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How much value has your Louisville home truly lost? The danger of generalized statements

by Tre Pryor

There are many ways to look at data.

Many can seem straight-forward, but there’s always a twist.

If you live in Louisville’s Area 4 and read InsiderLouisville’s year end analysis, you’d be distressed to see home values dropping 15.2 percent in your area.

What I’m about to share about home values should alleviate some of your concern.

When looking at real estate we understand that for most, the purchase of their home is the largest single investment they’ll ever make. (Families are still moving about every seven years so there are likely multiple “largest” investments, but you get the idea.)

Because there are so many dollars at stake, it’s particularly troubling for someone to see their home’s value decline—in some cases drastically.

The Golden Rule of Worth says, “The value of something is determined by what someone will pay for it.” For most products and services, these numbers fluctuate on a regular basis.

Based on this, the only way we know a specific home’s value is on the day of a sale where the home buyer signs their name on the dotted line.

OK, with me so far? Great!

Therefore, when an author writes about home values in aggregate, all of which were not sold on the same day, we’re looking at generalized data. There are a number of different ways to do this.

Chart of Louisville home values based on the FHFA house price index, not seasonally adjusted.

The Federal Housing Finance Association has created it's own index (see below) that measures housing values. The method is better than most but still isn

Methods of assessing a market

    • Method 1: One method would be comparing the average asking price of homes in a given area. After all, home owners (together with their brilliant Realtors) should know better than anyone what their home is worth, right? Kinda.
      Sure, it’s a data point to play with but asking prices aren’t sold prices and therefore haven’t established any true value. It’s really like guessing what the home might be worth; hardly a solid number.

 

    • Method 2: Another method is to compare average sold prices for a given area. This is a step in the right direction. But when looking at averages, if the standard deviation is large, the outliers affect the average too much.
      That may sound like gobbledygook so an example might be in order. Say you live in Briar Hill off Highway 22 in Crestwood. Some of the first homes built are now almost 40 years old! Yet, newer and much larger homes are being in the neighborhood’s new sections and these home prices are much higher.
      Comparing averages over time for this neighborhood would show less accuracy due to the wide range in home prices. (Sample size also plays a role.)

 

    • Method 3: A stronger method looks at an average of median sold prices. Medians remove some volatility and taking a 12-month trailing average of those medians gives us a far better picture of that area’s home values.
      This is the method I choose when analyzing aggregate values.

 

  • Also: There are also a variety of custom-made indexes, each with their own formulas. The worth of these vary based on the expertise of its creator.

The monkey wrench

Cartoon of a monkey holding a wrench

Numbers can be sliced a myriad of ways, many of which can tell completely different stories.

Like I mentioned at the outset, there’s always a twist. In this setting, another factor that affects all of these is home buyer behavior.

There are 52 homes currently for sale in Lake Forest. What if all the homes sold during the next month were all at the least expensive homes in this group?

If that happened, both the median and average sold prices would be lower but not because homes lost value. Instead, buyer behavior has more families looking for less expensive homes from the outset and the results would make you think that values have dropped.

Hopefully, this article has helped you better understand home values. When you saw that your home has lost X% of it’s value, that’s not necessarily true.

The numbers may be lying.

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