2015/03/18 by Hao Meng, Wen-Jie Xie, Wei-Xing Zhou
Economics, Econometrics and Finance · Physics and Astronomy · #Club #Convergence (economics) #Financial Markets and Investment Strategies #Financial Risk and Volatility Modeling #Financial market #Hodrick–Prescott filter #Housing Market and Economics #Recession #Stock (firearms) #Stock market #physics.soc-ph #q-fin.ST
paper · pdf · doi:10.1142/s0217979215501817
published as International Journal of Modern Physics B 29 (24), 1550181 (2015) · 16 Latex pages including 6 figures and 4 tables
arxiv created 2015/03/18 · openalex publication_date 2015/09/23 · arxiv updated 2015/10/16 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China’s economy has also slowed down by about 2%–3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.