Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal pric...Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.展开更多
The aim of the present work is to examine whether the price volatility of nonferrous metal futures can be used to predict the aggregate stock market returns in China. During a sample period from January of 2004 to Dec...The aim of the present work is to examine whether the price volatility of nonferrous metal futures can be used to predict the aggregate stock market returns in China. During a sample period from January of 2004 to December of 2011, empirical results show that the price volatility of basic nonferrous metals is a good predictor of value-weighted stock portfolio at various horizons in both in-sample and out-of-sample regressions. The predictive power of metal copper volatility is greater than that of aluminum. The results are robust to alternative measurements of variables and econometric approaches. After controlling several well-known macro pricing variables, the predictive power of copper volatility declines but remains statistically significant. Since the predictability exists only during our sample period, we conjecture that the stock market predictability by metal price volatility is partly driven by commodity financialization.展开更多
The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals （copper, aluminum and zinc） pricesincorporating structural changes. The ...The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals （copper, aluminum and zinc） pricesincorporating structural changes. The results show that copper, aluminum and zinc returns have many structure breaks points, and nonferrous metals have the greatvolatilityrisk during financial crisis. From the resultsof GARCH with and without structural changes,it isfoundthat the volatility clustering of single nonferrous metal is overvalued when ignoring the structural mutation, and the return of aluminum isthe most overvalued, indicating that aluminum market is more susceptible to external shock.Furthermore,it is also foundthatdynamic volatility correlation exists in the three prices of nonferrous metals, and the structural changes have no significant effect on the volatility correlation of thethree nonferrous metals.展开更多
基金Project(71073177)supported by the National Natural Science Foundation of ChinaProject(12JJ4077)supported by the Natural Science Foundation of Hunan Province of ChinaProject(2012zzts002)supported by the Fundamental Research Funds of Central South University,China
文摘Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.
基金Project(71071166)supported by the National Natural Science Foundation of China
文摘The aim of the present work is to examine whether the price volatility of nonferrous metal futures can be used to predict the aggregate stock market returns in China. During a sample period from January of 2004 to December of 2011, empirical results show that the price volatility of basic nonferrous metals is a good predictor of value-weighted stock portfolio at various horizons in both in-sample and out-of-sample regressions. The predictive power of metal copper volatility is greater than that of aluminum. The results are robust to alternative measurements of variables and econometric approaches. After controlling several well-known macro pricing variables, the predictive power of copper volatility declines but remains statistically significant. Since the predictability exists only during our sample period, we conjecture that the stock market predictability by metal price volatility is partly driven by commodity financialization.
基金Project(71072079)supported by the National Natural Science Foundation of China
文摘The GARCH and DCC-GARCH models are used to study the volatility aggregation and dynamic relevance of China’s three kinds of nonferrous metals （copper, aluminum and zinc） pricesincorporating structural changes. The results show that copper, aluminum and zinc returns have many structure breaks points, and nonferrous metals have the greatvolatilityrisk during financial crisis. From the resultsof GARCH with and without structural changes,it isfoundthat the volatility clustering of single nonferrous metal is overvalued when ignoring the structural mutation, and the return of aluminum isthe most overvalued, indicating that aluminum market is more susceptible to external shock.Furthermore,it is also foundthatdynamic volatility correlation exists in the three prices of nonferrous metals, and the structural changes have no significant effect on the volatility correlation of thethree nonferrous metals.
