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Residential Property Price Time Series Forecasting with Neural Networks

  • I. D. Wilson
  • S. D. Paris
  • J. A. Ware
  • D. H. Jenkins

Abstract

The residential property market accounts for a substantial proportion of UK economic activity. Professional valuersestimate property values based on current bid prices (open market values). However, there is no reliable forecastingservice for residential values with current bid prices being taken as the best indicator of future price movement. Thisapproach has failed to predict the periodic market crises or to produce estimates of long-term sustainable value (a recentEuropean Directive could be leading mortgage lenders towards the use of sustainable valuations in preference to the open market value). In this paper, we present artificial neural networks, trained using national housing transaction timeseries data, which forecasts future trends within the housing market.

Keywords

Root Mean Square Error Housing Market Residential Property Time Series Forecast Housing Price Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • I. D. Wilson
    • 1
  • S. D. Paris
    • 1
  • J. A. Ware
    • 1
  • D. H. Jenkins
    • 1
  1. 1.School of TechnologyUniversity of Glamorgan, PontypriddUK

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