Abstract：Coordinating the stabilization of housing prices and leverage is an inevitable choice to stabilize the macro econo my and improve people's well-being in the new development stage.Based on the time-varying conditional forecast distribution,this study realizes the categorical assessment of housing price change risk in China,and on the basis of examining the evolutionary characteristics and asymmetric contagion mechanism of housing price change risks of various types,the study uses the MQVAR model to test the regulating effect of different types of leverage on the upside and downside risks of housing price changes in China.The study finds that there is a significant difference in the stage of various types of housing price change risks and their spillover effects,and the total spillover effects of housing price change risks in first-,second-and third-tier cities show a significant decreasing trend after the "housing without speculation" guideline is put forward,in which the third-tier cities are the main spillovers of the downside risks of housing prices and the main recipients of the upside risks.There is obvious asymmetry and heterogeneity in the moderating effect of leverage on the housing price change risk,with the impact of leveraging by the financial sector and the residential sector on the upside risk of housing prices significantly stronger than the impact of deleveraging on the downside risk of housing prices;deleveraging by the financial sector,non-financial enterprises and the residential sector will lead to fluctuations in the downside risk of housing prices,whereas steadily advancing deleveraging by the government sector will not exacerbate the overall downside risk of housing prices.Therefore,in the new period of accelerated urbanization,real estate market regulation needs to pay more attention to the risk characteristics of housing prices,and build targeted and differentiated price regulation mechanisms and leverage adjustment policies.

Keyword：housing price; leverage; time-varying conditional forecast distribution; multivariate quantile vector autoregression model;