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Real Estate Analysis

I was looking to invest in real estate but found the analysis process too time-consuming and the results inconclusive.

I built the equivalent of an MLS (Multi-Listing Service) for real estate investors.

Overview​

Real estate web sites target home buyers - pretty pictures taken with wide angle lenses that makes rooms appear larger then they are, cute descriptions of how wonderful the house is, and glowing recommendations of the neighborhood. I kid, in jest.

What's missing is a real estate site for investors. Front and center is the ability to filter, sort, and rank properties based on an investment thesis.

For example, I'm looking for a single family home, with 3+ bedrooms and 2+ bathrooms, in a class "B" neighborhood, with positive cash flow, and better than average appreciation over a 7-10 year holding period. And I'd like the home price to be in the average price range.

The problem​

Researching real estate, for investment purposes, is difficult, especially at scale. It's almost impossible to generate financial statements for dozens or hundreds of potential properties.

I was looking for a tool that would let me analyze thousands of properties in each of the top 50 markets.

Gathering information, in a common form to make comparisons easier, for each property is impossible. Here is a partial list of things I would want to know about each property.

  • Property - asking price, previous sales, house data (rooms, sizes, infrastructure and updates, garage), taxes, insurance, etc.

  • Neighborhood - classification (A - D), comparable property sales, trends across many vectors, etc.

  • Census - population trends, household income, demographics (single, married, head of household, number of children), etc.

  • IRS - tax implications, such as regulation 1031, accelerated depreciation schedules, and tax advantages at the time of sale.

Each home is distinct and unique and every home has a place in an investment portfolio. The process, from analysis to consideration, requires an MBA in real estate analysis and software to analyze 1,000's of properties.

The solution​

Ingest every home in a regional MLS (Multi-Listing Service), augment it with public data; appreciation, depreciation, and expenses; census information; demographic trends; and neighborhood specifics.

Incorporate CPA-level accuracy as it pertains to investments. Take into account IRS rules, regulations, and tax implications for real estate investments.

Add the ability to filter, sort, and compare properties and projected returns over varying cycles. Cycles could be a holding period (3, 5, 7+ years), an investment profile (cap rate, return on investment, or return on equity), or one of a score of investment criteria.

The software​

The software I wrote consists of many processes:

  • Download public data on a periodic basis. For example, the departments of Housing and Urban Development (HUD) and the Federal Housing Finance Agency (FHFA) publish monthly statistics.

  • Create a common format to express every home, which includes property, purchase, dates (closing, occupancy, and mortgage), financing, improvements, income, mortgage, expenses (insurance, management, repairs, reserves, taxes, and utilities), appreciation, and depreciation.

  • Create a fiscal statement for the next 20 - 30 years, which is used to compare properties.

Issues to resolve​

Unfortunately, I never found a data set of market rents at a granular level (census block groups or census tracts). I would love to train a model to determine single family home rental rates.

I also need access to a feed of MLS information. From what I can determine, this requires a partnership with an MLS partner.

If you know where I can find a data set of rents or access to MLS data, please contact me. Much appreciated.

Technologies​

The real estate analysis software stack was written in Python.

MySQL is used for the database.