Sunday, June 3, 2018

A Good Home Valuation System Allows Least Adjustment Method alongside Distance and Sales Recency

Of the three popular methods to evaluate comparable sales ("comps") - distance radius, sales recency and least adjustment - least adjustment is the most powerful method. 

Since most comps are pooled from a limited distance within the same neighborhood and older sales are generally time adjusted, distance and sales recency become less powerful methods than the least adjustment. 

1. Least Adjustment

(Click on the image to enlarge)
The comps that require the least (quantitative) adjustments in terms of time and attributes are generally the best comps (in the above example, Least Adjustment is derived off the 'Total Adjustment' column). Remember, while determining least adjustments, signs are always ignored; therefore, +$3,000 and -$3,000 are tied. 

Also, when the scored pool is large enough (a pool of 10 comps is considered large), it is advisable to remove the two outliers (i.e., comps with lowest and highest adjusted sale prices - # 3 and 5 in this example) before applying the selection. 

2. Distance Radius

Based on this method, five comps closest to the subject (in linear distance) are selected. Notice that the outliers didn't influence the top five here.

3. Sales Recency

Obviously, this method requires the selection of the five most recent comps (in terms of the Sale Dates), post removal of the outliers.

Again, since Distance and Recency are already baked in the scoring, they become less powerful as final comps selection methods than their Least Adjustment counterpart. Therefore, a good home valuation system must provide for Least Adjustment alongside Distance and Recency.

I picked the above tables and spatial 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 use the system that works best for you.

All adjustments in Homequant are linear. In Automated Valuation Modeling (AVM), non-linear adjustments (due to the nature of their contributions) are generally used via non-linear regressions. If you are trying to learn AVM or understand how to make advanced non-linear adjustments, please check out my recent book on AVM "An  Illustrated Guide to Automated Valuation Modeling (AVM) in Excel..." on Amazon.

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