摘要
本文以8种农产品期货的高频数据为样本,实证考察了我国农产品期货市场已实现波动率的动态特征,发现农产品期货已实现波动率同时具有长记忆性和区制转换性。在此基础上构建了长记忆马尔科夫区制转换模型来预测农产品期货的已实现波动率,并比较和评价了该模型与其他嵌套模型的预测性能。结果发现,我国农产品期货的已实现波动率具有高波动和低波动两种不同的状态,状态之间的转换概率较小,低波动状态的稳定性比高波动状态强;同时引入长记忆性和区制转换能进一步提高模型的预测性能,长记忆马尔科夫区制转换模型是预测性能最好的模型。
This paper empirically analyzes the dynamic properties of the realized volatility in China' s agricultural commodity future markets by employing the high - frequency data of eight agricultural commodity futures, and finds that the realized volatility exhibits both long memory and regime switching features. To capture these properties simultaneously, we modeled the realized volatility of agricultural commodity futures in China' s future markets by a MS -ARFIMA model, and compared its forecasting performance with that of a variety of competing models which have been encompassed by the proposed model. The estimated results show that the dynamics of realized volatility for agricultural commodity futures are characterized by two levels of long memory: one associated with the low - volatility regime and the other one associated with the high - volatility regime, and the probability to stay in the low - volatility regime is higher than that of the high - volatility regime. The outsample volatility forecast results show that the combination of long memory with switching regimes can improve the out - of - sample realized volatility forecast performance, and the proposed MS - ARFIMA model represents the superior out - of - sample realized volatility forecasts over those obtained using nested models in China' s agricultural commodity future markets.
出处
《经济评论》
CSSCI
北大核心
2014年第4期50-67,共18页
Economic Review
基金
国家自然科学基金项目"农产品期货市场波动率的预测以及预测精度评价研究"(项目编号:71203067)
广东省高校优秀青年创新人才培育项目(育苗项目)"我国农产品期货市场波动率的预测研究"(项目编号:2012WYM_0033)
广东省哲学社会科学规划项目"广东省居民消费平滑研究"(项目编号:GD11YLJ01)
中央高校基本科研业务费专项资金中山大学青年教师培育项目"中国城乡居民消费行为差异与消费金融产品创新研究"(项目编号:13wkpy21)的资助
关键词
农产品期货
已实现波动率
长记忆性
区制转换预测
Agricultural Commodity Futures
Realized Volatility
Long Memory
Regime Switching
Forecast