Abstract
The real estate auction market has become increasingly important in the financial, economic and investment fields, but few artificial intelligence-based studies have attempted to forecast the auction prices of real estate. The purpose of this study is to develop forecasting models of real estate auction prices using artificial intelligence and statistical methodologies. The forecasting models are developed through a regression model, an artificial neural network and a genetic algorithm. For empirical analysis, we use Seoul apartment auction data from 2013 to 2017 to predict the auction prices and compare the forecasting accuracy of the models. The genetic algorithm model has the best performance, and effective regional segmentation based on the auction appraisal price improves the predictive accuracy.
Highlights
In the past, the real estate industry was not recognized as an advanced industrial category
The p-values in Table 14 show that the forecasting ability of the genetic algorithm (GA) models with grouping into 4, 5 and 6 zones based on auction appraisal price is significantly different from that with grouping based on five zones of the 2020 Seoul Basic City Plan
We present three forecasting models for real estate auction sale price using artificial intelligence and statistical methodologies: A regression model and artificial neural network (ANN) and GA models
Summary
The real estate industry was not recognized as an advanced industrial category. The data in the real estate auction industry are well-organized, enabling various in-depth analyses Considering both the real estate auction market and the capital market, the importance of related studies can be recognized. We find that effective regional segmentation based on the auction appraisal price plays a key role in increasing the predictive accuracy of a forecasting model These results offer valuable implications to forward looking investors at real estate auction markets, as well as managers of real estate funds. They are able to make more efficient investment strategies by using our GA model, which results in sustained economic benefits to the related stakeholder of real estate auction markets and the national economy In this sense, the model developed in this study plays a role in sustaining economic growth.
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