中国房地产业与银行业动态相关性及风险溢出性——基于GPD-Copula-CoVaR模型的实证研究
The dynamic correlation and risk spillover effect of real estate and banking in China: An empirical study based on GPD-Copula-CoVaR model

文章通过构建GPD-Copula-CoVaR模型，考察了2000年1月至2017年6月中国房地产与银行业的动态相关性与风险溢出性，并通过Monte Carlo方法拟合VaR，检验了模型样本外的预测能力。结果表明，房地产与银行的相关性与房地产市场的繁荣及政策调控密切相关，但严厉的政策调控只能暂时降低两个行业的相关性，并不是长效机制；样本外预测显示GPD-BB1Copula模型对实际风险损失的覆盖率更高，模型预测效果更好；此外，房地产与银行存在双向风险溢出效应，其中房地产对银行的风险溢出更强，约为40%。研究对相关投资者和政策制定者具有较强的应用价值。
Based on the GPD-Copula-CoVaR model, this paper investigates the dynamic correlation and risk spillover effect between real estate and banking, over the period 2000 M01-2017M06 in China. In addition, we examine the forecast effect through Monte Carlo method. The results show that the correlation between real estate and banking is highly related to the prosperity and political policies of the real estate market, and the correlation is higher when market in slump. The GPD-BB1 Copula model is suit for the risk situation. The out-of-sample forecast shows that GPD-BB1 Copula model coverage of the actual risk loss is higher, so the prediction ability is better. In addition, the two marks have bidirectional risk spillover effects in extreme situation, and real estate on the banking's spillover is stronger, about 40%. This article provides an effective method for measuring the risks associated with banking and real estate in favor of authorities for risk management.