Wednesday, September 24, 2014

Why is the most accurate free home valuation system today!

Traditionally, appraisers use comparable sales to value actual subject properties (having real house addresses with real property characteristics). The high costs of maintaining the subject population often gets reflected in less-than-adequate maintenance of the ever-changing sales population, thus producing obsolete comparable sales ("comps") and, in turn, outdated subject valuations.

Our solution demonstrates that a Defined (a.k.a. Simulated) subject ("subject") serves as good a purpose as an actual subject property, freeing up the hefty costs of maintaining the subject population. Our system,, - built on our solution - is therefore predicated upon empowering our users with a sophisticated yet easy-to-use methodology to define subjects, an up-to-date sales database, and an advanced comps matching and scoring tool so that the users can meaningfully undertake a series of experiments on-the-fly to arrive at their own value conclusions. In fact, in the process of defining their subjects, our users are essentially researching and duplicating actual subjects in their experimentation, without blindly relying on the often-outdated public record.

Additionally, unlike an institutional client, an average home buyer – in Free Home Valuation industry where we are positioned – is generally interested in valuing a handful of subject properties so researching and capturing such data tend to further motivate our users. 

Unquestionably, given the anemic health of most taxing jurisdictions nowadays and the falling tax base, subject populations are nowhere as up-to-date as they used to be in earlier years. In fact, the lack of field inspections by the assessing staff results in significant delays in the capture and inputting of the physical changes in the assessment system. Therefore, when a potential buyer or an investor depends on such subject data, the resulting valuations are generally less-than-perfect, to say the least. Alternatively, when a targeted subject is individually researched, inspected and manually entered – as is the case in our system – the resulting valuation becomes significantly more reliable.

The housing population consists of the (unsold) subject population and the sold population. Since only the most recent (one to two years) arms-length sales could be used as comps to value subjects, the general split between the subject population and the comp population is 95% and 5%. Considering our system accurately functions off 5% of the population, our system does not succumb to the data logistics, nor does it require a fortune in terms of investment in maintaining the data, allowing us to remain focused on updating the sales data and enhancing the technology to keep our visitors enticed.

Homequant system consists of two separate yet complementary modules: Valuation (micro) and Sales Query (macro).

Valuation Module

We are aware that sales by themselves are not comps; they have to be equalized and converged to the subject to become true comps, so the Homequant system has been built to provide for an excellent adjustment mechanism that users can experiment with and generate the optimal comps. In the process, we adhered to the strict market economics by attaching the highest importance to the location, followed by the property characteristics.

Defining Subject

In terms of the location, it is top-down, meaning users have to first select the county, then the city/town and the zip code and finally the actual address. For example, if the user is valuing a subject located at 46 John Street in Forest Hills, Queens, New York, s/he has to select Queens, Forest Hills, and Zip code (11374 or 11375) and then enter the street address, thus prompting comps to align with that location vertical. As the actual address is entered, a ‘validate address’ button below will pop up. Once the address is entered and the validation button is pressed, the address will be internally validated against the Google Earth database. If Google Earth finds a match, a new pop-up will confirm, absent which the address requires rework.

In terms of the property characteristics, Homequant uses the three most important continuous variables, namely land size, building size, and age (derived off of year built). Therefore, Homequant requires users to enter these three values. The subject definition is complete once the location and these three property characteristics values are entered.

Comps Selection

Of course, the most important exercise in Valuation is to select the right pool of comps. Once that’s done, Homequant adjusts, equalizes, ranks and finally returns the five best comps. In the process, Homequant requires users to select an appropriate comps selection range, between 10% and 40%, in order that an internal matching algorithm can pool and return the best five comps from the defined range. If a user selects a 10% comps selection range, comps within that land size, building size and age range of the defined subject would be evaluated for pooling. For instance, if the subject has a land size of 4,000 SF, building size of 1,500 SF and age of 50, comps between 4,400 and 3,600 SF in land sizes, 1350 and 1650 SF in building sizes and ages 45 to 55 would qualify for pooling. Needless to say, only those comps that pre-satisfy the location criteria would qualify for pooling as well.

Distance Radius

In addition to selecting the comps from a defined range, they must come from the vicinity within the subject’s location vertical. In other words, all factors remaining equal, comps that are closer to the subject are the better comps. In line with this established market theory, Homequant provides a ‘distance’ option allowing users to restrict the inflow of the comps between one and five miles. Alternatively, in rural counties where comps could be far apart, this option might be easily bypassed by selecting ‘none.’ Either way, this is a critical option in comps selection, without which the comps closer to the subject could be overridden by the distant ones.  

Comps Dollar Adjustment

In certain illiquid housing markets – for example, million-dollar-plus and waterfront – comps are often few and far between, forcing a much wider selection range – say within 30% of the subject’s. In those circumstances, comps require dollar adjustments. Homequant allows separate adjustment coefficients for land, building and age. If the subject sits on a 10,000 SF lot and the first two entering comps carry 8,000 and 12,000 SF respectively, then the first comp would be adjusted up (+) 2,000 SF, while the second would be adjusted down (-) 2,000 SF. If a land adjustment coefficient of $10 is chosen, $20,000 would be added to the sale price of the first comp, while $20,000 would be subtracted from the sale price of the second comp. This adjustment process would repeat for the building size as well as age.Without the proper selection range backed by the proper dollar adjustment, sales do not necessarily become comps to value a subject. Homequant’s competition in the free home valuation industry fails to recognize that and provides no such mechanism, thus forcing users to settle for eyeballing comps, coupled with unsound quantitative judgment.

Time Adjustment

Housing market is very dynamic, causing prices to be volatile – prices take off or swoon within a very short period of time, so two similar home sales nine months apart are not the same; they require sound quantitative time adjustment. An educated customer knows the dynamics in the market, meaning if the prices are on upward or downward trajectory. If the prices moved up 10% over the past one year, the older sales must be adjusted ‘up’ for time. Likewise, if the prices declined 10% year-over-year, older sales must be adjusted ‘down’ to be usable as comps. Homequant allows both positive and negative time adjustment to cure sales for time.

Valuation Date

Many valuation professionals – money managers, appraisers, assessors, etc. – need to value subjects for a different valuation date, other than the current period. Assessors often have a backward taxable status date; money managers often reprice a portfolio for a backward date; economic analysts often need to revalue properties for a forward date. Homequant allows valuation for all three valuation dates – current, forward and backward. On 11/1/2013, if a user wants to value a subject for 12/31/2013 projecting 1% monthly growth in prices, Homequant will automatically calculate the time-adjusted value as of that date – no additional entry or gyration will be needed. For the current and forward dates, all sales will be adjusted up, while for the backward date, all newer sales beyond the valuation date will be adjusted back. Again, Homequant’s competition in the free home valuation space does not offer any mechanism to adjust for time, let alone allowing flexible valuation dates.

Ranking Method

Once the comps are pooled, adjusted and scored they need to be ranked. Homequant provides three different methods: distance, sale date and least adjustment. When ‘distance’ is chosen, the qualified comp which is physically nearest to the subject is comp 1. If the ‘sale date’ method is chosen, the qualified comp with sale date closest to the valuation date becomes comp 1. Under the ‘least adjustment’ ranking method, sum of all dollar adjustments, including time adjustment, for each comp is compared and the one with least adjustment becomes comp 1. In evaluating the least adjustment amount, +/- signs are ignored. In other words, a total adjustment of $1,000 will supersede -$6,000.  While the distance and sale date methods are meaningful for the non-professional users, the least adjustment method would be a powerful tool for the professionals and advanced users.      

Minimum Comp Requirement

Homequant requires a minimum of five comps to value a subject so users would probably start at the bottom of the selection range, i.e., 10% and gradually work up depending on the results obtained. If less than five comps are pooled, a slider is provided to adjust the curve in increments of 5%, just like in the manual input box, to avoid having to manually enter into the boxes. In order to allow more qualified comps to come in, the distance could be increased, say from one mile to two miles, in combination with the widening of the selection range. For example, if the initial selections range of 10% across land, building and age and distance of one mile returned only two comps, the range could be increased to 20% and the distance to two miles.

Quantitative Output

Once the five comps are accepted a comps grid with details of each comp as well as the adjustments would be produced. Specifically, the grid would show the exact location including the street address of each comp, physical attributes in terms of land size, building size and age, sale price and sale date and the overall adjustments made to sale price to generate the adjusted sale price which, in turn, becomes the comparable metric, after having neutralized the physical and market differences in them. In order to study the output multi-dimensionally, the output table may be sorted by any of the columns listed there by simply clicking on the column header. This sorting is restricted to this output table without affecting the ranking method which controls the final comps grid. 

Spatial Output

All sales are geo-coded with Latitude and Longitude coordinates before uploading on to Homequant, paving the way for precise spatial views as well as concise spatial outputs. The final five comps – and the defined subject – are simultaneously shown on a Google Map, allowing users to visualize - and swap - their prior selection. In fact, this gives them a renewed chance to revise and anchor their final five, before moving on to valuing a different subject altogether. Alternatively, this spatial view also helps them understand why the fifth comp, for instance, had sold for 30% higher than their peers (perhaps, close to a lake). An educated user would instantly disregard that comp from the line-up, despite having met the basic size, distance and location criteria. Since Google Street View is also integrated on the same output, they can also view the actual homes as well as their surroundings.  It is very useful for the remote buyers researching into the area.

Comps Grid and Subject Value

The comps grid - which follows the selection of the final five comps - would be ranked by the ranking method chosen by the user. Simply put, if distance is the chosen as the ranking method, the comp that is physically nearest to the subject would show up in the grid lineup as comp 1. If no ranking method is chosen, the default method - Sale Date - would rank the grid.

In addition to the grid, a complete percentile distribution analysis of the full spectrum of the Adjusted Sales Price (ASP) has been provided right underneath the grid, thus translating the isolated sale prices into a market snapshot of where the probable values could be for the various interest groups. For example, an aggressive investor might consider a range between the 5th and 25th percentile, while an informed home-buyer would probably consider the 25th to 75th percentile as the most probable range, with the median (50th percentile) ASP being the most probable indicator of the market price, singularly, and so forth. 

Again, Homequant’s competition in the free home valuation space does not offer any mechanism to tabulate the selected comps on a grid or to statistically analyze them collectively.

Sales Query Module

In addition to valuing individual subjects, Homequant also offers a macro choice, called Sales Query, to help users understand the broader market. Users can learn a great deal of a specific market or a group of markets in many different permutations by spending a few moments here. In fact, the Valuation and Sales Query modules are designed to complement each other, without any unnecessary duplication of themes. Case in point: When a user is uncertain of the value parameters of a set of comps, s/he can visit this macro module to see how the results from the comps compare with the universe they are drawn from. If the user wants to learn more about the Forest Hills (NY/Queens) housing market before toying with individual subjects, s/he would go to Sales Query and run the global stats there.

Since sales as old as one year ago are included in the sales database the same time adjustment and valuation date options are incorporated in Sales Query. Again, in valuation date, the default is the current date so all sales would be time adjusted to this date (assuming a time adjustment factor is entered). Likewise, a forward or a backward date could be experimented with. When a time adjustment is sought, the output box would show different values between Sale Price and Adjusted Sale Price. If no time adjustment is sought, they would be identical. In Valuation module, the Adjusted Sale Price comprises of the sum of the feature-wise dollar adjustments and time adjustment, while in Sales Query, Adjusted Sale Price includes only the time adjustment component considering there are subjects here.

Sales Query output is simultaneously displayed on the Google Map as well, allowing new users to see where the selected node is located within the county.

To summarize the merits of our solution – the Homequant free home valuation system: 
  • Homequant solution is predicated upon the premise that user defined and researched subjects are as good, if not often better than the subject data from the public record which eliminates the need to maintain the gigantic subject population. It also translates to a significant saving in working capital that is otherwise better utilized in maintaining an updated sales population, resulting in more up-to-date sales and thus more accurate values.
  • Homequant solution – combining user-defined subjects, an up-to-date sales database, and an advanced self-directed tool (subject definition and comps matching, adjusting and ranking) – optimally empowers users, allowing them to arrive at their own value conclusions, objectively and iteratively – a far better approach than offering some model-driven frozen values that no one could decode.
  • Homequant recognizes that selecting comps from a given location or strata is not enough so it allows dollar adjustments to the size of the land and building, as well as to account for the annual depreciation of the building.
  • Homequant recognizes the ever-increasing volatility in the market – rapid rise and fall in prices – and therefore allows an effective time adjustment mechanism.
  • Homequant recognizes its audience comprises of professional and non-professional users so it provides for variable – current, forward and backward – valuation dates.
  • Homequant recognizes that the traditional ranking of comps by the distance alone is inadequate for the advanced users, so it provides for additional ranking methods like least adjustment and sale date.
  • Once the final five comps are scored, ranked and accepted, they are tabulated on a traditional appraisal grid, allowing professional users to relate to their comfort zone.
  • In addition to traditional value parameters like average and median price of comps, Homequant offers a full percentile distribution curve to accommodate advanced and professional users as well. Many advanced users like money managers, loan officers, portfolio analysts, etc. appreciate the addition of the percentile distribution.

While Homequant is not a full-blown property valuation system, this is however the most advanced valuation system available in the ‘Free Home Valuation’ space today to:

1. educate novice users to understand the local housing market more objectively,

2. offer a good bottom-up second opinion to the non-professional yet well-informed users,

3. help advanced retail users like home sales and mortgage professionals get a quick preview of a subject valuation, from anywhere,

4. help sophisticated wholesale users like real estate analysts and portfolio managers quickly sample the value of a given portfolio,

5. help assessment review officers and appeals/hearing courts determine if full-blown professional appraisals would be required.

So, how does Homequant's "Defined Subject" concept help the Valuation Community at large?

Often, the Valuation Entrepreneurs fail to make inroads into the Valuation business due to the high cost of the unsold  population data which tends to be about 95% of the entire population. Because of Homequant's discovery of the "Defined Subject" - meaning user-defined subjects - those entrepreneurs can jump into the business now, knowing full well that the sold data alone - generally available free of cost or for a token price from the taxing jurisdictions - would do the trick, without having to invest a fortune in acquiring and warehousing the unsold data which, in terms of quality, is questionable at best, to begin with.

The President of Homequant recently explained our invention: “There are roughly 90 million single family homes in the US and, on average, 5% of that universe annually sells. By inventing the concept of the user-defined subjects, we are able to value those 95% unsold properties by storing only the 5% sold data. The home valuation industry will soon recognize the significance of our invention.”

In a nutshell, the Homequant solution provides a very realistic – yet advanced – solution to the pros and non-pros alike by perfectly bridging the gap between the pseudo free home valuation sites showing only a list of comps and the enormously expensive professional appraisal systems.  

Try it. You'll love it! 

Here is the site address:


Sid Som MBA, MIM
Homequant, Inc.

Additional reading:
How to value a subject on Homequant site (step-by-step): 

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