Generally, in order to look at a real estate market, there have been a couple of statistics that are relatively easy to gather, and that can tell you either about the direction or the market or the status (current state) of the market.

 

Here I explain the ones I use, and the ones I don't, to make my short hand during the reports a little clearer for those out there who are unfamiliar.

 

 

 

 

 

  1. Real Estate Statistic #1: Home Selling Index

    I refer to this as the HSI, and it is the red line in my charts. This is a composite indicator that takes in to account all the relevant factors and sums them up in one, easy to digest number for how easy it will be for a seller in that particular location or town to sell a house. It tries to estimate the imbalance of buyer and sellers (more sellers than buyers pushes the number up, more sellers than buyers pushes it down) as well as how FAST houses are selling (Sellers are not real patient and will cut prices when they sit on the real estate market).  Numbers under 75 are generally buyers markets, where there is too much inventory or the inventory is moving so slowly that sellers will be receptive to offers. Numbers from 80-90 are generally neutral markets, where desirable properties are moving quickly, but less desirable properties, or over priced properties, are not moving well at all, and are racking up market time. Numbers above 100 indicated that the sellers are starting to take charge, and nice properties will go quite quickly, perhaps with multiple offers.  At 120+ virtually all properties desirable or not, will attract attention and attractive prices will sell these properties. As you get above 130, it indicates buyers are willing to take much more risk, and rising prices are likely to follow any sustained push above 130.
  2. Real Estate Statistic #2: Days on Market

    Called DOM for short. This is the easiest to understand, but not the most reliable statistic.  It reflects the length of time that a home has been on the market, and when looking at a collection of homes is usually averaged.  The number is a good indicator of demand, with a couple of exceptions.  Even in tight markets, it is unusual to see numbers under 60.  So I would characterize the numbers this way: 60-90= very strong demand.  90-120=Good Demand, 120-150 = Balanced Demand, 150-190 = Soft Demand, 190+ Weak Demand.  In my report I look at the DOM of both SOLD properties, which I consider to be the most reliable indicator, and Active properties, which is less accurate.  Active properties can be influenced by new construction and "unreasonable" sellers, and only a few can throw off the data significantly in some of Metrowest's smaller markets.  (There are some people comfortable marketing their property for 2-3 years, or more, and that screws up the data set).  
  3. Real Estate Statistic #3: Active/Solds ratio

    I don't actually track the ratio directly, but my graphs show the solds in Yellow and the Actives in Green.  When those lines are moving apart, prices are probably moving up or down, depending on which line is one top. When they are moving closer to each other, the market is closer to balance and level prices. The active/solds ratio is the Ratio of the Active properties on market divided by the Solds in the last six months.  I find this to be an excellent predictor of activity in most markets.  If you have many more solds than actives, that means that buyers like the prices in that town, and property is moving quickly.  This type of momentum often feeds itself, as buyers start to get into competitive situations, and start losing bids on preferred housing. Most buyers don't like to lose twice, so they get more aggressive the second time around.  As the solds number increases, there are fewer houses to go around, and if sustained, price increases are inevitable.  Conversely, if the actives far outnumber the solds, there are not enough buyers to go around, and sellers will need to make their property "stand out" in the buying community by lowering the price. (Or improving the property).  Note for all statistics after February, 2011 - I changed the data I collect to include pendings - properties that are firmly under contract.  I hadn't been collecting them as they eventually (about 90% anyway) to the sales statistics, but that's a lag period that I don't want in my data sets.  A very small number of these transactions do not go to completion, but it's worth that issue to get more relevant data.
  4. Real Estate Statistic #4: Price per Square foot

    This measures the sale price of a home based on the listed square footage.  Although square footage is not tracked uniformly, it differences tend to be constant and come out in the wash over town-sized data sets.  This number isn't often easy to get, but I record it when I can.  I feel it's a much better indicator of pricing and value (ONLY in aggregate!! To be used carefully when looking at one house) then it's most common friend, Median Home Prices.
  5. Real Estate Statistic #5: Median Home Prices

    Median price data is a statistic I do not track.  Frankly, I think it shouldn't be used except in the largest collections of data.  The reason I don't like it, and don't use it, is that real estate markets often see the top or the bottom of the market move INDEPENDENTLY of each other.  So in a small town, if the lower end starts selling while the top end stagnates, the median can fall dramatically, even though town pricing hasn't changed.  In 2010, most towns saw the opposite.  The top end moved dramatically while the lower end stagnated.  This had to do with more attractive Jumbo financing, and the end of the home buyer tax credits (which favored smaller housing purchases).  In many towns, the medians went up 10, 20, even 30% or more, but pricing was actually up less than 5% in most towns.  Due to the unreasonable expectations this number can set in both directions, I don't track it.
  6. Real Estate Statistic #6: Dollars per Square Foot ($/ sq foot)

    This is a statistic that I track, as it is probably the best metric of how expensive a town is. Although there are problems with this data set, due to the way square footage is often (mis)-represented, many of the misrepresentations cancel each other out. There's much less volatility in these numbers, and can be useful even in very small data sets over similar inventory. Appraisers calculate and reference this number a lot, and while it's hardly a definitive analysis of the value of a property, it makes an excellent starting point.
  7. Real Estate Statistic #7: Average Sold Price

    This is a statistic that I track, as it can be a little better than town medians. I look at the average sold price over the last 6 months.  Although the numbers, especially in small towns, can jump around just as median prices do, the jumps are less in volume (typically).  I don't feel that it has a lot of value looking at the changes from month to month, but over a 6-12 month period will give a good view of what kind of home you can buy at what price, and whether markets are strengthening or weakening.

 

Hopefully these will make my reports more readable in the future!

 

Matt Heisler

 

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 Matt Heisler