The article examines individual industry data series on the Chinese stock market and international commodity markets based on the application of the method of decomposition of generalized variance of forecast errors to build a secondary volatility index and overflow network. The DCC-GARCH model proposed by the author is used to study the effect of hedging wholesale goods on the Chinese stock market. The results show that in every industry in China, industry and consumer industry are the main risk-taking market, and the energy industry and financial industry are the main export risk market.

This paper examines the risk spillover mechanism between China's stock market and international commodity markets using selected industry data series on soybean copper, gold, silver, sugar, and crude oil. Based on the results of this analysis, a DCC-GARCH model is used to describe the dynamic correlation, build a risk hedging model, calculate the risk hedging efficiency, and evaluate the risk hedging effect. According to the findings, the industrial and optional consumer industries are the primary risk receiving markets, while the energy and finance industries are the primary risk export markets. The stock market crash in 2015 and the COVID-19 epidemic in 2020 made the risk spillover between China’s stock market and international commodity markets surge. On average, the commodity copper is the most efficient hedge, followed by silver, while commodities such as sugar, gold and soybeans are less effective, and copper will continue to be a good hedge for the Chinese stock market in the coming months.