EconPapers    
Economics at your fingertips  
 

Developing a real estate yield investment deviceusing granular data and machine learning

Monica Azqueta-Gavaldon, Gonzalo Azqueta-Gavaldon, Inigo Azqueta-Gavaldon and Andres Azqueta-Gavaldon

Papers from arXiv.org

Abstract: This project aims at creating an investment device to help investors determine which real estate units have a higher return to investment in Madrid. To do so, we gather data from Idealista.com, a real estate web-page with millions of real estate units across Spain, Italy and Portugal. In this preliminary version, we present the road map on how we gather the data; descriptive statistics of the 8,121 real estate units gathered (rental and sale); build a return index based on the difference in prices of rental and sale units(per neighbourhood and size) and introduce machine learning algorithms for rental real estate price prediction.

Date: 2020-06
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/2008.02629 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2008.02629

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2021-03-28
Handle: RePEc:arx:papers:2008.02629