• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.23-34
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• 2011

Property auctions have become a new method for real estate investment because the property auction market grows in tandem with the growth of the real estate market. This study focused on the statistical model for predicting bid price rates which is the main index for participants in the real estate auction market. For estimating the monthly bid price rate, we proposed a new method to make up for the mean of regions and terms as well as to reduce the prediction error using a decision tree analysis. We also proposed a linear regression model to predict a bid price rate for individual auction property. We applied the proposed model to apartment auction property and tried to predict the bid price rate as well as categorize individual auction property into an auction grade.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.255-266
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• 2021

Investment demand for factory facilities has increased due to the balloon effect caused by housing price regulation. This study investigated the impact of the real estate market and macroeconomic factors on the bid price ratio of apartment auctions and factory auctions, focusing on the metropolitan area. To this end, we reviewed theories and previous studies on real estate auctions, and examined how macroeconomic variables affect bid price ratio of apartments and factories using the panel vector autoregressive model. It was found that the increase in the apartment bid price ratio increases as the participation in apartment auctions increases. However, as the factory bid price ratio increases, the factory bid price ratio does not increase, it was confirmed that the positive (+) relationship between the successful bid price ratio and the bid price ratioe does not exist, unlike previous studies. Based on the analysis results, it is suggested that the real estate market and macroeconomic factors should be considered for the stable operation of the related relevant auction system. This study has limitations in that it is limited to the metropolitan area. In the future, research that expands the scope of research to the whole country and provinces should be conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.682-691
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• 2016

The purpose of this study is to explore the causal and precedence relationships between the housing sub-market and the results of a consumer sentiment survey about the housing market. This study investigates the relationships between the survey results and an apartment deal price index by size and bidding price rate in apartment auctions by extending research related to consumer sentiment surveys. We surveyed the Seoul Metropolitan Area and analyzed the results using a unit root test, cointegration test, Granger causality test, and cross-correlation test. It was confirmed that causality exists between the survey results and apartment deal price index by size and bidding price rate, and it was also confirmed that there are correlation and precedence relationships between them.