Forecasting the volatility of crude oil futures using high-frequency data: further evidence

被引:16
作者
Ma, Feng [1 ]
Wei, Yu [1 ,2 ]
Chen, Wang [3 ]
He, Feng [4 ]
机构
[1] Southwest Jiaotong Univ, Sch Econ & Management, First Sect Northern Second Ring Rd, Chengdu 610031, Sichuan, Peoples R China
[2] Yunnan Univ Finance & Econ, Sch Finance, 237 Longquan Rd, Kunming, Yunnan, Peoples R China
[3] Yangtze Normal Univ, Coll Finance & Econ, 16 Juxian Rd, Chongqing 408100, Peoples R China
[4] Nankai Univ, Inst Finance & Dev, 94 Weijin Rd, Tianjin 300071, Peoples R China
基金
中国国家自然科学基金;
关键词
Volatility forecasting; High-frequency volatility models; Signed jump variation; Forecasting evaluation; REALIZED VOLATILITY; CONDITIONAL HETEROSKEDASTICITY; IMPLIED VOLATILITY; RETURN VOLATILITY; PRICE SHOCKS; GARCH MODELS; MARKETS; STOCK; ACCURACY; IMPACT;
D O I
10.1007/s00181-017-1294-6
中图分类号
F [经济];
学科分类号
02 ;
摘要
We forecast the realized volatility of crude oil futures market using the heterogeneous autoregressive model for realized volatility and its various extensions. Out-of-sample findings indicate that the inclusion of jumps does not improve the forecasting accuracy of the volatility models, whereas the "leverage effect" pertaining to the difference between positive and negative realized semi-variances can significantly improve the forecasting accuracy in predicting the short- and medium-term volatility. However, the signed jump variations and its decomposition couldn't significantly enhance the models' forecasting accuracy on the long-term volatility.
引用
收藏
页码:653 / 678
页数:26
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