1. Company introduction
2. Problem Background and Summary
US real estate company Zillow provides services that predict how the housing prices they own will change in a year.
DH Engineering & Construction Co., Ltd. aims to benchmark Zillow and "develop a model for predicting housing value based on mathematical algorithms"
Analysis of Methodology Revealed by Zillow, Modification of Zillow Methodology to suit the Korean Housing Value Prediction Model, Analysis of Housing Status Required by Model, Propose factors that affect local values
3. Solving Process
Since Korea is heavily influenced by prices according to real estate policies, the Zillow methodology has been modified so that the sensitivity of the housing value prediction model is not measured in the past year, but in the past three years, so that it does not fluctuate much in the impact of the real estate boom or bad news.
An Analysis of the Correlation between the Factors Affecting Housing Prices in Gangnam-gu District. A Study on the Housing Price Determinants Using the Hedonic Price Model : Focused on the Ichon-dong Area, Seoul, by referring to the Ministry of Land, Infrastructure and Transport's actual transaction price disclosure system and Lee Kang and Choi Shin-hee's paper The research was conducted in Kim Joong-pyo and Hong Sung-jin's paper "Research on Housing Price Determinants in the Center of Large Cities: Focusing on Jung-gu, Daegu" and proposed data elements that can be obtained through Google API such as fire stations, police stations, kindergartens, daycare centers and hospitals closest to housing.
4. Ripple effects and future plans
It is expected that the systematic collection of data on proposed factors to measure housing status and local value will enable the verification of the methodology for the Korean model. The methodology presented through model verification needs to be modified and supplemented. Using the proposed model, we expect the value of the company to increase if DH Construction Co., Ltd. provides housing value forecasting services first.
1. Company introduction
2. Problem Background and Summary
US real estate company Zillow provides services that predict how the housing prices they own will change in a year.
DH Engineering & Construction Co., Ltd. aims to benchmark Zillow and "develop a model for predicting housing value based on mathematical algorithms"
Analysis of Methodology Revealed by Zillow, Modification of Zillow Methodology to suit the Korean Housing Value Prediction Model, Analysis of Housing Status Required by Model, Propose factors that affect local values
3. Solving Process
Since Korea is heavily influenced by prices according to real estate policies, the Zillow methodology has been modified so that the sensitivity of the housing value prediction model is not measured in the past year, but in the past three years, so that it does not fluctuate much in the impact of the real estate boom or bad news.
An Analysis of the Correlation between the Factors Affecting Housing Prices in Gangnam-gu District. A Study on the Housing Price Determinants Using the Hedonic Price Model : Focused on the Ichon-dong Area, Seoul, by referring to the Ministry of Land, Infrastructure and Transport's actual transaction price disclosure system and Lee Kang and Choi Shin-hee's paper The research was conducted in Kim Joong-pyo and Hong Sung-jin's paper "Research on Housing Price Determinants in the Center of Large Cities: Focusing on Jung-gu, Daegu" and proposed data elements that can be obtained through Google API such as fire stations, police stations, kindergartens, daycare centers and hospitals closest to housing.
4. Ripple effects and future plans
It is expected that the systematic collection of data on proposed factors to measure housing status and local value will enable the verification of the methodology for the Korean model. The methodology presented through model verification needs to be modified and supplemented. Using the proposed model, we expect the value of the company to increase if DH Construction Co., Ltd. provides housing value forecasting services first.