Impact of Pre-sale Home Increment on the Volatility Error of Existing Housing Prices
Ho-Wen Yang *
Department of Land Management, Feng Chia University, Taiwan.
Chia-Yu Chuang
Doctoral Program in Civil and Hydraulic Engineering and Construction Planning, Feng Chia University, Taiwan.
*Author to whom correspondence should be addressed.
Abstract
During periods of economic prosperity, real estate developers launch numerous pre-sale housing projects to expand business opportunities, fill market supply gaps, and reduce the demand for completed homes, thereby stabilizing housing prices. However, most people do not perceive housing prices as stabilizing. This raises research interest in whether the volume of pre-sale housing projects can mitigate the demand for completed homes and achieve price stability. This study aims to explore the impact of pre-sale housing project volumes on the volatility error of transaction prices of completed homes. Currently, the mainstream product in the market for completed homes is collective housing, typically classified based on building height and the presence of elevator facilities into apartments, mid-rise buildings, and high-rise buildings. Due to changes in the construction environment, the number of new apartment buildings has sharply decreased, making older apartments the primary objects of transactions. The study found that the ARIMA(2,1,0)-GARCH(1,1) model is the best model and exhibits clustering volatility. The GARCH(-1) volatility coefficient | \(\beta_1\) |=0.957913<1 indicating that volatility decreases geometrically over successive periods, achieving stability. When the volume of pre-sale housing projects is included in the model, the GARCH (-1) volatility coefficient | \(\beta_1\) |=1.032349>1, indicating that volatility increases geometrically over successive periods, failing to achieve stability. Furthermore, the interference coefficient \(\theta\)=0.0012>0 for pre-sale housing projects volumes does not reduce volatility. The price volatility model without incorporating pre-sale house project volumes is convergent. However, once pre-sale house project volumes are included, the model fails to effectively stabilize price volatility. This suggests that the market's expectations regarding the volume of pre-sale house projects volumes do not effectively stabilize price volatility.
Keywords: Volatility clustering, conditional heteroskedasticity, ARCH/GARCH model, taichung