Financial assets not only have variance risk, but also have timevarying skewness risk and kurtosis risk, which makes risk change study very limited if only based on the first or the second moment of the financial assets. GJRSKM model is an effective tool for higher moments risk description of the financial assets and can fit for the distribution of individual financial assets, however, MCopula function can connect marginal distribution of portfolio financial assets, thus, this paper establishes MCopulaGJRSKM model to study the interdependence between Shanghai and Shenzhen stock market. The empirical results show that there are higher moment risk and risk asymmetry of the logarithm earnings rate of Shanghai composite index and Shenzhen component index, i.e, conditional variance risk and conditional higher moment risk increase when the index falls, furthermore, the probability for the index rise of the two stock markets is bigger than that of the index fall under the extreme condition. 