rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Forecasting Models for the German Office Market
  name:
    name part: Bönner, Alexander.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2009
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XX, 175 p. 65 illus. online resource.
  abstract: In every market with free floating prices, all market participants are interested in the future developments of these prices. However, there is an evident research gap for forecasting models for the German office market. Alexander Bönner closes this gap by focusing on an empirical investigation of several rent and total yield forecasting models for nine major German cities. The applicability and performance of ARIMA, GARCH and multivariate regression models are analyzed and city as well as forecasting horizon-specific patterns are determined and interpreted. Univariate rent forecasting models generally outperform multivariate rent forecasting regression models in the short run. In the long run, multivariate regression models dominate. However, one must bear in mind that in some cities one model permanently outperforms the other. Eventually, the rent level is mainly determined by its economic fundamentals, which is also demonstrated for the total yield examination.
  table of contents: Literature Review -- Theoretical Foundations -- Design of the empirical study -- Empirical results: Rent forecasting -- Empirical results: Total yield forecasting -- Conclusion.
  note: by Alexander Bönner.
  subject:
    topic: Finance
  subject:
    topic: Finance
  subject:
    topic: Finance, general
  classification: HG1-HG9999
  classification: 332
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783834994028
  identifier: http://dx.doi.org/10.1007/978-3-8349-9402-8
  record info:
    record creation date: 100301
    record change date: 20151204165258.0
    record identifier: 978-3-8349-9402-8