You’re waiting at your dentist’s office and you see a financial magazine. The headline grabs your attention — “Top 10 Markets for Real Estate Investors.” The article lists markets with rising rents and markets with strong appreciation. But, it is of little help because everyone knows that past performance is a shaky foundation for tomorrow’s investments, and predictive data without context can be more dangerous than helpful.
If you are part of or want to be part of the new wave of investors using online data to make spot-on investment decisions, you need data that will give you a clear line of sight to the proper conclusions. You need data that helps you pull the trigger with confidence when you’re ready for your next deal.
The type of analysis such data promotes is not for hedge fund managers alone. In fact, the same data I use to make decisions for the funds I work with is the data you need to zero in on personal investments. Trusting partners and providers is good but verifying your decisions with primary source data is better.
I use a spreadsheet packed with more than 50 columns of data. Much of this data is available to anyone.
The data helps me answer five key questions about each market I look at:
- Is it a cash flow or flip market?
- Is there enough supply and enough demand?
- Is there room for the profits I require?
- Is there sufficient rental demand?
- Does the forecast show potential for appreciation?
Let’s talk about the types of data I collect, how I use it to answer these questions and where you can find similar data.
To know whether I want to buy and hold properties for the cash flow or just get in and out for a quick profit flip, I need to understand the historical appreciation a market has experienced. I want to know how much a market has appreciated since the data was first gathered in 1991 and especially how much prices have climbed since the 2009 trough. When I compare specific market data to the national average I can quickly see if high appreciation has pushed prices past the point where a buy-and-hold strategy makes sense.
For example, when I look at numbers for Rust Belt markets like Detroit and Cleveland or bread-basket markets like Kansas City and Topeka, or even deep south markets like Huntsville and Montgomery, I see that they have appreciated much less than the nation as a whole. This tells me that I need to look further, at additional data, to zero in on markets I might want to invest in. Five-year, one-year and 90-day trends show me if investing in a market still makes sense or if I’ve missed the cash flow party.
If the data shows average or higher-than-average appreciation, I take a different path — one that looks for flip opportunities in markets that make rising prices a springboard to quick capital gains.
As I look for markets where a buy-and-hold strategy will lead to passive income, I next look at median home age. I want to know about a market’s growth spurts and what they tell me about possible renovation levels and potential deferred maintenance. I also want to know what age of rentals potential tenants will be wanting. I don’t want to buy 70-year-old properties if renters would rather live in 30-year-old properties and those newer properties are readily available.
For example, my data shows me that in Scranton, Pa., 57 percent of homes were built before 1939 and the median home age is 74 years. Compare this to what my data shows for Fayetteville, Ark. In Fayetteville, 55 percent were built after 1990, and the median home age is 21 years. While I might be able to make a buy-and-hold strategy work in either market, this data tells me that a home built in the 1940s or 1950s in Scranton would be competitive in the rental market. Whereas in Fayetteville, a 75-year-old cash flow property might be in a D or F neighborhood rather than a C+, B- or even B neighborhood. This data keeps me oriented if I am considering both newer and older markets.
Before I dive into renovating a property, I need to know if the needed level of renovation will leave me enough room to make the cash flow I want. The percentage that foreclosed properties in a market are selling below non-distressed assets is the indicator I need.
So, if distressed assets in a market are selling for 58 percent below regular market sales, I know I have room to renovate and remain competitive. However, if another market’s data shows foreclosures selling at 26 percent below non-distressed sales, I know I will be very limited in my ability to perform significant renovations.
Finally, to determine the market type, I need to know something about market price histories. I look for price data for the year 2000, spring of 2007, summer of 2009 and the current quarter. This allows me to spot bubble markets and to eliminate them from consideration as buy-and-hold targets. It also tells me if flips may even be too risky.
For example, San Francisco peaked at $825,400 in 2007, dropped to $402,000 in 2009, and has climbed back to $1,600,000 in 2018. Knowing this can help me decide to 1031 exchange properties in that market and get out while my profits are still intact.
Supply and Demand
If you plan to buy multiple properties on an ongoing basis in a given market, supply and demand is critical. The data that will support your decisions are the number of homes in the process of foreclosure, the number actually foreclosed, the number of three-bedroom homes for sale below $60,000 and the total number of homes on the market. If there are not 150 to 200 homes in foreclosure and at a price well below the median home price, I feel the opportunity for that market has passed. Therefore, I would also pass on that market. Think of hundreds of investors all competing for the same 50 properties. Profitability would be tough to find.
I also use data to tell me the stage of the market cycle a city is in. Here are the datasets I use:
- Supply increase year-over-year (are there more properties on the market or less?)
- Sales activity year-over-year (more selling or less?)
- Percentage of asking price received (how much of a discount is the seller taking to move the unit?)
- Average days on market
Watching this data is one of the best ways to tell when you are moving between market cycle stages, thus allowing you to maximize returns.
I use more than 15 datasets to determine potential for profitability. First is the investment success ratio, which is arrived at by dividing the median foreclosure price by median income. The lower the ratio, the better chance an investor has of servicing the debt and making a high cash flow and return on investment. The higher the number, the more the market will trend toward lower or even negative cash flow if it is a true appreciation or flip market.
Next, I plug in numbers based upon the median foreclosure price. The median rent, mortgage payments, property taxes, insurance, vacancy, maintenance and property management costs allow me to calculate an estimated cash flow, total return on investment, cash-on-cash returns and cap rates. These averages allow me to easily compare markets.
It doesn’t matter how good an investment property looks on paper if you struggle to keep it leased. There are four datasets that help us determine whether there is sufficient rental demand in a market. The first is the market vacancy rate, followed by the market’s percentage of rentals as well as the percentage of owner occupants, and finally total population.
These datasets will tell you areas to avoid in a market and even markets to avoid. Rentals vs properties with owner occupants will indicate the viability of the rental market. Population numbers help you avoid markets too small to provide rental resilience and good exit strategies.
Market forecasting is important because in certain markets investors can make more money from appreciation than cash flow. For many investors this is where a blended strategy helps grow returns or where buying B to A- assets really pays off. Datasets focused on population growth, job growth, future job growth, unemployment, safety scores, school rankings and even SAT scores help me paint a picture of a market’s future.
Population and job growth drive demand, which drives up pricing. Low unemployment, low crime and good schools often drive up home values. Markets scoring poorly in these areas may have homes that cash flow well, but they typically won’t experience the same appreciation.
We’ve established that you need more data than a top 10 article in your dentist’s reading bin will provide. But where does the average investor find this type of information? My primary sources are the U.S. Census, the U.S. Department of Housing and Urban Development, the Federal Housing Finance Agency (FHFA), The National Association of Realtors (NAR), HUDuser.gov, Echodevdirectory.com, and ATTOM Data Solutions.