designed, constructed and explained in this paper addresses these concerns. The primary venue for
the tool aligns closely with users or students in an introductory or advanced real estate investment
course.
MODEL DESCRIPTION AND DESIGN
This section describes the model created to address the concerns revealed in the literature review.
First, the overall model framework and layout are explained; second, a deterministic mathematical
representation of the model is developed and discussed; third, a simple working example is provided
throughout the discussion to explain how the model incorporates multiple user supplied real estate
parameters and variables and produces risk verses reward estimates for going-in return on equity
(ROE) and holding period internal rate of returns (IRR). A final discussion is provided to show how
Monte Carlo simulation can be eventually incorporated into the model, albeit with all the added
complications and requirements presented in the literature review.v
The model allows students to simulate and test multiple real estate investment assumptions while
varying the range of the input variable combinations, such as rent, operational expenses, debt and
equity-risk premiums. The number of algorithmically controlled input variables is limited to only three,
while all remaining model parameters are held constant during the simulation process. Meredith, Shafer
& Turbin (2002) stress the rationale for keeping model variables, whenever possible, to a minimal
number and to those critical to the application. This is especially true for models built around simulation
analysis of multiple inputs. As more parameters are added, the garbage-in garbage-out (GIGO) issue
becomes a self fulfilling process. Figure 1 provides a high level layout of the model.