AUTOMATED EVALUATION MODELS in real estate market: A comparative analysis between linear regression and XGBoost

Silviu-IonuÈ› BÄ‚BÈšAN ()
Additional contact information
Silviu-IonuÈ› BÄ‚BÈšAN: Accounting andAudit Department, Faculty of Economics and BusinessAdministration, BabeÅŸ-Bolyai University

Annales Universitatis Apulensis Series Oeconomica, 2024, vol. 2, issue 26, 3

Abstract: The dynamic trend of the real estate market, as well as the rapid digitization process that has taken place recently, has created the need to identify techniques for automated property price valuation. This article aims to eliminate the problems of subjectivity and high resource consumption of traditional valuation by analyzing the practical implementation of automated valuation methods in the real estate market. Thus, the article performs a comparative analysis between classical prediction methods, such as linear regression, and complex prediction algorithms, such as XGBoost, which can be applied in real estate value prediction. By analyzing the accuracy of predictions on a sample of apartments in Cluj-Napoca, Romania, the study compares the two automatic valuation methods and draws the lines of their implementation. The results of this study can be used for the development of automatic valuation techniques at a global level.

Keywords: real estate; mass appraisals; automated appraisal; valuation standards. (search for similar items in EconPapers)
JEL-codes: C88 R30 R31 R32 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://oeconomica.uab.ro/upload/lucrari/2620242/03.pdf (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:alu:journl:v:2:y:2024:i:26:p:3

Access Statistics for this article

More articles in Annales Universitatis Apulensis Series Oeconomica from Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia
Bibliographic data for series maintained by Dan-Constantin Danuletiu ().