In this paper，the initial index system design ideas of the Goodhart and Hofmann （2001） is continued to be used here，in which the selection of index variables is from three aspects：monetary policy，external shocks and internal shocks. Based on the idea of dimensionality reduction，the PCA method is used to extract the Chinese financial condition index （FCI），and the HP filter，K-L information and other research methods are used to investigate the lead-lag relationship between FCI and macroeconomic variables. The results show that，during the sample period，China is in a slow recovery period of the third round of the financial business cycle，and a new round of rapid recovery of the financial cycle；Variables relating to price-based monetary policy instruments，real estate markets and commodity prices have a significant importance to FCI；In 2017，there is a high probability event for China to achieve steady economic growth，and systemic financial risk is a small probability event，but need to prevent the occurrence of local and regional financial risks.