A Data-Driven Approach to Real Estate Price Estimation: The Case Study Slovakia

Julius Golej, Andrej Adamušin and Miroslav Panik

ERES from European Real Estate Society (ERES)

Abstract: Automated value model (AVM) is a computerized statistically based software that collects and uses Big Data in the real estate sector. It uses property information such as comparable and historical sales, property characteristics, price trends, and any other information relevant to the property in its algorithm. The effectiveness of using AVM depends on the amount and especially the quality of the data used because only high-quality data can be considered reliable and representative. At the same time, it should be added that machine data collection and evaluation in the field of real estate would never be as accurate as manual valuation, where the appraiser can, based on his knowledge and experience, take into account factors that are not taken into account and documented in the collected data, through a physical inspection. Even if an appraiser uses certain specific methods to determine the price of a property, the appraiser's subjectivity factor always enters the valuation process, which can create a certain deviation in human-generated sales prices compared to the price generated by the software. The following contribution is devoted to the issue of creating an AVM model for evaluating real estate sales prices. The authors collaborated on the creation of such a model for practice in Slovak conditions, the main goal of which was to increase the efficiency and productivity of work in the field of real estate valuation.

Keywords: automated value model; Big data; Real Estate Market; Real estate prices (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2024-01-01
New Economics Papers: this item is included in nep-cmp and nep-ure
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