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Residential property price time series forecasting with neural networks

Authors
Journal
Knowledge-Based Systems
0950-7051
Publisher
Elsevier
Publication Date
Volume
15
Identifiers
DOI: 10.1016/s0950-7051(01)00169-1
Keywords
  • Gamma Test
  • Neural Network
  • Forecasting
Disciplines
  • Computer Science
  • Economics

Abstract

Abstract The residential property market accounts for a substantial proportion of UK economic activity. Professional valuers estimate property values based on current bid prices (open market values). However, there is no reliable forecasting service for residential values with current bid prices being taken as the best indicator of future price movement. This approach has failed to predict the periodic market crises or to produce estimates of long-term sustainable value (a recent European 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 time series data, which forecasts future trends within the housing market.

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