Dynamic linkages among global oil market, agricultural raw material markets and metal markets: An application of wavelet and copula approaches

被引:64
作者
Jiang, Yonghong [1 ,3 ]
Lao, Jiashun [2 ]
Mo, Bin [1 ]
Nie, He [1 ]
机构
[1] Jinan Univ, Inst Finance, Guangzhou 510632, Guangdong, Peoples R China
[2] Jinan Univ, Dept Math, Coll Informat Sci & Technol, Guangzhou 510632, Guangdong, Peoples R China
[3] Univ Wisconsin, Dept Econ, Eau Claire, WI 54701 USA
关键词
Wavelet squared coherence; Copula; Tail dependence; Global oil market; Agricultural raw material markets; Metal markets; COMMODITY PRICES EVIDENCE; CRUDE-OIL; EXCHANGE-RATES; VOLATILITY; ENERGY; SHOCKS; SPILLOVERS; CAUSALITY; CORN; DEPENDENCE;
D O I
10.1016/j.physa.2018.05.092
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This paper aims to study the dynamic dependence among global oil market, agricultural raw material markets and metal markets. For this purpose, the wavelet squared coherence approach is used to capture the interdependence level and lag-lead relationship of three markets across time at different frequencies. We also combine wavelet and copula to analyze tail dependence among the three markets at different time-horizons. The results reveal that global oil market lags behind agricultural raw material markets but leads metal markets while metal markets change in parallel with agricultural raw material markets. In addition, the long-term linkages are stronger and more lasting than the corresponding short-term ones. The results also suggest that the dependence structure changes over time and the financial crisis has a great shock to the degree of dependencies among the three markets. All of these results are not only beneficial to optimize asset allocation and risk management for investors, but also play significant roles in maintaining the stability of the financial market. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:265 / 279
页数:15
相关论文
共 47 条
[1]   The role of outliers and oil price shocks on volatility of metal prices [J].
Behmiri, Niaz Bashiri ;
Manera, Matteo .
RESOURCES POLICY, 2015, 46 :139-150
[2]   The substitutive effect of biofuels on fossil fuels in the lower and higher crude oil price periods [J].
Chang, Ting-Huan ;
Su, Hsin-Mei .
ENERGY, 2010, 35 (07) :2807-2813
[3]   Modeling the relationship between the oil price and global food prices [J].
Chen, Sheng-Tung ;
Kuo, Hsiao-I ;
Chen, Chi-Chung .
APPLIED ENERGY, 2010, 87 (08) :2517-2525
[4]   Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis [J].
Du, Xiaodong ;
Yu, Cindy L. ;
Hayes, Dermot J. .
ENERGY ECONOMICS, 2011, 33 (03) :497-503
[5]  
Dutta A., 2017, RESOUR POLICY
[6]   Do oil prices drive agricultural commodity prices? Evidence from South Africa [J].
Fowowe, Babajide .
ENERGY, 2016, 104 :149-157
[7]   ON THE RELATION BETWEEN THE EXPECTED VALUE AND THE VOLATILITY OF THE NOMINAL EXCESS RETURN ON STOCKS [J].
GLOSTEN, LR ;
JAGANNATHAN, R ;
RUNKLE, DE .
JOURNAL OF FINANCE, 1993, 48 (05) :1779-1801
[8]   Application of the cross wavelet transform and wavelet coherence to geophysical time series [J].
Grinsted, A ;
Moore, JC ;
Jevrejeva, S .
NONLINEAR PROCESSES IN GEOPHYSICS, 2004, 11 (5-6) :561-566
[9]  
Hkiri B., 2016, APPL ECON, V48, P1
[10]   Dependence and risk management in oil and stock markets. A wavelet-copula analysis [J].
Jammazi, Rania ;
Reboredo, Juan C. .
ENERGY, 2016, 107 :866-888