An oil futures volatility forecast perspective on the selection of high-frequency jump tests

被引:7
|
作者
Li, Xiafei [1 ]
Liao, Yin [2 ]
Lu, Xinjie [1 ,3 ]
Ma, Feng [1 ,3 ]
机构
[1] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu, Peoples R China
[2] Macquarie Univ, Dept Appl Finance, Sydney, Australia
[3] Serv Sci & Innovat Key Lab Sichuan Prov, Chengdu, Peoples R China
关键词
Oil futures volatility; Jump test selection; Volatility forecasting; HAR-RV-type models; High -frequency data; PRICE SHOCKS; STOCK; VARIANCE; MARKETS; MODELS; COMPONENT; IMPACT; NOISE; US;
D O I
10.1016/j.eneco.2022.106358
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper examines the forecasting performances of high-frequency jump tests for oil futures volatility from a comprehensive perspective. It contributes to the literature by investigating which jump test is the best for oil futures volatility forecasting under different circumstances and whether the jump component extracted from multiple alternative tests is useful for further improving forecasting performance. Our results show that the jumps of the TOD test (Bollerslev et al., 2013) have satisfactory performance over the medium-term and espe-cially the short-term forecasting horizons. Most importantly, the jump components from the intersection of multiple intraday tests further improve the forecasting performance. A variety of further discussions, including models controlling for stock market effects and considering periods of high (low) volatility and the COVID-19 pandemic period, confirm the conclusions. This paper attempts to shed light on oil futures volatility predic-tion from the perspective of jump test selection.
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页数:18
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