中文摘要：

运用高频金融数据建模和预测中国有色金属期货市场波动率，并探索已实现波动率的波动时变性和杠杆效应。拓展了LHAR-CJ模型，并对上海期货交易所铜和铝期货进行实证研究。研究表明，已实现波动率存在动态依赖性和时变性，它们均可通过长记忆性的HAR-GARCH结构体现。此外，中国有色金属期货市场波动率存在显著的周杠杆效应。最后，样本内预测和样本外预测的结果表明，考虑了已实现波动率的波动时变性和杠杆效应的HAR-CJ-G模型能有效地提高解释能力和样本外预测能力。

英文摘要：

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-varyingvolatility of realized volatility and leverage effects,effectively improves the explanatory power as well as out-of sample predictive performance.