Case Study: Maximize Your Investment Return Using Real Estate Software
Author: Joe Li / Category: UncategorizedWith all the volatility in today’s real estate market, it’s more important than ever to understand the numbers before you buy. As my grandmother used to say, know how deep the pool is before you jump in! The right software can do just that (metaphorically speaking, of course), turning an often confusing and intimidating analysis into a straight-forward (and dare I say “fun”) exercise. The following case study looks at real estate investment analysis software, and how it can be used by investors—novice and professional, alike—to assess the financial viability and risk of a property.
This case study analyzes real world properties using real estate investment analysis software by GreyStone Analytics (full disclosure: I’m the founder and CEO of GreyStone Analytics, so please forgive any bias). The goal of the study is not to promote a particular software product, but to show how such analysis tools can help investors make profitable decisions.
The scenario: You have $25,000 you want to invest in real estate. You want to maximize your financial return while minimizing risk.
The problem: There are several properties to choose from in your area. How do you select the right one? You need an effective way to evaluate and compare investment financials.
The solution: Use real estate investment analysis software to quickly, simply and effectively evaluate the financial viability and risk of all your options.
About the Property
As the basis for this case study, I looked through real estate listings in my hometown of York, PA. There were several listings that met the criteria for the investor scenario described above. Let’s start by looking at one property in particular:
Property A (Codorus Manor):
Purchase Price: $159,900
Number of Units: 4
Total Monthly Rent: $2,125
Property Tax: $3,150
Other Operating Costs: $580/month (property management) + $100/month (maintenance)
Closing Costs: $3,000
Estimated Cost of Resale: 7.0% of sales price
Loan: 30-year fixed rate @ 6.000%
Of the $25,000 the investor has to invest, we assume $3,000 goes to closing costs and the remaining $22,000 is used as a down payment. That translates into a loan of $137,900 ($159,900 purchase price MINUS $22,000 down payment).
Before diving into the analysis, we need to make a few more assumptions regarding future revenue, costs and resale valuation. While it’s difficult to accurately predict future market trends, the GreyStone software automatically displays historical zip code-level market data to provide context for these assumptions. For instance, Property A is in the 17404 zip code. According to the software, the median rent for this zip code increased by an average annual rate of 2.7% (from 1990 to 2000). The user can modify the assumption based on his/her knowledge of the market, but for purposes of this analysis we’ll use the historical rate of 2.7%. We assume operating costs and taxes increase by 2.0% annually, and the property has an average vacancy rate of 3.0%.
Similarly, we must make assumptions regarding the property’s resale value. Most software packages allow you to choose from a few different valuation methodologies. The GreyStone software, for instance, allows you to estimate the property’s future value using any one of the following methods:
- Annual Appreciation
- Cap Rate (based on current year Net Operating Income)
- Cap Rate (based on next year Net Operating Income)
- Gross Rent Multiplier
For purposes of this example, we’ll use the annual appreciation method. Again, we’ll apply the historical market data from the software, which shows a 3.5% annual increase in median home value for the zip code.
While the software lets you go into much more detail (e.g., capital expenses, variable interest rates, interest only/balloon loans, refinancing, passive loss assumptions, unit level revenue/vacancy assumptions, reimbursable expenses, etc.), we’ll keep this example relatively simple.
The software walks the user through a set of input screens: Property, Loan, Revenue, and Costs. An example of the Property input screen is shown below (note, the Market Data in the lower-left corner is automatically generated by the software, based on the zip code entered by the user).