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Open AccessArticle

Developing a Forecasting Model for Real Estate Auction Prices Using Artificial Intelligence

1
Graduate Program in Investment Information Engineering, Yonsei University, Seoul 03722, Korea
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Department of Industrial Engineering, Yonsei University, Seoul 03722, Korea
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Department of Business Administration, Sejong University, Seoul 05006, Korea
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(7), 2899; https://doi.org/10.3390/su12072899
Received: 2 March 2020 / Revised: 31 March 2020 / Accepted: 2 April 2020 / Published: 5 April 2020
(This article belongs to the Special Issue Robo-Advisor and Artificial Intelligence in Finance)
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. View Full-Text
Keywords: genetic algorithm; artificial neural network; real estate; auction; forecasting model genetic algorithm; artificial neural network; real estate; auction; forecasting model
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Kang, J.; Lee, H.J.; Jeong, S.H.; Lee, H.S.; Oh, K.J. Developing a Forecasting Model for Real Estate Auction Prices Using Artificial Intelligence. Sustainability 2020, 12, 2899.

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