imulation analysis of ex ante real estate investment returns can provide greater insights into
real estate investment risks. Many real estate professionals fail to utilize risk-based metrics
when valuing real estate properties, even after the benefits of representing returns as a range
of probability-based outcomes have been widely publicized. The model created and described is this
paper addresses these concerns by utilizing a subjective discrete probability model strategically
positioned between manual “what-if” analysis and more advanced Monte Carlo simulation. It is
envisioned that such a program will help stimulate a more deliberate discussion and understanding of
real estate return volatility within the classroom, thus serving as platform that encourages the adoption
of more advanced risk analytics in the real estate profession.