I’m working on a new series on probabilistic modeling over at my blog, adventuresincre.com. Real Estate analysis tends to be very two dimensional, where our best guess assumptions are entered into a model and we heavily rely on the one return outputs that come from those assumptions.
Stochastic modeling involves putting variability into a real estate investment’s assumptions, then running thousands of simulations (Monte Carlo) and examining the range and average of the returns from the collective simulations to ascertain not just the return but the risk inherent in the investment.
Two Posts to Kick Off the Series
I’ve started the series by writing two posts on the topic. My first post, entitled How to Run Monte Carlo Simulations in Excel, is a tutorial on how to use Data Tables and probability functions such as the RAND() and RANDBETWEEN() to run thousands of Monte Carlo simulations. With the results of those simulations, I show how an “Expected Return” is calculated together with the standard deviation and range for the returns.
In my second post, I share an Apartment Acquisition Model with Built-In Monte Carlo Simulation Module that I built to test the concepts. The model is an adaptation of an earlier Apartment Valuation model that I built. It includes a custom Macro that runs 10,000 simulations for both net present value and unleveraged internal rate of return.