Comparison of prices depending on factors in the secondary housing market

The article considers the issue of pricing for the secondary real estate market regarding local causes (physical properties of housing). The aim of the study was to verify the following hypotheses: the influence of the pricing factors of residential real estate on its value is determined by its pric...

Full description

Bibliographic Details
Main Authors: Koktashev Vladislav, Makeev Vladimir, Peresunko Pavel, Mikhalev Anton, Tynchenko Vadim
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:SHS Web of Conferences
Online Access:https://www.shs-conferences.org/articles/shsconf/pdf/2021/27/shsconf_icsr2021_00083.pdf
id doaj-5e16fbd05b4d44e1bb44b058912965cf
record_format Article
spelling doaj-5e16fbd05b4d44e1bb44b058912965cf2021-08-02T08:02:20ZengEDP SciencesSHS Web of Conferences2261-24242021-01-011160008310.1051/shsconf/202111600083shsconf_icsr2021_00083Comparison of prices depending on factors in the secondary housing marketKoktashev Vladislav0Makeev Vladimir1Peresunko Pavel2Mikhalev Anton3Tynchenko VadimSiberian Federal UniversitySiberian Federal UniversitySiberian Federal UniversitySiberian Federal UniversityThe article considers the issue of pricing for the secondary real estate market regarding local causes (physical properties of housing). The aim of the study was to verify the following hypotheses: the influence of the pricing factors of residential real estate on its value is determined by its price segment and the influence of infrastructure on the value of apartments in different cities is the same. In the hypothesis test, data were used on the secondary housing market of the cities of Novosibirsk and Krasnoyarsk, taken from the site of «CIAN» apartment sale announcements and from various open data sources. During the study, non-parametric methods of machine learning, model-agnostic methods for the interpretation of predictive models, hierarchical clustering are involved. As a result of the work, the first hypothesis was confirmed and the second hypothesis was refuted, the high accuracy of forecasting the cost of an apartment was achieved, and the peculiarities of price formation for secondary housing objects were revealed and described.https://www.shs-conferences.org/articles/shsconf/pdf/2021/27/shsconf_icsr2021_00083.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Koktashev Vladislav
Makeev Vladimir
Peresunko Pavel
Mikhalev Anton
Tynchenko Vadim
spellingShingle Koktashev Vladislav
Makeev Vladimir
Peresunko Pavel
Mikhalev Anton
Tynchenko Vadim
Comparison of prices depending on factors in the secondary housing market
SHS Web of Conferences
author_facet Koktashev Vladislav
Makeev Vladimir
Peresunko Pavel
Mikhalev Anton
Tynchenko Vadim
author_sort Koktashev Vladislav
title Comparison of prices depending on factors in the secondary housing market
title_short Comparison of prices depending on factors in the secondary housing market
title_full Comparison of prices depending on factors in the secondary housing market
title_fullStr Comparison of prices depending on factors in the secondary housing market
title_full_unstemmed Comparison of prices depending on factors in the secondary housing market
title_sort comparison of prices depending on factors in the secondary housing market
publisher EDP Sciences
series SHS Web of Conferences
issn 2261-2424
publishDate 2021-01-01
description The article considers the issue of pricing for the secondary real estate market regarding local causes (physical properties of housing). The aim of the study was to verify the following hypotheses: the influence of the pricing factors of residential real estate on its value is determined by its price segment and the influence of infrastructure on the value of apartments in different cities is the same. In the hypothesis test, data were used on the secondary housing market of the cities of Novosibirsk and Krasnoyarsk, taken from the site of «CIAN» apartment sale announcements and from various open data sources. During the study, non-parametric methods of machine learning, model-agnostic methods for the interpretation of predictive models, hierarchical clustering are involved. As a result of the work, the first hypothesis was confirmed and the second hypothesis was refuted, the high accuracy of forecasting the cost of an apartment was achieved, and the peculiarities of price formation for secondary housing objects were revealed and described.
url https://www.shs-conferences.org/articles/shsconf/pdf/2021/27/shsconf_icsr2021_00083.pdf
work_keys_str_mv AT koktashevvladislav comparisonofpricesdependingonfactorsinthesecondaryhousingmarket
AT makeevvladimir comparisonofpricesdependingonfactorsinthesecondaryhousingmarket
AT peresunkopavel comparisonofpricesdependingonfactorsinthesecondaryhousingmarket
AT mikhalevanton comparisonofpricesdependingonfactorsinthesecondaryhousingmarket
AT tynchenkovadim comparisonofpricesdependingonfactorsinthesecondaryhousingmarket
_version_ 1721238808756748288