{"title":"Forecasting housing prices in Turkey by machine learning methods","authors":"M. Kayakuş, M. Terzioğlu, Filiz Yetiz","doi":"10.36253/aestim-12320","DOIUrl":null,"url":null,"abstract":"In this study, decision tree regression, artificial neural networks (ANN) and support vector machines (SVM) methods are applied by using monthly data for the period 2013-2020 in the estimation of housing sales in Turkey. In the analysis, the volume of individual mortgage loans offered by banks, the average annual interest rate of mortgage loans from macroeconomic and market variables, the consumer price index (CPI), the BIST 100 index, the benchmark bond interest rate, gold prices and the values of the US dollar and Euro Turkish lira and the housing sales price per square meter in Turkey are used. As a result of the analysis carried out on the model created house sales prices in the Turkish housing market have been successfully estimated and in the light of these estimates, it is determined that banks can guide banks in the creation of various credit packages and appropriate loan targets to support the housing sector.","PeriodicalId":53999,"journal":{"name":"Aestimum","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aestimum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36253/aestim-12320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 3
Abstract
In this study, decision tree regression, artificial neural networks (ANN) and support vector machines (SVM) methods are applied by using monthly data for the period 2013-2020 in the estimation of housing sales in Turkey. In the analysis, the volume of individual mortgage loans offered by banks, the average annual interest rate of mortgage loans from macroeconomic and market variables, the consumer price index (CPI), the BIST 100 index, the benchmark bond interest rate, gold prices and the values of the US dollar and Euro Turkish lira and the housing sales price per square meter in Turkey are used. As a result of the analysis carried out on the model created house sales prices in the Turkish housing market have been successfully estimated and in the light of these estimates, it is determined that banks can guide banks in the creation of various credit packages and appropriate loan targets to support the housing sector.
期刊介绍：
Aestimum is a peer-reviewed Journal dedicated to the methodological study of appraisal and land economics. Established in 1976 by the Italian Association of Appraisers and Land Economists, which was legally recognized by Ministerial Decree, March 1993. Topics of interests comprise rural, urban and environmental appraisal, evaluation of public investments and land use planning. All the areas under discussion are addressed to the International scene. The interdisciplinary approach is one of the mainstays of this editorial project and all of the above mentioned topics are developed taking into consideration the economic, legal and urban planning aspects. Aestimum is biannual Journal and publishes articles both in Italian and English. Articles submitted are subjected to a double blind peer review process.
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