Beyond DCF analysis in real estate financial modeling : probabilistic evaluation of real estate ventures

This thesis introduces probabilistic valuation techniques and encourages their usage in the real estate industry. Including uncertainty and real options into real estate financial models is worthwhile, especially when there is an elevated level of unpredictability surrounding the investment decision. Incorporating uncertainty into real estate pro formas not only provides different results over deterministic models, it changes the angle of attack to real estate valuation problems. When uncertainty is taken into account, the focus shifts from simply maximizing financial returns, to modeling and managing uncertainty to make better ex ante finance and design decisions. The ability to add optionality in probabilistic financial modeling can enhance returns by curtailing losses during downturns and taking advantage of upside conditions. A step-by-step example is carefully crafted to demonstrate the simplicity with which uncertainty, Monte Carlo Simulations and Real Options may be included into real estate pro formas. The example is entirely Excel based and is separated into three parts with each progressively increasing in complexity. SimpleCo Tower establishes the familiar Discounted Cash Flow pro forma as a starting point. ModerateCo Tower describes how uncertainty and Monte Carlo simulations can be incorporated into a pro forma while illustrating the effect of non-linearity on financial models. ChallengeCo Tower reveals how real options can add value to an investment and how it should not be overlooked. The case study illustrates how the techniques outlined in this thesis can add significant value to real estate decisions without much added effort or investment in expensive software. The case study also shows how the use of real world data to model uncertainty can be put into practice.

Department dc:contributor.department

Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Leung, Keith Chin-Kee

Advisor dc:contributor.advisor

• Richard de Neufville and David Geltner.

• Center for Real Estate. Program in Real Estate Development.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/87612

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/87612