Residential property price time series forecasting with neural networks
| Autor: | Ian D. Wilson, D. H. Jenkins, J. A. Ware, S. D. Paris |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Information Systems and Management
Sustainable Value Computer science media_common.quotation_subject Management Information Systems Artificial Intelligence Open market operation Service (economics) Value (economics) Econometrics Time series Preference (economics) Software Valuation (finance) media_common |
| Zdroj: | Knowledge-Based Systems. 15:335-341 |
| ISSN: | 0950-7051 |
| DOI: | 10.1016/s0950-7051(01)00169-1 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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