Determining the Credibility of Market Comps

Darren Mize, ASA and Doug Teten / September 15, 2020

So how do you determine the credibility of data when using a comparable sales database? At GCF our appraisers like to analyze comps using what's called the R-Squared Method and we decided to apply that method against some of our own PeerComps data.

The R-Squared method compares a data set to the line of regression on a statistical chart. The R-Squared function is a score that ranges from 0% to 100%, where 0% represents the lack of cohesion of a data set to its regression mean, and a score of 100% represents perfect cohesion. In business valuation, the industry generally considers an R-Squared score of 75% and above as reasonable.

Above, we plot a PeerComps’ transaction set, against the linear regression representing the relationship between Price and EBIDTA. The data being used is a plot of PeerComps data comprised of all Medical Equipment and Supplies Wholesalers’ transactions (NAICS code 423450) with revenue size between $1.0 million and $10.0 million. Typically, outliers are eliminated to avoid skewing of data, but since there were no outliers, no data points were eliminated in this study. Also, it is worth noting that all transactions are SBA approved, therefore eliminating most outliers as a factor anyway.

Here is where PeerComps scored:

  • 94.5% when comparing Price vs. EBIDTA
  • 95.2 % when comparing Price vs. SDE
  • 64.2% when comparing Price vs. Revenue

Based on this study, the PeerComps data provides approximately 95% accuracy based on EBIDTA or SDE. We do not consider Price vs. Revenue since cash flow drives value, not revenue. However, the empirical study shows that this market trades on a multiple of earnings, and really cannot be gauged by revenue with any certainty. This holds true for most industries.

The R-Squared test is a function available in Excel (RSQ) and we would challenge you to run this test of data cohesion on other databases. We have, and the clear winner is PeerComps. In other databases, we occasionally get a score in the 75% – 80% range, however in most cases to get there we would need to eliminate numerous outliers. Of all the databases GCF subscribes to, we have found PeerComps to be the most accurate, primarily because the PeerComps data is composed of reliable data, where outliers are rarely found.

In conclusion, PeerComps allows you to accurately present a market based approach to value based on actual SBA financed market transactions with a significantly high level of accuracy. The R-Squared study also helps to explain how the market trades, and the legitimacy of the valuation method. PeerComps has a track record of accuracy that is completely unprecedented, and superior to other comparable sales databases.