Abstract:This paper seeks to model and forecast the Chinese nonferrous metals futures market volatility and allows new insights into the time-varying volatility of realized volatility and leverage effects using high-frequency data. The LHAR-CJ model is extended and the empirical research on copper and aluminum futures in Shanghai Futures Exchange suggests the dynamic dependencies and time-varying volatility of realized volatility, which are captured by long memory HAR-GARCH model. Besides, the findings also show the significant weekly leverage effects in Chinese nonferrous metals futures market volatility. Finally, in-sample and out-of-sample forecasts are investigated, and the results show that the LHAR-CJ-G model, considering time-varying volatility of realized volatility and leverage effects, effectively improves the explanatory power as well as out-of sample predictive performance.

Key words: volatility forecasting; leverage effect; time-varying volatility; nonferrous metals futures; high-frequency data