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dc.contributor.authorApergis, Nicholas
dc.contributor.authorPayne, James
dc.date.accessioned2019-05-24T15:33:57Z
dc.date.available2019-05-24T15:33:57Z
dc.date.issued2019-04-22
dc.identifier.citationApergis, N., and Payne, J. (2019) 'Modeling the time varying volatility of housing returns: Further evidence from the U.S. Metropolitan condominium markets'. Review of Financial Economics. DOI: 10.1002/rfe.1063.en_US
dc.identifier.issn10583300
dc.identifier.doi10.1002/rfe.1063
dc.identifier.urihttp://hdl.handle.net/10545/623785
dc.description.abstractThis study extends the literature on modeling the volatility of housing returns to the case of condominium returns for five major U.S. metropolitan areas (Boston, Chicago, Los Angeles, New York, and San Francisco). Through the estimation of ARMA models for the respective condominium returns, we find volatility clustering of the residuals. The results from an ARMA-TGARCH-M model reveal the absence of asymmetry in the conditional variance. Dummy variables associated with the housing market collapse unique to each metropolitan area were statistically insignificant in the conditional variance equation, but negative and statistically significant in the mean equation. Condominium markets in Los Angeles and San Francisco exhibit the greatest persistence to volatility shocks.en_US
dc.description.sponsorshipN/Aen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.urlhttps://onlinelibrary.wiley.com/doi/pdf/10.1002/rfe.1063en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectU.S. metropolitan areasen_US
dc.subjectcondominium returnsen_US
dc.subjecttime-varying volatilityen_US
dc.subjectGARCH modelsen_US
dc.titleModeling the time varying volatility of housing returns: Further evidence from the U.S. Metropolitan condominium marketsen_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Derbyen_US
dc.contributor.departmentUniversity of Texas, El Pasoen_US
dc.identifier.journalReview of Financial Economicsen_US
dcterms.dateAccepted2019-03-24
dc.author.detail786373en_US


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