Essec\Faculty\Model\Contribution {#2216
#_index: "academ_contributions"
#_id: "8328"
#_source: array:26 [
"id" => "8328"
"slug" => "physical-real-estate-risk-factors-and-investor-behavior"
"yearMonth" => "2001-06"
"year" => "2001"
"title" => "Physical Real Estate: Risk Factors and Investor Behavior"
"description" => "BARONI, M., BARTHELEMY, F. et MOKRANE, M. (2001). <i>Physical Real Estate: Risk Factors and Investor Behavior</i>. ESSEC Business School."
"authors" => array:3 [
0 => array:3 [
"name" => "BARONI Michel"
"bid" => "B00000023"
"slug" => "baroni-michel"
]
1 => array:2 [
"name" => "BARTHELEMY Fabrice"
"bid" => "B00006901"
]
2 => array:1 [
"name" => "MOKRANE M."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 21:00:33"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Les principaux facteurs de risque de l'immobilier physique en région parisienne sur la période 1973-1998 sont identifiés grâce à une méthode d'Analyse en Composantes Principales (ACP) et à une méthode de régression "stepwise" sur environ 100 000 données de transactions. La première méthode montre qu'une combinaison de variables comme le taux long, l'écart entre le taux long et le taux court, l'indice actions, les loyers, le chômage ou l'indice immobilier coté, ne peuvent pas capturer totalement le risque de rendement en capital immobilier physique. La seconde méthode montre que si l'on devait néanmoins tenter d'utiliser un modèle factoriel pour représenter les mouvements sur les rendements immobiliers, les facteurs à retenir seraient : les loyers, le chômage, l'immobilier coté. Des comparaisons avec les indices existants permettent d'établir des résultats intéressants concernant la nature du risque, le comportement des intervenants sur le marché, et la nature de la crise des années 1990."
"en" => "The main risk factors for residential properties in the Paris area over the 1973-1978 period are identified using a Principal Component Analysis as well as a Stepwise WLS Regression Method. The first method indicates that linear or log-linear combinations of factors such as interest rates, interest rate spreads, equity market returns, rents, unemployment, or even market traded real estate cannot wholly capture physical real estate return risk. The second method indicates it is nevertheless possible to derive a factor model for real estate risk, and that the consistent factors are rents, unemployment, and listed real estate. Comparisons of our factor model index with the IPD index and the Notaires/INSEE square-metre price index, as well as statistical probe of the database, yield interesting implications concerning real estate risk, market participant behaviour, and the nature of the so-called 1990's "speculative bubble"."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-12-22T04:21:46.000Z"
"docTitle" => "Physical Real Estate: Risk Factors and Investor Behavior"
"docSurtitle" => "Working Papers"
"authorNames" => "<a href="/cv/baroni-michel">BARONI Michel</a>, BARTHELEMY Fabrice, MOKRANE M."
"docDescription" => "<span class="document-property-authors">BARONI Michel, BARTHELEMY Fabrice, MOKRANE M.</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2001</span>"
"keywordList" => ""
"docPreview" => "<b>Physical Real Estate: Risk Factors and Investor Behavior</b><br><span>2001-06 | Working Papers </span>"
"docType" => "research"
"publicationLink" => "<a href="#" target="_blank">Physical Real Estate: Risk Factors and Investor Behavior</a>"
]
+lang: "en"
+"_type": "_doc"
+"_score": 8.639127
+"parent": null
}
