Building financial models is an art. The only way to improve your craft is to build various financial models across several industries. Let’s try a model for an investment that is not beyond the reach of most individuals – an investment property.
Before we jump into building a financial model, we should ask ourselves what drives our exploring business. The answer will have significant implications for how we construct the model.
Who Will Use It?
Who will be using this model, and what will they be using it for? A company may have a new product for which they need to calculate an optimal price. Or an investor may want to map out a project to see what kind of investment return he or she can expect.
Depending on these scenarios, the result of what the model will calculate may be very different. Unless you know exactly what decision the user of your model needs to make, you may find yourself starting over several times until you find an approach that uses the right inputs to find the appropriate outputs.
On to Real Estate
In our scenario, we want to determine what kind of financial return we can expect from an investment property given certain information about the investment. This information would include variables such as the purchase price, rate of appreciation, the price at which we can rent it out, the financing terms available for the property, etc.
Our return on this investment will be driven by two primary factors: our rental income and the appreciation of the property value. Therefore, we should begin by forecasting rental income and the appreciation of the property in consideration.
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Once we have built out that portion of the model, we can use the information we have calculated to figure out how we will finance the purchase of the property and what financial expenses we can expect to incur as a result.
Next, we tackle the property management expenses. We will need to use the property value that we forecasted to calculate property taxes, so we must build the model in a certain order.
With these projections in place, we can begin to piece together the income statement and the balance sheet. As we put these in place, we may spot items that we haven’t yet calculated, and we may have to go back and add them in the appropriate places.
Finally, we can use these financials to project the cash flow to the investor and calculate our return on investment.
Laying Out the Model
We should also think about how we want to lay it out to keep our workspace clean. For example, in Excel, one of the best ways to organize financial models is to separate certain sections of the model on different worksheets.
We can give each tab a name that describes the information contained in it. This way, other model users can better understand where data is calculated in the model and how it flows.
Let’s use four tabs in our investment property model: property, financing, expenses, and financials. Property, financing, and expenses will be the tabs on which we input assumptions and make projections for our model. The financials tab will be our results page, where we will display the output of our model in a way that’s easily understood.
Let’s start with the property tab by renaming the tab “Property” and adding this title in cell A1 of the worksheet. By taking care of some of these formatting issues on the front end, we’ll have an easier time keeping the model clean.
Next, let’s set up our assumptions box. A few rows below the title, type “Assumptions” and make a vertical list of the following inputs:
Initial Monthly Rent
Annual Rent Increase
In the cells to the right of each input label, we’ll set up an input field by adding a realistic placeholder for each value. We will format each of these values to be blue in color. This is a common modeling convention to indicate that these are input values. This formatting will make it easier for us and others to understand how the model flows. Here are some corresponding values to start with:
The purchase price will be the price we expect to pay for a particular property. The initial monthly rent will be the price for which we expect to rent out the property. Finally, the occupancy rate will measure how well we keep the property rented out (95% occupancy will mean that there will only be about 18 days that the property will go un-rented between tenants each year).
Annual appreciation will determine the rate at the value of our property increases (or decreases) each year. Annual rent increase will determine how much we will increase the rent each year. The broker fee measures the percentage of the property’s sale price we will have to pay a broker when we sell the property.
The investment period is how long we will hold the property for before we sell it. Now that we have a good set of property assumptions down, we can begin to make calculations based on these assumptions.
A Note on Time Periods
There are many ways to begin forecasting out values across time. For example, you could project financials monthly, quarterly, annually, or some combination of the three. For most models, you should consider forecasting the financials monthly during the first couple of years.
By doing so, you allow users of the model to see some of the cyclicality of the business (if there is any). It also allows you to spot certain problems with the business model that may not show up in annual projections (such as cash balance deficiencies). After the first couple of years, you can then forecast the financials on an annual basis.
For our purposes, annual projections will cut down on the complexity of the model. However, one side effect of this choice is that when we begin amortizing mortgages later, we will incur more interest expense than we would if we were making monthly principal payments (which is what happens in reality).
Another modeling choice you may want to consider is whether to use actual date headings for your projection columns (12/31/2010, 12/31/2011,…). Doing so can help perform more complex functions later, but again, for our purposes, we will use 1, 2, 3, etc., to measure our years. In Excel, we can play with the formatting of these numbers a bit to read:
Year 1 Year 2 Year 3 Year 4…
These numbers should be entered below our assumptions box with the first year starting in at least column B. We will carry these values out to year ten. Projections made beyond ten years do not have much credibility, so most financial models do not exceed ten years.
On to the Projections
Now that we have set up our time labels on the “Property” worksheet, we are ready to begin our projections. Here are the initial values we want to project for the next ten years in our model:
Equity Line Bal.
Owned Property Value
Add these line items in column A just below and where we added the year labels.
The property value line will project the value of the property over time. The value in year one will be equal to our purchase price assumption, and the formula for it will reference that assumption. The formula for each year to the right of the first year will be as follows:
B14 is the cell directly to the left of the year in which we are currently calculating the property value, and $B$7 is an absolute reference to our “Annual Appreciation” assumption. This formula can be dragged across the row to calculate the remaining years for the property value.
The annual rent line will calculate the annual rental income from the property each year. The formula for the first year appears as follows:
B12 should be the “1” in the year labels we created. $B$10 should be an absolute reference to our investment period assumption (the data in our assumption cell should be an integer even if it is formatted to read “years,” otherwise the formula will not work). B5 should reference our monthly rent assumption, and $B$6 should be an absolute reference to the occupancy rate.
This function says that if our investment period is less than the year in which this value is to be calculated, then the result must be zero (we will no longer own the property after it is sold, so we can’t collect rent). Otherwise, the formula will calculate the annual rent, which is the monthly rent multiplied by twelve and multiplied by the occupancy rate.