Ask any Realtor how he or she prices houses, and you will hear a version of the following statement: “Well, I look at the comparable sales and then I …” In defense of our industry, using comparable sales (or “comps,” as all the cool Realtors say) to price listings is what we were taught. Find the three “closest” comparable sales (looking at features, age, geography and size), make some adjustments for the features that differ and use this analysis to arrive at an asking price for the home. Appraisers largely use the same technique, as does the local county assessor’s office. Trulia and Zillow apply similar inputs to their valuation algorithms, too. The comparable sales method has been in use in our industry for as long as I can remember, and I am approaching 25 years in this business.
A comp is a closed sale that shares as much similarity as possible with the home being valued. A good comp will be a recent sale of a similar type of property from within (or nearby) the subject property’s neighborhood. In theory, the more similar the comparable sale, the more power it has. The base logic behind using comps to price goes something like this — if House A sold for $X, House B sold for $Y and House C sold for $Z, then your house should sell for some adjusted average of the three, provided that the comps used are the most appropriate ones available.
But is this really accurate?
Maybe we should answer this question with another question: Would you drive a car by looking in the rear view mirror? I hope not. Most of us look out the front window (when not looking down at our cell phones, but I digress) because we are far more concerned with where we are going than where we have been. Stated simply, we are more concerned with future events than past ones.
We (Realtors, sellers, buyers, bankers, appraisers, homebuilders) have all been trained for so long to look at the comps for guidance, but we fail to fully acknowledge that comps are really events that occurred in the past.
Take a look at the chart below from the past two years. It tracks homes that went under contract across our region (Richmond, Virginia).
Do you notice a difference from the first half to the second half of the year? How about between 2013 and 2014? How about from April to July?
Do you think you have made a correct pricing decision if you made a pricing decision in July based on May? What if you were a buyer and trying to decide how aggressive (or resolute) to be? Do you think an August buyer could have held firm on a lower offer and gotten a larger concession?
The core issue is that comps are easy to measure and thus prevalently used. It’s unfortunate. The comp is not a fact, per se, it is a result. The reasons why someone else paid a specific amount for a specific home at a specific point in the past is a combination of many complex inputs which do not lend themselves to easy analysis. Inventory levels, interest rates, consumer confidence, seasonality, the “wealth effect” created by the Dow Jones Industrial Average and NASDAQ, mortgage rules, the Dodd-Frank Wall Street Reform and Consumer Protection Act , job growth (regionally, nationally and internationally), population trends … all of these combine to influence buyer behavior.
This is not to say that using comps to help price a home is without merit, as understanding what has happened recently is a good place to start. If you can determine a point from which to begin your analysis, it is a great help. Establishing patterns in past behavior has value … it is just that using comps exclusively falls short, especially in a dynamic market. The quicker the market shifts, the less value any individual comp has. And the last time I checked, the market is still moving extremely quickly.
So what to do?
Short of hiring a genie, learning to read tea leaves or polishing off the crystal ball, how does one predict the future? The real answer is that no one can predict the future, but we are all capable of far more accurate guesses than we realize. With just the mastery of a few basic forward-facing skills, we can really positively impact our client’s decision making. If your advice can impact a client’s financial decision by 2-3 percent, do you think that becomes powerful at all? You bet!
Our excuses are now gone — “big data” is is upon us, and “information as a commodity” means we all have not only the access, but also the tools, to get predictive. It is up to us to take the next step.
And do you know what the coolest thing about all of this is? We have the best data! Our local MLS is the most accurate database available with (effectively) real-time adjustments being made to inventory and absorption, pricing and days on market (or any other field you want to use.) It is a fabulous resource. Why do you think Trulia and Zillow want it? Because they they know they can never recreate it.
At the end of the day, most of our MLSs offer statistical packages designed to help us all get better at analysis. And if your local MLS does not offer the statistical packages to help you analyze the data, do it the old-fashioned way by locking the office door, putting the cell phone on airplane mode, whipping out the legal pad and pen and your calculator, and manually calculate the seasonal absorption rate of the sub-market. Our clients are increasingly expecting these skills from our industry, and if we are unwilling (or unable) to provide forward-facing analysis, Trulia and Zillow are more than happy to take a whack at it.
Rick Jarvis is a co-founder of the One South Realty Group in Richmond, Virginia.