Automating real estate investment analysis in Kazakhstan
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Date
2023
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Abstract
In the modern world, data plays the most important role not only for the development of medium and small businesses and the formation of large economies, but also for the comfortable everyday life of every person. This study examines the Kazakh residential real estate market in the city of Almaty to apply machine learning algorithms to real estate data for price prediction. We know that this market is an important sector of the global economy. The residential real estate market in Kazakhstan is a complex structure, consisting of hundreds of thousands of apartments, characterized by many features. At the same time, any changes in the market may cause speculation and a deliberate increase in real estate prices. That is why it is so important to understand what the real cost of an apartment is and where it is more expensive. The research focused on building a real estate value prediction model using machine learning methods such as linear regression, XGBoost, Random Forest, and Prophet. The data was taken from the krisha.kz website for the following dates: November 30, 2020, May 9, 2021 and November 2, 2022. The number of processed data for each of these dates was 6807, 3426 and 32424 records, respectively. Among the tested models, XGBoost and Random Forest showed the best results.
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medium and small businesses, market, machine learning algorithms, global economy