Machine learning model to detect real estate investment opportunities in Barcelona

The real estate market in large cities experiences constant price fluctuations, driven by both macroeconomic variables and specific circumstances of sellers. These conditions make identifying properties priced lower than similar ones a challenge. This research developed a machine learning model to d...

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Detalles Bibliográficos
Autor: García de Olalla Blancafort, Verónica
Tipo de recurso: tesis de maestría
Fecha de publicación:2025
País:España
Institución:Universitat Oberta de Catalunya (UOC)
Repositorio:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/152370
Acceso en línea:https://hdl.handle.net/10609/152370
Access Level:acceso abierto
Palabra clave:real estate
machine learning
bienes raíces
inversión
aprendizaje automático
Big data -- TFM
Dades massives -- TFM
Descripción
Sumario:The real estate market in large cities experiences constant price fluctuations, driven by both macroeconomic variables and specific circumstances of sellers. These conditions make identifying properties priced lower than similar ones a challenge. This research developed a machine learning model to detect such opportunities in Barcelona. To achieve this objective, various machine learning models were evaluated and compared to identify the one that provided the most accurate price predictions, thereby facilitating the identification of opportunities for both investors and non-expert individuals seeking undervalued residential properties. Additionally, an interactive dashboard application was developed to visualize the main opportunities, with monthly updates. This approach not only facilitates decision making but also enables continuous monitoring of real estate market trends.