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A Rapidly Updating Stratified Mix-Adjusted Median Property Price Index Model

2020 IEEE Symposium Series on Computational Intelligence (SSCI)(2020)

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摘要
Homeowners, first-time buyers, banks, governments and construction companies are highly interested in following the state of the property market. Currently, property price indexes are published several months out of date and hence do not offer the up-to-date information which housing market stakeholders need in order to make informed decisions. In this article, we present an updated version of a central-price tendency based property price index which uses geospatial property data and stratification in order to compare similar houses. The expansion of the algorithm to include additional parameters owing to a new data structure implementation and a richer dataset allows for the construction of a far smoother and more robust index than the original algorithm produced.
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关键词
stratified mix-adjusted median property price index model,first-time buyers,construction companies,property market,informed decisions,central-price tendency,geospatial property data,stratification,smoother index,robust index,housing market stakeholders
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