TY - JOUR
T1 - Portfolio management and dependencies among precious metal markets
T2 - Evidence from a Copula quantile-on-quantile approach
AU - Al-Yahyaee, Khamis Hamed
AU - Mensi, Walid
AU - Maitra, Debasish
AU - Al-Jarrah, Idries Mohammad Wanas
N1 - Publisher Copyright:
© 2019
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/12
Y1 - 2019/12
N2 - This study examines the dependence structure among four major precious metal markets: gold, palladium, platinum, and silver. Using the novel Copula Quantile-on-Quantile Regression (C-QQR) approach of Sim (2016), we show that precious metals share a systemic relationship despite their different demand-supply interplays, applications, and the macroeconomic factors, which influence their values. Our results also suggest that correlations among markets do not remain constant over time. Furthermore, we identify the quantiles of returns for two metals where maximum benefits of negative correlations can be obtained to enhance portfolio diversification. This knowledge provides an opportunity for hedgers to decide when they should avoid going long or short on a particular metal. Finally, we find that our approach determines optimal portfolio weights that can reduce risk in metals markets more efficiently than traditional, conditional covariance-based approaches.
AB - This study examines the dependence structure among four major precious metal markets: gold, palladium, platinum, and silver. Using the novel Copula Quantile-on-Quantile Regression (C-QQR) approach of Sim (2016), we show that precious metals share a systemic relationship despite their different demand-supply interplays, applications, and the macroeconomic factors, which influence their values. Our results also suggest that correlations among markets do not remain constant over time. Furthermore, we identify the quantiles of returns for two metals where maximum benefits of negative correlations can be obtained to enhance portfolio diversification. This knowledge provides an opportunity for hedgers to decide when they should avoid going long or short on a particular metal. Finally, we find that our approach determines optimal portfolio weights that can reduce risk in metals markets more efficiently than traditional, conditional covariance-based approaches.
KW - Copula quantile-on-quantile
KW - Hedging
KW - Precious metal markets
KW - Tail dependence
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U2 - 10.1016/j.resourpol.2019.101529
DO - 10.1016/j.resourpol.2019.101529
M3 - Article
AN - SCOPUS:85074338864
SN - 0301-4207
VL - 64
JO - Resources Policy
JF - Resources Policy
M1 - 101529
ER -