Artikel
The importance of economic variables on London real estate market: A random forest approach
This paper follows the recent literature on real estate price prediction and proposes to take advantage of machine learning techniques to better explain which variables are more important in describing the real estate market evolution. We apply the random forest algorithm on London real estate data and analyze the local variables that influence the interaction between housing demand, supply and price. The variables choice is based on an urban point of view, where the main force driving the market is the interaction between local factors like population growth, net migration, new buildings and net supply.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Risks ; ISSN: 2227-9091 ; Volume: 8 ; Year: 2020 ; Issue: 4 ; Pages: 1-17 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Housing Supply and Markets
Financial Forecasting and Simulation
- Thema
-
house price prediction
real estate
machine learning
random forest
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Levantesi, Susanna
Piscopo, Gabriella
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2020
- DOI
-
doi:10.3390/risks8040112
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Levantesi, Susanna
- Piscopo, Gabriella
- MDPI
Entstanden
- 2020
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