Estimation of real estate asset pricing models

In this project we aim to develop 4 different methods in order to estimate the real market price of 380 properties owned by Midtown Realty Group in Miami, Florida -- We used the ordinary least squares, generalized method of moments, artificial neural networks and fuzzy inference systems -- The compa...

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Autores:
Arias Arbeláez, Felipe Alonso
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
OAI Identifier:
oai:repository.eafit.edu.co:10784/12335
Acceso en línea:
http://hdl.handle.net/10784/12335
Palabra clave:
Método generalizado de momentos
Real estate
Estimation
Econometrics
MERCADO DE LA VIVIENDA
MÍNIMOS CUADRADOS
MODELOS ECONOMÉTRICOS
ÍNDICE DE PRECIOS
Housing market
Least squares
Econometric models
Price indexes
Rights
License
Acceso abierto
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dc.title.spa.fl_str_mv Estimation of real estate asset pricing models
title Estimation of real estate asset pricing models
spellingShingle Estimation of real estate asset pricing models
Método generalizado de momentos
Real estate
Estimation
Econometrics
MERCADO DE LA VIVIENDA
MÍNIMOS CUADRADOS
MODELOS ECONOMÉTRICOS
ÍNDICE DE PRECIOS
Housing market
Least squares
Econometric models
Price indexes
title_short Estimation of real estate asset pricing models
title_full Estimation of real estate asset pricing models
title_fullStr Estimation of real estate asset pricing models
title_full_unstemmed Estimation of real estate asset pricing models
title_sort Estimation of real estate asset pricing models
dc.creator.fl_str_mv Arias Arbeláez, Felipe Alonso
dc.contributor.advisor.spa.fl_str_mv Zuluaga Díaz, Francisco Iván
dc.contributor.author.none.fl_str_mv Arias Arbeláez, Felipe Alonso
dc.subject.spa.fl_str_mv Método generalizado de momentos
topic Método generalizado de momentos
Real estate
Estimation
Econometrics
MERCADO DE LA VIVIENDA
MÍNIMOS CUADRADOS
MODELOS ECONOMÉTRICOS
ÍNDICE DE PRECIOS
Housing market
Least squares
Econometric models
Price indexes
dc.subject.ddc.spa.fl_str_mv Real estate
Estimation
Econometrics
dc.subject.lemb.spa.fl_str_mv MERCADO DE LA VIVIENDA
MÍNIMOS CUADRADOS
MODELOS ECONOMÉTRICOS
ÍNDICE DE PRECIOS
dc.subject.keyword.spa.fl_str_mv Housing market
Least squares
Econometric models
Price indexes
description In this project we aim to develop 4 different methods in order to estimate the real market price of 380 properties owned by Midtown Realty Group in Miami, Florida -- We used the ordinary least squares, generalized method of moments, artificial neural networks and fuzzy inference systems -- The comparison between the 4 models was made using the root mean squared errors (RMSE) with an interesting result showing that the best method to estimate housing price given our data set is the artificial neural network using the correct network architecture -- Some further work is proposed in order to make more comparison between the models and dene the best model for housing price
publishDate 2016
dc.date.issued.none.fl_str_mv 2016
dc.date.available.none.fl_str_mv 2018-06-01T02:29:09Z
dc.date.accessioned.none.fl_str_mv 2018-06-01T02:29:09Z
dc.type.eng.fl_str_mv bachelorThesis
dc.type.none.fl_str_mv info:eu-repo/semantics/bachelorThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.local.spa.fl_str_mv Trabajo de grado
dc.type.hasVersion.eng.fl_str_mv acceptedVersion
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/12335
dc.identifier.local.none.fl_str_mv 330.015195CD A696E
url http://hdl.handle.net/10784/12335
identifier_str_mv 330.015195CD A696E
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
http://purl.org/coar/access_right/c_abf2
dc.coverage.spatial.eng.fl_str_mv Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.spa.fl_str_mv Universidad EAFIT
dc.publisher.program.spa.fl_str_mv Economía
dc.publisher.department.spa.fl_str_mv Escuela de Economía y Finanzas. Departamento de Economía.
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/cc1856c3-bc2f-422b-88e4-65a4b1a43b7a/download
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repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
repository.mail.fl_str_mv repositorio@eafit.edu.co
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spelling Zuluaga Díaz, Francisco IvánArias Arbeláez, Felipe Alonso7b98aa25-d157-497a-a27f-8d61ddb1593d-1Economistafariasa@eafit.edu.coMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2018-06-01T02:29:09Z20162018-06-01T02:29:09Zhttp://hdl.handle.net/10784/12335330.015195CD A696EIn this project we aim to develop 4 different methods in order to estimate the real market price of 380 properties owned by Midtown Realty Group in Miami, Florida -- We used the ordinary least squares, generalized method of moments, artificial neural networks and fuzzy inference systems -- The comparison between the 4 models was made using the root mean squared errors (RMSE) with an interesting result showing that the best method to estimate housing price given our data set is the artificial neural network using the correct network architecture -- Some further work is proposed in order to make more comparison between the models and dene the best model for housing priceUniversidad EAFITEconomíaEscuela de Economía y Finanzas. Departamento de Economía.Método generalizado de momentosReal estateEstimationEconometricsMERCADO DE LA VIVIENDAMÍNIMOS CUADRADOSMODELOS ECONOMÉTRICOSÍNDICE DE PRECIOSHousing marketLeast squaresEconometric modelsPrice indexesEstimation of real estate asset pricing modelsbachelorThesisinfo:eu-repo/semantics/bachelorThesisTrabajo de gradoacceptedVersionhttp://purl.org/coar/resource_type/c_7a1fAcceso abiertohttp://purl.org/coar/access_right/c_abf2LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repository.eafit.edu.co/bitstreams/cc1856c3-bc2f-422b-88e4-65a4b1a43b7a/download8a4605be74aa9ea9d79846c1fba20a33MD51ORIGINALFelipeAlonso_AriasArbelaez_FranciscoIvan_ZuluagaDiaz_2016.pdfFelipeAlonso_AriasArbelaez_FranciscoIvan_ZuluagaDiaz_2016.pdfTrabajo de gradoapplication/pdf463408https://repository.eafit.edu.co/bitstreams/833c43c5-cf60-47ad-b85e-e69de6bf989a/download19fdb578716b8fb0a1789176678efdcdMD5210784/12335oai:repository.eafit.edu.co:10784/123352024-12-04 11:48:31.878open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.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