{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/106454"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/106454","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Idiosyncratic risk in US commercial real estate","abstract":"Commercial Real Estate price performance is captured at the aggregate (or market) level by a price index such as Moody's RCA CPPI Index. However, individual property performance could be significantly different from the aggregate index performance (both national and metro indices) due to several property related reasons which are different from the factors affecting the market. For example, a tenant's lease termination, an excellent property manager securing attractive leases, unusual operating expenses are some of those (unobserved) property specific characteristics that affect property performance. Specifically, the RCA CPPI Index tracks all sales transaction pairs and using them, constructs a regression model that represents the price index that best fits the sale transactions. The difference between the individual property sales pair performance and that predicted by the aggregate index is captured by the residual of the regression model and represents idiosyncratic risk which is different from the market risk as represented by the aggregate index. Idiosyncratic risk can be quite important for real estate investors. In the absence of derivative contracts for synthetic investment, no one can invest in the aggregate market as a whole. The objective of this thesis is to quantify the idiosyncratic risk (dispersion) of individual CRE transactions in the US from the observed RCA-CPPI national and metro level (regional) indices' performance during the period 2001-15. In this regard, the thesis tries to capture the basic dynamic nature of how the idiosyncratic price dispersion tends to evolve over time as well as by property type and by metro market. Also, the thesis seeks to understand the potential drivers behind the dispersion.","abstract_html":"Commercial Real Estate price performance is captured at the aggregate (or market) level by a price index such as Moody's RCA CPPI Index. However, individual property performance could be significantly different from the aggregate index performance (both national and metro indices) due to several property related reasons which are different from the factors affecting the market. For example, a tenant's lease termination, an excellent property manager securing attractive leases, unusual operating expenses are some of those (unobserved) property specific characteristics that affect property performance. Specifically, the RCA CPPI Index tracks all sales transaction pairs and using them, constructs a regression model that represents the price index that best fits the sale transactions. The difference between the individual property sales pair performance and that predicted by the aggregate index is captured by the residual of the regression model and represents idiosyncratic risk which is different from the market risk as represented by the aggregate index. Idiosyncratic risk can be quite important for real estate investors. In the absence of derivative contracts for synthetic investment, no one can invest in the aggregate market as a whole. The objective of this thesis is to quantify the idiosyncratic risk (dispersion) of individual CRE transactions in the US from the observed RCA-CPPI national and metro level (regional) indices' performance during the period 2001-15. In this regard, the thesis tries to capture the basic dynamic nature of how the idiosyncratic price dispersion tends to evolve over time as well as by property type and by metro market. Also, the thesis seeks to understand the potential drivers behind the dispersion.","abstract_has_math":false,"creators":["Yella, Phanidhar"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development.","school":null,"contributors":[],"advisors":["David Geltner."],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016","date_published":"2016","updated_at":"2026-07-22T22:22:13Z","subjects":["Center for Real Estate. Program in Real Estate Development."],"languages":["eng"],"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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/106454","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["David Geltner."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Center for Real Estate. Program in Real Estate Development."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Center for Real Estate. 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However, individual property performance could be significantly different from the aggregate index performance (both national and metro indices) due to several property related reasons which are different from the factors affecting the market. For example, a tenant's lease termination, an excellent property manager securing attractive leases, unusual operating expenses are some of those (unobserved) property specific characteristics that affect property performance. Specifically, the RCA CPPI Index tracks all sales transaction pairs and using them, constructs a regression model that represents the price index that best fits the sale transactions. The difference between the individual property sales pair performance and that predicted by the aggregate index is captured by the residual of the regression model and represents idiosyncratic risk which is different from the market risk as represented by the aggregate index. Idiosyncratic risk can be quite important for real estate investors. In the absence of derivative contracts for synthetic investment, no one can invest in the aggregate market as a whole. The objective of this thesis is to quantify the idiosyncratic risk (dispersion) of individual CRE transactions in the US from the observed RCA-CPPI national and metro level (regional) indices' performance during the period 2001-15. In this regard, the thesis tries to capture the basic dynamic nature of how the idiosyncratic price dispersion tends to evolve over time as well as by property type and by metro market. 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For example, a tenant's lease termination, an excellent property manager securing attractive leases, unusual operating expenses are some of those (unobserved) property specific characteristics that affect property performance. Specifically, the RCA CPPI Index tracks all sales transaction pairs and using them, constructs a regression model that represents the price index that best fits the sale transactions. The difference between the individual property sales pair performance and that predicted by the aggregate index is captured by the residual of the regression model and represents idiosyncratic risk which is different from the market risk as represented by the aggregate index. Idiosyncratic risk can be quite important for real estate investors. In the absence of derivative contracts for synthetic investment, no one can invest in the aggregate market as a whole. The objective of this thesis is to quantify the idiosyncratic risk (dispersion) of individual CRE transactions in the US from the observed RCA-CPPI national and metro level (regional) indices' performance during the period 2001-15. In this regard, the thesis tries to capture the basic dynamic nature of how the idiosyncratic price dispersion tends to evolve over time as well as by property type and by metro market. Also, the thesis seeks to understand the potential drivers behind the dispersion."],"dc:description.degree":["S.M. in Real Estate Development"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/106454"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"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. 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