Sophisticated sensitivity : can developers guess smarter?

The commercial real estate industry is currently in a state of turmoil, as access to capital markets is as constrained as consumer demand. Today many real estate development firms find themselves in difficult positions, with plummeting net operating income and upwardly mobile capitalization rates. Tail events - market events that were believed, based on statistics, to be rare occurrences - seem to be occurring with more and more regularity. With increasing uncertainty and market volatility, the question must be asked: how well can real estate developers predict returns? The purpose of this thesis is threefold: First, to determine whether real estate developers are accurately projecting real estate development returns; second, to determine where input assumption estimation errors are made in the ex ante proforma; and third, we undertake an analysis and application of Monte Carlo Simulation to ascertain whether, by providing practitioners another layer of transaction information, simulation is additive to the development return forecasting process. Through the careful analysis of both ex ante and ex post proformas of real estate development projects, this thesis is one of the first to show how well developers predict the outcomes of their projects. Our findings are rather surprising. We determine that ex ante and ex post real estate returns vary dramatically. On average expected development returns are shown to be 23.2%, while realized returns are only 9.4%. To understand this discrepancy we analyze each project proforma to identify where, during the valuation and development processes, developers made mistakes.