Developing your SFR strategy

September 4, 2020

Far too often, we see single-family real-estate investors overweight cap rates and discount the impacts of home and land appreciation in their investment decisions. This type of analysis is really only valuable for investors who don't use leverage and plan to hold investments in perpetuity. In every other situation, equity appreciation has enormous impacts on both net yields and total returns. That's why underwriting for price appreciation should be given as much weight as cap rates in your return analysis, if not more.

House appreciation vs. land appreciation

To start, let's clear one thing up.  Houses themselves are not necessarily appreciating assets.  Without ongoing maintenance and proper care, the structure itself will actually depreciate (hence, why the IRS lets investors depreciate the structure).  While it is possible for an asset to appreciate above the annual maintenance expenditures, in the majority of cases this appreciation will not in itself outpace the rate of inflation.  Which means that most assets will only appreciate in terms of nominal dollars, not real dollars.  House structures are highly heterogenous and the future appreciation of a structure may be subject to the idiosyncratic preferences of buyers at some point in the future.  This can be very challenging to predict, never mind model mathematically.  Thus, when you think about price appreciation assumptions, the vast majority of the analysis should focus on the land instead of the asset.

Land is a fundamentally scarce appreciating asset.  By looking at land and specific geospatial attributes of a potential investment, we can create high-quality sets of assumptions to add necessary context to our price appreciation assumptions.

Location, location, location

The reason that real estate agents preach this simple mantra is because the vast majority of the time it works.  Above all else, location will determine the potential for a property to appreciate.  While many interpret these words to mean that better location means "higher-end," that misses the point and is not an effective input for modeling HPA. When we look at our internal data sets, we see a couple of interesting trends.

  1. HPA is generally higher the closer you get to an urban core
  2. HPA is generally higher the closer you get to an urban node
  3. HPA is lower in high price point areas

When we look at national averages for price appreciation over the long run, we tend to see a convergence around 3.7%. But the divergence from this mean is quite large from market to market and very large within a given market.

Comparing Net Yields and HPA Across Markets (1980 - 2000)

Generally speaking, we see remarkable consistency from market to market for the combination of Net Yield + Equity Appreciation.  However, outlier markets do exist, especially as attractive markets cycle over time.  Often the greatest opportunity for the greatest returns resides in markets on the verge of rotating into favor.  For example, if a city like Nashville successfully transitions into a Tier 1 city that's no longer dependent on tourism, the current property prices will be looked at as an astonishing discount.

HPA Growth Rate Changes Over the Past 40 Years

When we compare historical appreciation rates from 1980-2000 to 2000-2020, it becomes obvious which markets have rolled into favor, which have rolled out of favor, and which have remained consistently attractive throughout both periods.  While choosing a market certainly improves your chances of equity appreciation, it does not guarantee it.  Even in highly attractive markets, certain neighborhoods can go long periods of time with lower appreciation rates than the market itself.

Build a simple HPA model and stick to it

Once you have you basic set of assumptions, you will want to build a simple model that includes HPA and helps you determine what prices you should be willing to pay in each area where you're considering investment.  The vast majority of this model can be done with simple Excel sheets. Here is a quick opportunity fund calculator we built for a client which an investment thesis around specific distance to commercial nodes, weighted by relative market maturity (determined by $/sqft of recent sales comps).

Sample Calculator Using Distance to Node Modifiers in Excel

Once you have the basic model in place, you will be much better equipped to incorporate HPA in your investment analysis, an exercise that offers significant returns on investment across the investment lifecycle.

HPA is more important than ever

Historically low interest rates, constrained supply, and increasing demand for detached SFR are making equity appreciation analysis even more critical. By ignoring HPA altogether, assuming consistent HPA, or overly focusing on cap rates, investors are setting themselves up for failure.  On the flip side, the investors that carefully model and weigh HPA in investment decisions are poised to capture significant alpha over the next five to ten years. At Elara, we go so far as to model HPA (along with every other expense and revenue assumption) down to a few hundred "block groups" for each market where we operate.  While this level of granularity is not practical for most investors, it does provide interesting underwriting and operating advantages.  If you are interested in learning more about the technology that we use to achieve this modeling granularity, please reach out to chris@elara.one and we would be happy to help.

About Elara

Elara is a full-service, technology-powered property management solution that handles acquisitions, renovations, ongoing management, and strategic disposition of residential rentals. With a combination of data-driven decision-making and world-class operating experience, we deliver efficiency and quality at scale to help you get more out of every home. Schedule a meeting with our team.