Analytics Using Data Mining for Forecastingthe Risk Characteristics of Real Estate Funds
데이터마이닝을 이용한 부동산펀드 위험 특성 분석

Gyung Min Kim
2017 Journal of Real Estate Analysis  
❙ Abstract ❙ This study was carried out with the intent to help institutional investors and the staff of investment companies to select investment goods on the basis of the results of forecasting and analyzing the risk characteristics of domestic and foreign real estate funds (REFs) through classification analysis, thereby minimizing risk and maximizing profitability. The data used for the valuation analysis and classification analysis of REF risk consisted of data on 402 asset management
more » ... et management companies' performance in domestic and overseas REF investment products. Data mining was used to classify and analyze the risk characteristics of REFs. As a result of the predictive analysis of investment values based on the classification analysis of data mining, the classification accuracy of the predictive analysis was found to be 97.76%, showing a high classification rate. Therefore, it is expected that the results of analysis using the decision tree model (C5.0) will offer standards for the development and sale of domestic and overseas REF products to the persons in charge of product planning and asset management in asset management companies and product sale companies.
doi:10.30902/jrea.2017.3.2.39 fatcat:yinjbsqi4jefjgcjxaa7e4dvrm