<?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>2026-09-18T22:53:00Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/97959" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/97959</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">John F. Kennedy and David M. Geltner.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Sacchini Bruzual, Bernardo A</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">2015-07-31T19:08:10Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2015-07-31T19:08:10Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/97959</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">913888085</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, 2015.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 71-73).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">The rising supply of both domestic and international capital pursuing yield in major U.S. real estate markets is staggering and has resulted in substantial unmet demand for quality, institutional assets. This thesis examines the pricing and yield arbitrage between institutional and sub-institutional grade assets, as defined by valuation parameters, alongside the feasibility of an investment model to capitalize on the aggregation of subinstitutional assets into portfolios attractive to institutional investment. The U.S. market was analyzed both quantitatively and qualitatively to determine the viability of the perceived arbitrage, the components comprising both institutional and noninstitutional markets, and where these have been successfully capitalized on with an aggregation investment model. In order to assess the viability and best practices of an aggregation strategy, interviews were conducted with firms invested in or executing this model. A repeat sales index was also created using data provided by Real Capital Analytics which comprised over 68,000 transactions of assets valued above $2.5 million which transacted between 2000 and 2014 across the United States. The interviews, regressions, and corresponding data analysis revealed distinguishable trends underlying institutional and sub-institutional assets within specific markets. These trends suggest that there is inefficiency in the real estate market regarding the pricing of certain sub-institutional assets in older, land-constrained cities making them target locations for an urban aggregation model. The largest disparities between sub-institutional and institutional investments were found in the yield and growth rates of specific assets based on underlying market criteria. By aggregating these two metrics for total return averages for non-institutional and institutional assets, and by analyzing the risk performance of each, we conclude the existence of a different pricing of risk, which generates the potential for arbitrage. Specifically, non-institutional properties exhibited better risk-adjusted returns relative to their larger counterparts for land constrained, older regions and cities, confirming our hypothesis.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Bernardo A. Sacchini Bruzual.</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">113 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">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.</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">Dueling markets : capitalizing on the non-institutional and institutional asset arbitrage</dim:field>
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   	&lt;Title>Dueling markets : capitalizing on the non-institutional and institutional asset arbitrage&lt;/Title>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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   	&lt;Abstract>The rising supply of both domestic and international capital pursuing yield in major U.S. real estate markets is staggering and has resulted in substantial unmet demand for quality, institutional assets. This thesis examines the pricing and yield arbitrage between institutional and sub-institutional grade assets, as defined by valuation parameters, alongside the feasibility of an investment model to capitalize on the aggregation of subinstitutional assets into portfolios attractive to institutional investment. The U.S. market was analyzed both quantitatively and qualitatively to determine the viability of the perceived arbitrage, the components comprising both institutional and noninstitutional markets, and where these have been successfully capitalized on with an aggregation investment model. In order to assess the viability and best practices of an aggregation strategy, interviews were conducted with firms invested in or executing this model. A repeat sales index was also created using data provided by Real Capital Analytics which comprised over 68,000 transactions of assets valued above $2.5 million which transacted between 2000 and 2014 across the United States. The interviews, regressions, and corresponding data analysis revealed distinguishable trends underlying institutional and sub-institutional assets within specific markets. These trends suggest that there is inefficiency in the real estate market regarding the pricing of certain sub-institutional assets in older, land-constrained cities making them target locations for an urban aggregation model. The largest disparities between sub-institutional and institutional investments were found in the yield and growth rates of specific assets based on underlying market criteria. By aggregating these two metrics for total return averages for non-institutional and institutional assets, and by analyzing the risk performance of each, we conclude the existence of a different pricing of risk, which generates the potential for arbitrage. Specifically, non-institutional properties exhibited better risk-adjusted returns relative to their larger counterparts for land constrained, older regions and cities, confirming our hypothesis.&lt;/Abstract>
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