Screening for Residential Real Estate Investment Opportunities – Part 2

Objective

In my last post about Screening for Investment Opportunities, I discussed a zip-code approach utilizing IRS data trends for the past few years. Looking at the same geography, I wanted to post another method to quickly compare different zip codes by using current, demographic information.

Zip Code Level Data via Moving.Com

Many websites focused on various aspects of people moving will offer information services so people rely on them as a one stop shop. One particular website – Moving.com – provides easy-to-access demographic information for zip codes across the US. Clicking the link above will take you to a screen shown below:

As shown above, you can type in the zip code and click “Get Report” to access the information below:

While this is just a snapshot of the detailed information, the different sections presented include:

• Demographics
• Income and Jobs
• Ethnicity
• Education
• Climate
• Crime
• Residential

I used various data points from these pages across the same zip codes used in my previous post. I compared the data to National figures and the median of the selected zip codes as the benchmark and came up with the following screen below. The “Value” column aggregates the number of times each zip code ‘outperformed’ the national benchmark and the median of the zip codes (a total of 2 points for each factor). While this method is very generic, potential investors may feel the need to experiment with their weighting schedule if they feel certain factors are more important than others. Weight based on your gut instinct, if you don’t know how important something is… research it.

I utilized the same tranches as before: (1) Green – High Growth, (2) Yellow – Potential Growth, and (3) Red – Low Growth.

First set of factors:

The second set of factors and the value for each zip code are below. Keep in mind, the specific zip code will of course not “outperform” the national index when it comes to factors such as Homes Owned and the number of Graduate degrees (above). Using my formula, the same logic would be applied to all of the zip codes, so we can ignore the impact of this hole in the analysis.

For comparability, we can look at the map to see where the zip codes lay:

Now that we have two data sets of analysis for the zip codes I am interested in, I can begin to dive deeper by focusing on what type of risk do I want to take, what is my investment horizon, what are the trade-offs between these zip codes, what sort of return am I looking for (note that the return question comes after your risk management questions), etc. We can also compare the analysis from the IRS data we analyzed earlier to see the overlap between the two data sets.

Conclusion

Now that we have looked at the overall trends, we see there are certainly some zip codes that have historically outperformed others. As always in finance, you have to remember that the past is no indication of the future. The next step in the analysis that we will explore over the next couple of posts focuses on risk management techniques.