Appraiser credibility continues to decay over time.  Even during the great runup in prices, and now the spotty, often rapid rundown in prices – residential appraisers mostly turned a blind eye to the need for this critical “time adjustment.”  Non-residential appraisers have yet to see the coming value shifts.

Shamefully, a time adjustment, (or market price index) is one of the easiest and most reliable adjustments that can be made – if done using modern analysis!

I am told that about half of form residential appraisal reports had “zero” change in prices for market conditions, while at the same time reporting the market was increasing, and then – decreasing.

The most common avoidance used is:  “I used recent comparables, so no adjustment is needed.”

A common, but unreliable method, is “paired-sales.”  Often these are claimed, but not evidenced.  Paired-sales of similar property transactions is a disproven method, as the fiction of “matched-pairs” is just that – a fiction!  Even if there is a resale of a particular property, it will reflect an inappropriate time period, and will usually reflect differing sale conditions, or even property condition (a fixer?).

Other fictions, starting from the worst, include:

  • Pretend that market price levels are “stable;”
  • Consumer price index, national or regional;
  • Published city or area home price indexes;
  • Zip code, neighborhood or census tracts;

This fiction is that somehow, to use a geographic area is sufficient to define the behavior of a market.  A market competitive to the subject.  Unfortunately, geography alone never defines a CMS© (Competitive Market Segment).

As presented in the Stats, Graphs, and Data Science1 class, there is a simple requirement to define the CMS by five dimensions:  Property type/rights, transaction terms, time, space, and preference features.

It is a basic foundation of modern data science that if you get the data right, a useful result is assured.  With complete market facts, we get result reliability, not just a “worthy of belief” opinion.

Once the right, “truly” competitive data is defined, the analysis is straightforward.

In the CAA (Community of Asset Analysts) we share open-source software.  We visualize the data with a simple scatterplot, trend line, and slope.  The slope is our time adjustment and price index.

Once you have set up your MLS (or other data source) template, it takes just seconds (yes, seconds) to create the graph, check for outliers and trend shifts, and post the calculated time adjustment to each comparable within the market segment.

The math is true, the analysis is transparent, and the result is reproducible.  It is factual.

The model intuitively appealing, visual, and algorithmically correct.

Best of all, it eases and improves other adjustment issues.  It improves sureness and trueness of the result, (accuracy and precision).

This is the clear solution to market analysis, price-indexing, and increased appraisal reliability.

Any other method produces biased results, (opinion too high, or too low).

Valuemetrics.info, and GeorgeDell.com make the process available to all in free and low-cost webinars, and of course as fundamental core theory in the Stats, Graphs, and Data Science1 class.  The class provides software, examples, templates, and practice.