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Dushi Huayuan: Using Monte Carlo Simulation to Value Flexibility in a Chinese Real Estate Development Project



Thesis Advisor: David Geltner, Professor of Real Estate Finance, Department of Urban Studies and Planning


Real estate development in China is a fast-paced business. Volatile market conditions have prompted Chinese developers to build and sell quickly in an attempt to mitigate market fluctuation risk, especially when the real estate market is hot. But are they leaving money on the table?

We’ve conducted a rigorous quantitative analysis of Dushi Huayuan—a large-scale residential project in the fictitious city of Gangkou Shi—from the standpoint of its developer Acumen Properties. The thesis takes the form of a traditional business case study: we first crafted the story based on actual events, then built a Monte Carlo simulation model using Excel to test the value of flexibility—specifically the value of dividing the project into multiple phases—at Dushi Huayuan, and finally designed three exercises for students to learn not only the technical aspects of modeling, but also the business concepts related to working in the Chinese real estate market. The exercises will walk students through the following: (1) build a simulation process to reflect the crucial exogenous dynamic economic variables that largely determine the project’s financial outcome; (2) expand upon this model by introducing phases in the project to understand how this new flexibility can affect expected net present value; and (3) employ the use of a waterfall analysis to examine fairness from an investment perspective between joint venture partners using standard-market terms.

Chinese developers—along with most developers worldwide—typically make decisions based on their experiences and intuition but without the use of detailed quantitative analysis. Our thesis ultimately seeks to change generally accepted industry practice by creating a pedagogical tool to help future real estate leaders better understand the advantages of using quantitative methods to inform rational business decisions.