<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T08:07:38Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/120651" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/120651</identifier><datestamp>2021-07-05T14:03:20Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Walter N. Torous.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Song, Weijia, S.M. Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Center for Real Estate</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2019-03-01T19:55:14Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2019-03-01T19:55:14Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2018</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/120651</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1088411580</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2018.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 34-35).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">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.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Weijia Song.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Real Estate Development</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">35 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">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.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Center for Real Estate. Program in Real Estate Development.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">'The Optimal Mix' : deploying portfolio theory on real estate asset returns in mixed-use development</dim:field>
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   	&lt;Title>&amp;apos;The Optimal Mix&amp;apos; : deploying portfolio theory on real estate asset returns in mixed-use development&lt;/Title>
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   	&lt;PublicationDate>2018&lt;/PublicationDate>
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        	&lt;DisplayName>Song, Weijia, S.M. Massachusetts Institute of Technology&lt;/DisplayName>
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    &lt;Keyword>Center for Real Estate. Program in Real Estate Development.&lt;/Keyword>
   	&lt;Abstract>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 &amp;apos;optimal mix&amp;apos; in mixed-use development resulting in a programmatic melange. Current practices largely determine the program mix through &amp;quot;gut intuition&amp;quot; or &amp;quot;rule of thumb&amp;quot;, 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 &amp;apos;optimal mix&amp;apos; 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 &amp;apos;optimal mix&amp;apos; that will generate the highest risk-adjusted returns for an investor, bringing to the forefront a new method in intelligent programming.&lt;/Abstract>
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