'The Optimal Mix' : deploying portfolio theory on real estate asset returns in mixed-use development

Mixed-use has emerged as one of the most popular and demanded forms of real estate development in many metropolitan regions around the world. While mixed-use development broadly incorporates a variety of functions including, residential, commercial, and retail programs within one project, there is little science in determining the 'optimal mix' in mixed-use development resulting in a programmatic melange. Current practices largely determine the program mix through "gut intuition" or "rule of thumb", and value mixed-use projects by the returns of the individual components. This study seeks to develop an alternative model in defining an ideal program mix in mixed-use development that is based on an optimized and quantifiable portfolio value. The goal is to develop a framework for determining a recipe for mixed-use development in the hope of guiding future development practices in building more efficient, profitable and sustainable mixed-use developments across the United States. This study sees an opportunity to apply Modern Portfolio Theory, a widely adopted method in the finance industry that determines the most efficient allocation in a portfolio of assets, to identify an optimal program mix in mixed-use development projects. Mixed-use developments are inherently a portfolio of distinct real estate assets. Each component product type, such as residential, office, and retail can be thought of as individual assets within a mixed-use portfolio. These component assets offer varying returns and volatilities due to their individual characteristics and correlations with the market. If a mixed-use project is viewed as a portfolio, then an opportunity exists to optimize the project by adjusting allocations in the individual assets, resulting in an efficiently programmed project that maximizes total project returns for a given level of risk. Using market data, this thesis intends to identify the 'optimal mix' for fourteen markets across the United States. The study seeks to discuss the real-world limitations of implementing these program mixes in order to propose a new method to quantify and evaluate programming in mixed-use development; a method based on determining an 'optimal mix' that will generate the highest risk-adjusted returns for an investor, bringing to the forefront a new method in intelligent programming.

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

2018

Author dc:creator

• Song, Weijia, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Walter N. Torous.

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

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written 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/1721.1/120651

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/120651