Establishment of Forecasting Model for Purchase Probability in Pre-Sale Housing Agency
Date Issued
2014
Date
2014
Author(s)
Chen, Chia-Chuan
Abstract
Research of house buying in the real estate industry is gradually catch people’s attention in recent years. However, most research is focusing on the preferences of final buyers, the relationship between consumer’s preferences and house properties, the impact of different searching methods in house buying and so on. Topics like purchasing probability or forecasting model in house buying are still waiting us to discover. Although experts can guess a rough percentage for each consumers through their experiences, and it generally reaches an agreement that it is very important to know the probability of a consumer to buy a house, there is no research in Taiwan to establish a forecasting model in realestate industry to predict the probability of a consumer to buy the house until now.
The transaction amount of house buying is relatively large, but it is still in the scope of consumer behavior. That is to say, different products may cause different purchasing behaviors; even the same product may lead to different results according to different consumers. When we looked back to what we could know from the historical research, we found out that consumers would change their preference procedure to different types of house, such as pre-sale, new built, and existing house for many years. Therefore, we should not put them together to discuess. On the other hand, if we only looked from one side, like buyers’ point of view only, and ignored other consumers who did not buy the house in the end, it is possible that we could not predict the future market efficiently due to the limitation of data analysis. Consider what mentioned before, this research is aimed to a listed real esate agency company, collecting both the buyers and the consumers who didn’t buy the pre-sale house form 2012 to 2013 in Taipei, and finally establishing a forecasting model by logistic regression model in pre-sale house market, which is verified through Leave-One-Out Cross-Validation method.
Real estate has various characteristics, and consumer behavior is also very complicated. This research may not able to completely explain it, which may lead to low R-square for the models, but it can be proved that most models in this research is acceptable according to AUC results and meet the expectation of experts. In conclusion, the forecasting model in pre-sale house buying is feasible and has crucial contribution to Taiwan’s real estate industry.
Subjects
不動產分析
預售屋
預測模型
Logistic
SDGs
Type
thesis
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