Residential property price time series forecasting with neural networks

I. D. Wilson*, S. D. Paris, D. H. Jenkins

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    56 Citations (Scopus)


    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.

    Original languageEnglish
    Pages (from-to)335-341
    Number of pages7
    JournalKnowledge-Based Systems
    Issue number5-6
    Publication statusPublished - 1 Jul 2002


    • Forecasting
    • Gamma test
    • Neural network


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