Asymmetric and time-frequency volatility connectedness between China and international crude oil markets with portfolio implications

被引:9
作者
Liu, Zhenhua [1 ]
Ji, Qiang [2 ,3 ]
Zhai, Pengxiang [4 ]
Ding, Zhihua [1 ]
机构
[1] China Univ Min & Technol, Sch Econ & Management, Xuzhou 221116, Peoples R China
[2] Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing 100049, Peoples R China
[4] Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Oil market Time-frequency domain Volatility spillovers High-frequency data Trading strategy; IMPULSE-RESPONSE ANALYSIS; INDEX FUTURES MARKETS; QUANTILE COHERENCY; STOCK MARKETS; TRANSMISSION; SPILLOVERS; INTEGRATION; PRICES; SHOCKS; RISK;
D O I
10.1016/j.ribaf.2023.102039
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper tries to examine asymmetric and time-frequency volatility connectedness between the Chinese crude oil futures market and international oil benchmarks. To this end, we separate the realized volatility as bad or good volatility and decompose the aggregate volatility connectedness among these oil markets into the short-, medium-, and long-term components. Our results first show that these crude oil markets are highly connected, whereas the Chinese crude oil futures market is a net receiver in the volatility system. Second, the spillover effect caused by bad volatility is significantly different from that of good volatility, revealing significant asymmetry in the volatility spillovers. Third, the volatility spillovers in the short-term frequency band account for the most of total volatility spillovers. Finally, our results prove that the volatility connectedness information among different oil markets helps design trading strategies and shed light on the arbitrage opportunities in the Chinese new crude oil futures market.
引用
收藏
页数:22
相关论文
共 91 条
[1]  
Adelman M.A., 1984, The Energy Journal, V5, P1
[2]   The influence of intraday seasonality on volatility transmission pattern [J].
Alemany, N. ;
Arago, V. ;
Salvador, E. .
QUANTITATIVE FINANCE, 2019, 19 (07) :1179-1197
[3]  
[Anonymous], Xinhua
[4]  
Bachmeier LJ, 2006, ENERG J, V27, P55
[5]  
Barndorff-Nielsen O.E., 2010, VOLATILITY TIME SERI
[6]   Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets [J].
Barunik, Jozef ;
Kocenda, Evzen .
ENERGY JOURNAL, 2019, 40 :157-174
[7]   Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk [J].
Barunik, Jozef ;
Krehlik, Tomas .
JOURNAL OF FINANCIAL ECONOMETRICS, 2018, 16 (02) :271-296
[8]   Asymmetric connectedness on the US stock market: Bad and good volatility spillovers [J].
Barunik, Jozef ;
Kocenda, Evzen ;
Vacha, Lukas .
JOURNAL OF FINANCIAL MARKETS, 2016, 27 :55-78
[9]   Volatility Spillovers Across Petroleum Markets [J].
Barunik, Jozef ;
Kocenda, Evzen ;
Vacha, Lukas .
ENERGY JOURNAL, 2015, 36 (03) :309-329
[10]   Price and volatility spillovers across the international steam coal market [J].
Batten, Jonathan A. ;
Brzeszczynski, Janusz ;
Ciner, Cetin ;
Lau, Marco C. K. ;
Lucey, Brian ;
Yarovaya, Larisa .
ENERGY ECONOMICS, 2019, 77 :119-138