Sunday, October 28, 2018

A Step-by-Step Guide to Home Valuation with Comparable Sales

Step-1: Define the Subject

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Once you zero in on a particular property you are interested in ("Subject"), compare the listed data (MLS or other listing services) with the County database (public record and available online). If they are at variance, call the Assessor's office and ask for an explanation. Land data could differ slightly as more and more public offices use GIS algorithms, while sellers/listing agents would extract the data from the original documents, potentially paving the way for limited discrepancies. Building SF and Year Built must be close, if not identical.

Step-2: Define Comps Criteria

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Comps criteria collectively is a function of the sub-market (greater neighborhood) the comps would be drawn from. In a very liquid market (with enough recent arms-length sales) the range could be tighter and vice versa. Since the comps must be similar to the subject in physical attributes, a set of selection ranges needs to be defined; similarly, adjustment rates are needed to equalize the differentials. For example, while the subject is 2,000, the comps could range between 1,600 and 2,400, thus requiring dollar adjustments. The 2,400 SF comp must be adjusted down to 2,000 SF while the 1,600 SF must be adjusted up, at the local replacement cost new($100/SF in the example). The rates could be significantly higher in expensive coastal markets while lower in rural areas.

Since the comps database might comprise an admixture of older and newer sales (generally 12 to 24 months depending on the liquidity of the market), all comps must be time-adjusted to a particular valuation date, thereby making sale dates for the pooled comps irrelevant. Once time-adjusted, there is no difference between two sales occurring in two different quarters. The sub-market in the above example did much better than its peers so an annual growth of 12% (1% per month) has been used to adjust all sales up to the valuation date. This piece of research (collecting the growth data at the sub-market level) is important. In a declining market, the adjustment would be negative meaning decay in value. Any quality market-oriented application would allow all three valuation dates: current, forward and backward.

Step-3: Select Comps

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Based on the selection criteria set forth, most self-directed valuation systems will return a pool of up to 10 most recent comps, five of which will eventually contribute to the subject value. I am using the Homequant system as I own and operate it, to avoid having to deal with any copyright issues. These are Homequant system requirements (a pool of up to 10 and 5 comps to value a subject). You may find another system online with different scoring requirements (choose the one that works best for you).

Assuming you have more than 5 (in our example, we got all 10), you have to evaluate them and choose the best 5. There are three most common methods to evaluate the pool: Distance (comps that are closest to the subject), Recency (most recent sales) and Least Adjustments (comps that require least adjustments, ignoring signs, that is, -2,500 and +2,500 are considered identical contributors). We chose the Distance method; in other words, we chose the 5 comps that are closest - in linear distance - to the subject. Of course, before you start the evaluation process, remove the two outliers, as a rule: the two comps with minimum and maximum adjusted sale prices; in the above example, comp # 1 and 10 are the two outliers. Again, removal of outliers is possible if the pool contains more than 5 comps. Notice that the lineup of the resulting 5 comps looks statistically meaningful.

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Irrespective of the evaluation methodology being chosen, comps must be simultaneously reviewed spatially, meaning reviewing the precise location of the comps on the map is equally important. The reason is simple: often, despite meeting the distance criteria, certain comps might come from incompatible yet contiguous neighborhoods. For example, since our subject is away from the lake, comps from the lakefront block (comps #7) would be inappropriate, although the distance criteria could have been met. Therefore, the spatial review of the comps is critical.   

Step-4: Analyze Final Value

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The final valuation picture is generally depicted via a tabular form called the Comps Grid. It's a line item comparative analysis of the subject vis-à-vis the final five comps that contribute to the subject value. It shows the neighborhood(s) they are drawn from, respective distances from the subject, property characteristics with dollar adjustments, and the sales complex including time adjustments. All of this collectively translates to the subject value. The most probable value is usually the median value of the adjusted sale prices of the five comps, while the most probable value range represents the statistical bound between the 25th and 75th percentile values. Of course, these parameters are specific to the Homequant system and may vary by the application or the target audience. For example, an alternative system that is geared towards the short-term investors might expand the probable value range to the 5th and 95th percentiles, thus revealing the potential short-term investors' entry and exit points. 

I picked the above graphics from as I own and operate it, to avoid having to deal with any copyright issues. My Homequant site is totally self-directed (no modeled values), totally free (no strings), and requires no login or registration whatsoever. Please choose the self-directed site that works best for you.

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