Champ-Challenger analysis is an excellent way to provide a validation of one's primary research. If the local housing market is the primary research focus, some competing stats from the condo market could offer an excellent challenge in the form of validation. This comparative approach from the same collective market also provides readers with a context to better understand the primary stats. In valuation analysis, unchallenged stats leave a void that technical valuation experts like the valuation modelers often fail to understand. Here are some specifics:
1. Presenting the Components – While analyzing the single-family residence (SFR) market, one should analyze and present it separately from townhomes (including PUD/HOA), condos and, coops. Instead of combining them as one category and averaging the results, the component-level analysis would make more sense, as their demand characteristics are usually different. The alternative approach could be (value) weighted averages.
2. Diverging Components – Aggregate demand is not necessarily the best way to present a particular market, especially when the components do not move in tandem or diverge significantly. For example, the Condo market generally leads the housing market – on the way up and on the way down. In presenting a residential market analysis where the growth is at variance, it's better to explain the SFR market as the Champ while the condo market serves as the challenger, thus clearly portraying the divergence. A combined picture would musk the on-going reality -- a classic mistake many local reporters tend to make.
3. Power of Challenger – The Challenger analysis is nothing but a validation exercise. When the Champ is meaningfully challenged (validated), the study becomes inherently more meaningful and statistically more significant, considering they are mined off the mutually exclusive and competing market segments. That is why the Property Tax Appeals consultants often hire well-known AVM consultants to develop a challenger AVM to unearth the over-valued parcels on the tax roll. The same concept applies to the other major markets, e.g., challenging a sector Mutual Fund with a competing ETF or a country analysis in emerging Europe with BRICS.
4. Single Parameter Champ – An unchallenged single parameter champ like the month-over-month median SFR sale price analysis is inadequate (it is necessary but not sufficient) to make informed business decisions. It needs to be challenged both "intra" and "inter." The intra challenger (from within the group) is generally the normalized Median Sale Price per SF. Builders often challenge the market approach with a market-adjusted cost approach. Conversely, the ideal "inter" could be the analysis of the condo market as it is a competing component (sub-market) of the overall housing market, thus leading to the highest and best analytical use of the overall market.
5. Reducing Market Noise – Normally, the SFR and condo markets remain in sync. When they diverge, one needs to investigate the reason. Since the condo market often takes the lead, either way, it could be tell-tale, pointing to the beginning of a new market swing; for example, if the condo market starts to trend up, SFRs and Townhomes won't be far behind. When they diverge for a long time, one must run the normalized tests to determine if the market internals are diverging. If not, it could be the "monthly" aberration. The 2-Month Moving Average helps reduce the monthly noise. These are the primary tools one must initially apply in diagnosing the reason for market divergence. If those tools are unhelpful, a step-by-step regression model could point to more precise reasons.
6. Challenger Condo Model – If one is forced to build a challenger (regression) model for the condo market, one must remember that the condo modeling is different from the SFR modeling. Condo modeling can be top-down or bottom-up. It's good to avoid top-down modeling as it involves income modeling requiring hard-to-find condo complex-level income-expense data. Since condo sales are at the unit level, the bottom-up market modeling is more common. In addition to the unit-level condo sales data, market modeling does require data related to the unit-level property attributes, complex-level amenities, and general location, which are available on county assessment sites. Under severe time constraints or If the condo data are not easily accessible, a condo sales ratio study could provide a stop-gap challenge.
7. Apples-to-apples comparison – The SFR market tends to be more homogeneous than the condo market. Though there are Waterfront Mansions, French Tudors, Brownstones, etc. in the SFR market, they do not necessarily form the norm. Conversely, condo markets routinely comprise low-rise, mid-rise, high-rise, skyscrapers, etc. with significantly different amenities. So, one needs to know the apples-to-apples comparison; for example, in NYC, only the low-rise condos are grouped with the SFRs in the same tax class, easing the comparison. In suburban markets, it is prudent to remove the high-rise and skyscraper condos from the sample. Of course, if one uses the Median Sale Price or Median SP/SF, a handful of high-rise condo unit sales would not skew the results.
8. Data for External Analysts – While collecting the data, the external analyst must know that, nowadays, a vast majority of counties (where the population-level data originates) make at least the sales data available on their sites (as customer service so the property owners can develop their own comparables analysis and validate the market values on the tax roll). Additionally, it's prudent to choose a county that makes the property data elements like Bldg SF, Land SF, Year Built, etc. available to develop the normalized tests or the regression model. Of course, when one has ample time for the project and is undertaking it for the institution, one would be better off buying the data from a national data vendor with many more data variables. Most data vendors offer a small data sample to evaluate the quality of data and the variables they warehouse.
9. The External Challenger – Last but not least, it's good to compare the internal results with S&P Case-Shiller's indices. The Case-Shiller monthly housing indices are available for the 20 major markets (MSAs), both seasonally adjusted and unadjusted. Since the internal analysis is generally seasonally unadjusted, the comparison must be made with Case-Shiller's unadjusted indices. Since the 3rd party data comes with many copyright restrictions, the comparison should be shown in the report with full disclaimers, but not in the presentation. Moreover, considering this is the 3rd party work, it does not make much economic sense to promote theirs; instead, one must always learn to encourage one's own/internal work as the solution. For instance, smart real estate brokers always advise their salespeople to sell in-house inventory as it costs the brokerage a lot of money and time to acquire exclusive listings.
Again, a good champ-challenger analysis is self-selling and convincing as the challenger does most of the selling.
-Sid Som, MBA, MIM
homequant@gmail.com
