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Daily House Price Indexes: Construction, Modeling, and Longer-Run Predictions

dc.contributor.author Bollerslev, Tim
dc.contributor.author Patton, Andrew J
dc.contributor.author Wenjing, W
dc.date.accessioned 2016-12-06T15:19:01Z
dc.date.issued 2013-06-11
dc.identifier.uri https://hdl.handle.net/10161/13189
dc.description.abstract We construct daily house price indexes for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the procedure used in the construction of the popular monthly Case-Shiller house price indexes. Our new daily house price indexes exhibit similar characteristics to other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity, which are well described by a relatively simple multivariate GARCH type model. The sample and model-implied correlations across house price index returns are low at the daily frequency, but rise monotonically with the return horizon, and are all commensurate with existing empirical evidence for the existing monthly and quarterly house price series. A simple model of daily house price index returns produces forecasts of monthly house price changes that are superior to various alternative forecast procedures based on lower frequency data, underscoring the informational advantages of our new more finely sampled daily price series.
dc.format.extent 49 pages
dc.relation.ispartof Economic Research Initiatives at Duke (ERID)
dc.subject real estate
dc.subject price indices
dc.subject repeat sales index
dc.subject high frequency data
dc.title Daily House Price Indexes: Construction, Modeling, and Longer-Run Predictions
dc.type Journal article
pubs.issue 166
pubs.organisational-group Duke
pubs.organisational-group Economics
pubs.organisational-group Trinity College of Arts & Sciences


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