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Financial modeling has become an essential part of most real estate transactions today. This is because of the fact that real estate deals today are complex are undertaken not only by individuals but by corporations who specialize in such transactions. Take the case of Real Estate Investment Trusts (REITs), for example. These trusts are organizations that have large sums of money and are also capable of taking up lots of leverage. Hence, just like any other investor, they, too, use financial models in order to find out exactly how changes in their assumptions will impact their expected cash flows and returns.

Real estate as an investment class is very different from other investment classes. This is the reason that the modeling skills required for real estate modeling are also very different. Some unique features related to real estate modeling have been listed in this article below.

Real Estate Financial Modelling: Unique Factors

For the purpose of financial modeling, real estate is defined as any property which is owned by a group of people and rented out to a different group of people. Self-occupied properties are generally beyond the realm of financial modeling. This is because financial modeling is done by corporations who are in the business of commercially letting out properties. People buying residential properties generally do not require elaborate financial models. In most cases, the simple back of the envelope calculations are more than sufficient.

All financial models depend upon assumptions. In the case of real estate modeling, the assumptions being made are quite different than other models. Some of the parameters about which assumptions are made have been listed below.

  1. Rental Yield: The starting point of any real estate financial model is the rental yield. In simple words, it means the amount of rent that a property is expected to generate expressed as a percentage of the total value of the property. For instance, if the value of a property is $100 and the annual rent is $5, then the rental yield is about 5%.

    Financial modelers use benchmark rental yields depending upon the project in question. For example, if the project being undertaken is the simple let out of an existing building, then the rental yield will be less. It will be in the range of the yield provided by fixed income securities. However, if the investors plan to develop the property and create value before renting it out, then the yield could be higher.

    This number is quite important because of the fact that it sets the top line for the rest of the financial model. The rental yield can be compared to the revenue numbers in other financial models. Other expenses are then deducted from this number to derive the net operating income.

  2. Vacancy Factor: An experienced financial modeler knows that it is not prudent to assume that the property will always be rented out all the time. Lease contracts allow people to opt-out of the contract after providing a brief notice. Hence, a vacancy factor should be built into the model. For instance, if the vacancy factor is 10%, then the modeler should reduce the yield by 10%. The vacancy factor reduces the top line of the financial statement. Needless to say that all the numbers which follow are negatively affected by the vacancy factor. Hence, if a novice financial modeler fails to account for vacancy, it can throw the entire model off track.

  3. Loan To Value Ratio: This is a measure of leverage built into the property investment. Loan to value ratio (LTV) is commonly used by banks to finalize the amount of loan that they want to give to the property. This number is derived by dividing the amount of loan being taken with the total value of the property. From a financial modeler's perspective, this number symbolizes the debt which has to be undertaken for the project. The debt number is an important factor in determining the interest payable as well as the periodic payments. Financial modelers must also be aware that a higher loan to value ratio makes a project more vulnerable to interest rate changes. This is because the interest payments increase more if more debt has been used to finance the project.

  4. Loan To Cost Ratio: In many cases, investors do not buy ready-made properties. Instead, they buy land and then build the entire property from the grounds up. In such cases, there is no market value available. Instead, there is a project cost that can be used for analysis. Hence, in such cases, the loan to value ratio is replaced by the loan to cost ratio. The reason is that assuming any market value could be speculative and could lead to more leverage.

  5. Amortization Period: The amortization period also determines whether the periodic payments will be higher or lower. For instance, if the entire property is amortized within two years, the periodic payments will be higher as compared to whether the property is amortized over twenty years. In general, longer amortization periods mean that more interest has to be paid. This is a very important assumption, and if the wrong number is assumed here, all the numbers in the model could change drastically!

The bottom line is that financial modeling for real estate is a totally different ball game as compared to the DCF models and three statement models that we have been working with till now.

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