• norsk
    • English
  • norsk 
    • norsk
    • English
  • Logg inn
Vis innførsel 
  •   Hjem
  • Handelshøyskolen BI
  • Student papers
  • Master of Science
  • Vis innførsel
  •   Hjem
  • Handelshøyskolen BI
  • Student papers
  • Master of Science
  • Vis innførsel
JavaScript is disabled for your browser. Some features of this site may not work without it.

Predicting Real Estate Price Variations using Machine Learning and Google Trends

Begaud, Bradley
Master thesis
Thumbnail
Åpne
2942403.pdf (3.245Mb)
Data - Base Form.xlsx (44.46Kb)
Thesis Data - Predictive Data.xlsx (47.69Kb)
Thesis Data - Results, Tables and Graphs.xlsx (36.66Kb)
Permanent lenke
https://hdl.handle.net/11250/2823595
Utgivelsesdato
2021
Metadata
Vis full innførsel
Samlinger
  • Master of Science [1550]
Sammendrag
The goal of this paper is to create a modern model via the use of machine learning

(such as support vector regression, regression tree and neural networks) and google

trends to predict real estate price variations. The model should achieve significant

predictive capabilities in monthly variations and should be both interpretable and not

overly complex. There is major interest in being able to predict real estate prices and

many articles have been published on the subject. Most traditional models use

economic data which are usually published quarterly or annually and thus are not

very efficient for short term predicting. As an investor, real estate has always been an

asset class of interest for its performance, diversifying effect on a portfolio and its

interest to a short or long term investor. The interest in the subject goes beyond

investors as it is one of the most important costs for a regular family. These models

will use as inputs various variables that effect either directly or indirectly prices in

real estate. We will focus on the Miami metropolitan area or the Miami-Fort

Lauderdale-Pompano Beach area. The US market was chosen because it provides the

best access to reliable and consistent data. Our model will also focus on predicting

single family house prices which are very popular in the US.
Beskrivelse
Masteroppgave(MSc) in Master of Science in Finance/(Financial Economics) - Handelshøyskolen BI,2021
Utgiver
Handelshøyskolen BI

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit
 

 

Bla i

Hele arkivetDelarkiv og samlingerUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifterDenne samlingenUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifter

Min side

Logg inn

Statistikk

Besøksstatistikk

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit