知识与财富的链接
利用GPH方法对中国期货市场收益率的高频数据进行检验, 实证结果表明: 期货市场高频收益率数据的波动性具有长记忆性特征. 然后应用一类描述金融市场波动性过程的长记忆性特征的分整自回归条件异方差FIGARCH模型和HYGARCH模型, 研究了中国期货市场高频数据波动性过程, 实证结果表明长记忆的GARCH类模型在预测期货市场高频数据波动率比较合适. 且相比较而言, HYGARCH模型比FIGARCH模型更加适用于期货市场.
At first,this paper investigates high frequency intra day commodity futures returns,using GPH model analyzes copper,soybean and cotton intra day returns and finds that there is very similar long memory in volatility features at 5 minutes frequency level.Then using a kinds of GARCH model as FIGARCH and HYGARCH fractionally integrated volatility processes describes the long memory features, we find that HYGARCH is more suitable for futures markers.
