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Forecasting housing prices in Turkey by machine learning methods

التفاصيل البيبلوغرافية
العنوان: Forecasting housing prices in Turkey by machine learning methods
المؤلفون: Mehmet Kayakuş, Mustafa Terzioğlu, Filiz Yetiz
المصدر: Aestimum, Vol 80 (2022)
بيانات النشر: Firenze University Press, 2022.
سنة النشر: 2022
المجموعة: LCC:Industries. Land use. Labor
مصطلحات موضوعية: Home sales price prediction, Decision tree regression, Artificial neural networks, Support vector machines, Industries. Land use. Labor, HD28-9999
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
Italian
تدمد: 1592-6117
1724-2118
Relation: https://oaj.fupress.net/index.php/ceset/article/view/12320; https://doaj.org/toc/1592-6117; https://doaj.org/toc/1724-2118
DOI: 10.36253/aestim-12320
URL الوصول: https://doaj.org/article/190debc2c93e4cd9a96d37c860c9fbf9
رقم الانضمام: edsdoj.190debc2c93e4cd9a96d37c860c9fbf9
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15926117
17242118
DOI:10.36253/aestim-12320