale was over a year old. The only change noted was a new roof in the interim. Given the data shown in the charts above, the increase was in line with the submarket increase and is further support for the increase that was occurring before January of this year, but does not provide good information for the current trends.
All of this information combined can help support the opinion of where the market is as of the effective date. More importantly, it can help defend the report in the event that the market changes and the appraiser is accused of having ignored market conditions that were noted at that time.
Many participants in the market are concerned there is a shift that is inevitable, either on the immediate horizon, or off a few years. In any event, with the elimination of the 1004MC as a requirement, appraisers are not absolved of supporting their opinion of market conditions at the time of the appraisal report, and all of these tools, and others, are available to the appraiser to better help support the decision.
Let’s view the elimination of the 1004MC as an opportunity to really shine and support our work. After all, we are the neighborhood experts, but we need to be compelling in our decisions when faced with increased computer models and data alternatives. This is our opportunity to show the value that we bring as analytical researchers.
Thanks Rachel. Yes FNMA wants what is similar to the subject and FHA wants the entire market.
Because FHA wants ‘market data’ and FNMA wants carefully screened and selected data. Data which on the basis of conformity alone would tend to suggest the quality of their portfolio is better or less risky than one in which broad price ranges; ages and quality levels were found. One that may suggest a subject could be nearer the bottom of the neighborhood ‘barrel’ than the top or middle.
What FNMA wants for the neighborhood section is misleading. FNMA says to use one set of sales for the housing trends (comps), but use a whole different set of sales for housing price and age. Comps for one section, all homes for the other. FHA approach is the classic approach.
One useless form down now move on to the next (2005). And how many years till the clients we perform appraisals for actually stop asking for this useless form?
A very informative article. Thank you.
However, I can not but help to remember the clear capital hybrid product thread from only several months ago, and the dailies which came after.
If I recall correctly, well, it’s difficult to reconcile the fact these emerging product lineups are absolutely not in compliance with these sensible guidance points.
Nice. I would caution that median list price of a set of data divided by median sale price of a set of data is not the same as the median sale to list price ratio. The latter calculates the ratio before identifying the median of a set of ratios. The results are different. The same context is lost when taking the median sale price and dividing that median by the median square foot. That is not the same as the median sold price per square foot. I am not trying to be argumentative. I am attempting to illuminate that the sequence of calculations should be clarified in the column labels.
Thank you Dave, and I would love some help understanding the process since I must not be doing it right (although at least it is consistent). Could you please provide some examples? All of the people reading would benefit as well. Good to learn new things.
The median list price is constantly changing. One of the most active changes in M.L.S. is the number of times listing price will have changed before sold. After the sale, the List price ratio becomes stable. At any one time during the listing, this may be is a hopeful indicator, it may be cursor of the future, however our date of value is in the past under the FHA or the FNMA definition.
Yeah, take care with that though, the various MLS systems have varied ways of calculating MC list vs sale figures. Some populate the MC data with anything listed, even if withdrawn and not successfully sold, possibly skewing result. You’ll likely recognize this due to mismatching numbers where the final % number is not indicative of a simple division analysis of the two list price and sales price numbers populating that time block. I find that looking at list vs sale for about a half dozen to dozen individual units provides more illuminating perspective.
I download the MLS data into excel. his allows me to sort and graph the data. I might take 200 items from the chosen neighborhood of active, pending, contingent and closed items.
These items can be re configured sorted and conclusions taken from these individual processes. The weakness of large data is ever present, and ever self correcting.
In the past I used Don Manchowitz? algorithm which was available free on the internet
Sounds like more work. I just filter within MLS then pop up the MC, and then recalculate a proper median list and ratio. Easy. It all depends on what your local MLS offers. It’s not yet mandatory to have to scrape data into excel and other programs, hopefully never will be. Intuitive market research. Something only experience brings. Don’t get too bogged down in the tech or you’ll miss the real property picture. Cheers.
Sounds like you meant to say Bagged down. The two MLS’s used had easy access. They allowed special items to be put into excel for the downloads. The sorts and the graphs were as easy as excel the thoughts took a minute more.
No longer an appraiser. Just interested in my profession for the last 50+ years
The lead article is about trends.
But I never hear anyone talking about how the fed purposefully depreciates currency 2-3% yearly, and plans on doing that year over year.
I know it may be difficult to understand but the federal reserve seeks prosperity through debt, by devaluing your currency.
Anyways, nobody talk about cash equivalency and a manipulated lending rate, inflation or fiat currency, perhaps you’ll make better sense of the lending markets than I’m able to. Cheers.
Rachel, I hope you know by now that you are one of my favorite appraisal authors to read. Seriously. I have tremendous regard for your experience, skills and opinions. Much of what you have written is spot on, but there is a fundamental flaw arising from an assumption in one area above.
PRIOR to FNMA adopting the misguided 1004MC appraisers did NOT measure neighborhood trends by the subject property. It simply did not happen, and the rationale or reasons for doing that by FNMA was just more of flawed practices that reduced overall appraisal quality. Comparable sales didn’t even enter the picture until the sales comparison approach was being performed. A neighborhood analysis was just that. It was independent of ‘comparable’ sales until after the sales reconciliation and maybe even final reconciliation where we then explained ‘how’ the subject fit and was perceived within its neighborhood.
The whole point of a neighborhood analysis is not to isolate comparable property (at least not initially). It is to identify HOW the subject property relates to its neighborhood. Does the subject conform in terms of price, size, quality and condition? Is it an over improvement? Is it an under improvement? HOW does the subject fit in the neighborhood?
Many markets have extremes in value. Huge extremes. When we ignore this and only consider similar property in the neighborhood analysis we are actually producing misleading results. Investors may be lead to believe a compatible degree of homogeneity exists, that simply does not. They may rate the investment lower risk as a result. A brilliant, albeit dishonest move on FNMAs part if intentional.
The minute FNMA forced us to change our core neighborhood analyses to hopefully better fit the fatally flawed 1004MC & their UCDP data-gathering plans it also negated the benefit and purpose of neighborhood analyses.
We substituted a limited and flawed analysis of only those properties in the neighborhood that are ‘comparable’ to a subject for a meaningful neighborhood analysis. (I’ll hold off confusing this with a competitive market area analysis which would or could effectively be the same thing).
Instead of looking at the entire picture, we started looking through a straw at only selected segments of it. We effectively eliminated micro economic analysis from the appraisal.
We allowed data scrubbers and software pushers to virtually eliminate the one condition of the market that they cannot reconcile with automated data. That was the REAL MARKET itself!
The ‘market’ that had a price range from $250k to 1.5k; had industrial presence and commercial uses; poorly maintained and above average maintained housing. One that had entry level housing as well as step up housing. A real market area-not a fantasy one.
A little ‘secret’ about markets. Agents historically never only showed certain category houses to clients.” We” (I used to be one) always tried to ‘bracket’ those. One we knew was inferior and no chance of being bought; one that was superior and too costly to buy, and lastly the one we hoped to sell based on our interviews with the buyers. Admittedly this was before the current batch of agents that seems afraid to meet with their clients in person, & in advance as a condition of showing them property. Before the days of “go drive by” and let me know what you think agents; & internet ‘lists’.
Thanks Mike, I certainly appreciate your thoughts on this. In the article, I tried to address the requirements from the Selling Guide, as well as macro data. There are two charts directly culled from a sample, which includes both the macro data and a submarket that would be similar to what Fannie Mae requests. There are also some charts here with larger macro data from sources such as Trulia and Movoto, which is useful to include. I find also that RPR has good data. The point is, that we want to have support for whatever we decide the market is doing, be it the submarket, or the macro market, or both. For my appraisal reports, I like to analyze both, because you have to know what is going on in the wider market to have a good grasp of the submarket.
Thank you for your kind comments and thoughtful discussion. We truly do need to reach out and try to help each other in order to stay relevant, and out of trouble 😉
I fondly remember the 1004MC as the beginning of the carnage way back in 2009. Adios 1004MC…may you ferment in Hell.
Still using the MC. I like it. It’s easy and satisfies the standard if accompanied by some market data and what not.
Still using MC and some of the clients out there still request this, now in a special SOW statement they just added on. It’s simple, convenient, and helps structure meaningful research approaches. It’s not always on point, but if you take the time to narrow and play with data, most of the time it’s a great tool to use. MC could have used more detail, a UC populace slot, room for a larger data set or supplementary additional MC, and honestly would have been better implemented if there was no data correlation to the figures in the MC vs the figures in the 1004 form. Sometimes I have to still fill in the MC w/ above grid figures, even though I’ve posted a supplementary MC which better expressed trending. This is because automatic review tools seek to match the consistency of entered data.
The above grid 1004 figures are for best expression of value range for this particular segment of properties. The MC is for best expression of market price and value trending. The two considerations are not just automatically the same, no matter how the non licensed tech crews program automatic report review protocols. Tech advancement people in the appraisal industry know just enough to be dangerous and disruptive, only rarely are they actually helpful. Don, bumping the thread. More people should bump older commentary threads, this website is rich with informative data.
I have a sneaking suspicion someone did not plan out the unintended consequences which come with tinkering of appraisal process and demand for increases in production volume… Waiting in line for another full fee client. Long lines, bummer. 3 out of 4 appraisers would rather freeze to death in line rather than work with amc’s. Perspective my dear Watson, perspective.
Remember gang your sub-market THAT MUST BE DISCUSSED is defined as the radius set by the most distant Comp. This MUST be discussed.
Wow , what happened to collecting fee, and charging enough? good stuff from Rachel!
We’ve changed a lot in our thinking, much brought on from more intense information. Used to think the longer on the market the higher the price, better information from lp/sp ratios clearly illustrate that the properties only sell within 3 or 5% of their FINAL listing. I quit FHA et al when the client dictated girding 3 listings. Most Realtors won’t report contingent sales because the deal might queer.
Realist is a wonderful tool. You can search by PRICE (priced over 5 million, or a geographical neighborhood) McMichale, a pioneer thought that price was one of the best indicators??, many listings agent do also. Sometimes we have to illustrate our position in an unpopular manner.
Downloading realist data into a familiar spread sheet allows us to illustrate spreads of raw data into usable & sensible information.
Sorting comparable info by Sq Foots and then re, re re sorting into differing scenarios illustrate a situation before we have to graph. Downloading the in altered Spread sheet into the report may add a few pages but illustrates the repeat-ability which is the all important report quality
Not really – graphs are only good relating to sub-market trends – anything else is bells and whistles. Incidentally, those graphs are RARELY properly explained or defined.
Ain’t nothin right on, most reports require a lots of words, many writers won’t.